anti social behaviour causes and solutions essay

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IELTS Writing Task 2 Topic: There is a General Increase in Anti-Social Behaviours

Updated On Jan 10, 2024

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One of the various types of essays that can be asked in the IELTS Writing task 2 is a cause solution essay. The cause solution essay in IELTS requires candidates to talk about a certain causes and suggest possible solutions to the same.

Given below is an example of a cause & solution essay. Let’s understand how to frame the essay from the ideas we have.

TOPIC: There is a general increase in anti-social behaviours and a lack of respect for others. What are the causes and solutions? (IELTS Writing Test in Vietnam, 05/12/2015)

Cause-solution type essay

Introduction

• Paraphrase the statement of the topic and give a brief inside with one sentence for the same.
• State what can be expected in the forthcoming paragraphs ( possible causes and solutions)
• Paragraph 1: Causes. (People may hold an anti-social attitude or disrespect others because they live in an environment where violence and discrimination are the norms.) (As modern parents are becoming increasingly busy with their jobs, they may have the proclivity to be indifferent to children’s education.)
• Paragraph 2: Solutions. (On the national level, the first obvious solution is to reduce violence and discrimination. As this would be a massive act, all the voters and legislators should be responsible.) (On the nuclear-family level, parents must not underestimate the significance of their guidance for children. If they notice any signs of an anti-social or insolent manner in children, they must provide them with negative evaluations of these signs.)

Reparaphrase the question and give a concise reflection of cause and solution mentioned.

Sample Essay

The widespread problem of anti-social behaviours and disrespectful attitudes towards others has long been a major topic of concern in society. Some of the major culprits of this problem will be discussed before the most important solutions are drawn.

Reasons for this alarming situation vary. In some cases, people may hold an anti-social attitude or disrespect others because they live in an environment where violence and discrimination are the norms. For example, children of sexist parents in rural families in Vietnam, irrespective of their gender, show a worrying tendency of disrespecting women. In some other cases, it is the lack of parental guidance that is to blame. As modern parents are becoming increasingly busy with their jobs, they may have the proclivity to be indifferent to children’s education. When there is no one to help young children distinguish between the good and the bad, ill-mannered attitudes may emerge and develop among them without being controlled.

A number of definite actions could be taken to mitigate the problem. On the national level, the first obvious solution is to reduce violence and discrimination. As this would be a massive act, all the voters and legislators should be responsible. Together, they could call for stricter enforcement of the laws on violent and discriminatory acts to deter them from happening. Furthermore, on the nuclear-family level, parents must not underestimate the significance of their guidance for children. If they notice any signs of an anti-social or insolent manner in children, they must provide them with negative evaluations of these signs. At the same time, parents could also educate their children about social manners by instilling a pro-social sense in them. These actions, albeit small, could have a strong influence on children when they mature.

To conclude, it is clear that violence, discrimination, and the indifference of parents to children’s education are the major catalysts for the increase in anti-social behaviours and disrespect for others. Strong measures, such as stringent law enforcement on violent and discriminatory acts, must be taken to alleviate this distressing situation.

Band 9 Sample Essay

The pervading instances of apathy and vitriolic behaviour amongst each other have been a menace to society for a long time and that continues to grow even today. The possible causes and remedies have been touched upon in this essay.

The major reason and foundational cause of it are born with the way one’s upbringing is subjected to, at large. The seed of rancour often germinates in childhood itself. Reports have suggested that children brought up in a toxic environment and violent households are twice as much imperilled to grow as individuals which may by the conventional definitions and boundaries, be called as having anti-social tendencies. Similarly, being subjected to bully or snide remarks all through the process of being grownup have reportedly been suggestive of laying the baselines of rancorous demeanours and hence, asocial personalities. Another major reason could be reckless parenting, where children are often inclined towards learning what they discern from extrinsic factors including peer pressure. Then, the notorious and most pronounced cause, the unregulated graphic contents majority of the people, primarily children are seen to be persuaded by.

The possible remedies and preventive measures that could be taken in this regard shall be good and meticulous parenting. As is also said, “Childhood shows the man as the morning shows the day”, the early years of a person should be assiduously catered to. In schools and colleges, it is of prime importance to monitor the activities and be alert and cautious to any actions suggestive of discrimination or suppression. They should be handled strictly and apposite actions should be taken likewise. Workplaces likewise should be diligent enough in taking into notice such episodes of apathy and culprits should be dealt with with the rightful actions. Internal whistleblowers, anti-bullying squad and other associations likewise could be of immense help. Overlooking these matters and avoiding the same generally en route to something grave and hence, should be spoken out and reported as whatever the case may be.

Conclusively, the scourge of antisocial behaviour could only be contained when these issues are not  slipped under the rag of trivial matters.

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Explore other Problem Solution Essays

Nehasri Ravishenbagam

Janice Thompson

Kasturika Samanta

Post your Comments

Posted on Oct 31, 2021

Surge in anti-social behaviour towards peers has been the talk of the town. Be it a youngster or an old person, both tend to lack respect for others around them. Some daily life significant examples include seniors yelling at their junior colleagues at work places, kids yelling at parents to get their demands fulfilled, literates shouting at illiterates for their lack of knowledge. This attitude has created a friction between people further resulting in demise of relationships. The aftereffects affect not only personal life but also professional life leading to mental health issues. There are numerous reasons to support the rise in arrogance and egoistic nature of human beings. First, people have more educational qualifications as compared to the previous generations which is a factor of dominance. Another reason is tech-friendliness which majority of people have these days. But, still a minority prevails who isn’t able to operate each and every device or app. When they seek a solution from tech savvy people, they are often insulted. Last but not the least, having diverse educational qualification and the desired skillset for jobs, incomes of job aspirants or business owners have reached a phase where ‘sky is the limit’. The solutions to these problems are simple yet effective. Government and Multinational Corporations should introduce several schemes and programs wherein they provide courses in various aspects like personality development, language learning, computer and apps, public speaking and motivational mantras etc. This will not only build the morale of our fellow peers but also can efficiently contribute to the nation’s GDP. To conclude, one must treat others with dignity and love irrespective of their backgrounds. Nobody deserves to be ill treated or humiliated for any reason. We could inculcate the basic habits of saying the magic words- Please, Sorry and Thankyou and teach this habit to everyone around us. This could bring a massive change in the coming future.

Posted on Nov 1, 2021

Overall band score: 5.5

Coherence: You should put causes in one para and solutions in another para.

Posted on Oct 4, 2021

People are increasingly becoming anti-social and many lack respect for others. The major culprits of such behavior ought to be the social media and lack of parent supervision. This essay will outline these causes and possible ways to mitigate them.

With the advent of several social media platforms, children and adults have equally become addicted to them. Leading to lose interest in socializing and interacting with others directly. Furthermore, with the lack of social interaction young ones fail to learn and develop etiquette. On the other hand, absence of parents due to their busy jobs results in them being indifferent to their children’s manners. They fail to distinguish good from bad, causing the ill-mannered behavior. In a study, the behavioral pattern of kids raised by parents was thirty percent better with the ones raised under guardian supervision.

Social interactions and proper etiquette are essential for communal growth. Several measures can be taken to ensure them. Firstly, the access to social media applications should be time and age restricted. Parents could limit the internet bandwidth to lessen the usage. Secondly, family time should be encouraged to develop socializing skills. Additionally, behavioral lessons should be included in academics. These actions, although small, could have a strong influence on children when they mature.

To conclude, lack of mutual respect amongst people and reduced interest to socialize is increasing with the generation of the millennials. Majorly caused by addiction to virtual world and lack of guidance from parents. This could be mitigated reducing online life and increasing offline communication beginning within the family.

Prabhjeet kaur

Posted on Apr 15, 2021

Shall I post any essay answer in the comment section

Posted on Jul 20, 2021

Please post your answer. One of our IELTS Trainers will evaluate the answer and reply to your comment.

Nguyen Thu Ha

Posted on Feb 20, 2021

It is worrying that anti-social behaviors and disrespect towards others are on the increase. This essay will explain some reasons behind this trend together with possible measures. The most common cause for rude behaviors against others is the prolonged stress one has to face in our modern life. Not only do people work longer hours, but they also face greater work load or responsibility, let alone the financial burden when supporting a family. People have to compete nearly in everything they do, like finding a stand on the bus, securing a place for their kids in a good school or driving their vehicles through a congestion. This stress is the most common cause for ones to lose temper easily and act more violently than necessary. Nevertheless, we should not let outside factors erode our kindness and temperament but learn to adapt and relieve stress before it can build up. Taking up yoga or mediation, balancing between work and life are of great use to regain our self-control and positive mood. Secondly, the mass media has much to play in spreading the antisocial behaviors. Villains often upload the viral videos or pictures on the net to attract curiosity of the netizens, attaining their goals of more viewers and shares. The more one sees these videos or disturbing images, the more likely they regard these acts as norms. This is especially true for the young who are quite impressionable and mimic what they see with little critical thinking. It is easy to find teenagers using vogue language prevalently either online or offline. It is high time parents and guardians monitor what their children access to on the net and properly guide them to better exploit the virtual means. Besides, the administrators of these platforms such as Facebook or Twitters should clearly label and eliminate malicious contents to keep users safer on the net. In conclusion, the prevalence of rudeness and violence in modern society can be attributed to the increasingly stressful life and the ubiquity of bad contents commonly seen in various media sites. It is therefore strongly recommended that each individual learn how to alleviate stress and lead a more balanced life. In terms of the impact brought by the media, people should be selective in what they see or read while web managers should strictly alleviate wicked content put on their platforms.

Blessed Onothoja

Posted on May 29, 2017

The rise in poor moral behaviours among people has attracted lot of concern. This may be a result of several challenges faced by individuals. There are a number of solutions to these problems.

Firstly, disrespectful attitude may be a result of poor or no moral tutolage at the development stage of children. Modern society has brought with it the struggle for survival which leave parents with little or no time to teach their wards the different between good and bad and correct them appropriately when they default. When schools are also too busy with their curriculum, the children are left at the mercy of society. This children may grow up not being able to demonstrate proper morals.

Secondly, improper morals may be birthed from a society of hate and violence. When people breed hate for each other, there hearts will always devise strategise for war, and mutual respect will be totally absent. For instance, the violence in the southern part of Nigeria in 1999 led to many losing their lives until the intervention of the government.

There are a good number of solutions to these challenges. Parents should consider their children as the future and always incorporate them into their daily schedule. In addition, moral teachings should be part of school’s curriculum at children developmental stages. Lastly, the issue of violence should be addressed by inacting and enforcing laws against violence and promoting mediums that will foster peace in our society.

In conclusion, with the measures discussed, the issue of moral disfunctional behaviour can be addressed and reduced in the society.

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There is a General Increase in Anti-Social Behaviour Essay

There is a general increase in anti-social behaviour & disrespect – ielts essay.

Many people think that there is a general increase in anti-social Behaviour and disrespect for others. What do you think,

what are the reasons for this and how to fix the situation? OR What might have caused this situation? How to improve it?

This essay was asked on 28th August, 2021, Morning Slot, India .

There is a General Increase in Anti-Social Behaviour – IELTS Essay – Model Answer 1

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The widespread problem of anti-social behavior and disrespectful attitudes towards others has long been a major topic of concern in society. Some of the major culprits of this problem will be discussed before the most important solutions are drawn.

Reasons for this alarming situation vary. In some cases, people may hold an anti-social attitude or disrespect others because they live in an environment where violence and discrimination are the norms. For example, children of sexist parents in rural families in Vietnam, irrespective of their gender, show a worrying tendency of disrespecting women. In some other cases, it is the lack of parental guidance that is to blame. As modern parents are becoming increasingly busy with their jobs, they may have the proclivity to be indifferent to childhood education. When there is no one to help young children distinguish between the good and the bad, ill-mannered attitudes may emerge and develop among them without being controlled.

A number of definite actions could be taken to mitigate the problem. On the national level, the first obvious solution is to reduce violence and discrimination. As this would be a massive act, all voters and legislators should be responsible. Together, they could call for stricter enforcement of the laws on violent and discriminatory acts to deter them from happening. In addition, on the nuclear-family level, parents must not underestimate the significance of their guidance for children. If they notice any signs of an anti-social or insolent manner in children, they must provide them with negative evaluations of these signs. At the same time, parents could also educate their children about social manners by instilling a pro-social sense in them. These actions, albeit small, could have a strong influence on children when they mature.

To conclude, it is clear that violence, discrimination, and the indifference of parents to children’s education are the major catalysts for an increase in anti-social behavior and disrespect for others. Strong measures, such as stringent law enforcement on violent and discriminatory acts, must be taken to alleviate this distressing situation.

General Increase in Anti-Social Behaviour & Disrespect for others IELTS Essay – Model Answer 2

Nowadays, many people believe that crime and disrespect are on the rise in society. In this essay, I will look at the probable causes and solutions to cater these problems.

To begin with, television and virtual media should be seen as the main factors in the cultivation of violence among citizens. In other words, they strongly influence a person in the direction of terrible antisocial behavior and disrespect for each other. For example, television shows such as Game of Thrones that promote crime, bloodshed, and hatred are in high demand, especially among children, and set a negative example for them. The solution might be to control this content. Parents can control the channels their children watch, and the government can motivate a person to self-discipline as well as to engage in creative activities to build a healthy mind, which can be done by opening more gyms, parks, and recreational activities.

In addition, lack of proper education at a primitive stage can also be a major cause of crime and disrespect among people, especially among the younger generation. This is because proper schooling provides a better life and a sense of responsibility among members of the community, but lack of it leads the individual in the wrong direction. The main reason for the lack of adequate education is high school attendance fees, with the result that most people cannot even finish high school. The solution to this problem is free education for everyone. For instance, Canada and Germany provide their citizens with free education and scholarships, which leads to low crime rates in their countries, and also contributes to the development of a civilized community. Therefore, by providing free education, it is possible to solve the problem of a high level of crime and uncivilization.

To conclude, by controlling content on television and on the Internet, either through self-control or by parents watching over their children, and by providing free education to everyone, the crimes and disrespect that are prevalent in society can be significantly reduced.

Anti-Social Behaviour Problem and Solution IELTS Essay – Model Answer 3

It is unfortunate that in the midst of vast progress in every field of life there is also a growth in anti-social behaviour and people have become less respectful of each other. This essay intends to analyze some causes of this phenomenon and suggests some ways to ameliorate the situation.

Today, we live in an era of technology in which the whole Earth has shrunk and become a global village. Everybody is connected to everybody through telephone lines and the Internet, but the warmth of relationships has taken a back seat. Most people have more than enough wealth, comfort, and freedom, but their hearts desire even more. To satisfy their hearts’ greed people have become workaholics, and as a result, have no time for family and friends. People have become selfish, isolated, and indifferent. Each person is busy in his own quest for more. To add to it, the youngsters who are at ease with the new technology think that the elderly are good for nothing and that is why they don’t respect them.

The changing family structure is another big cause of this phenomenon. Earlier, people lived in joint families and the grandparents were there to supervise the children. Now there are nuclear families in which both parents go out to work, and children are left unattended in the hands of pervasive media like the TV and the Internet. No one monitors what they watch and they see the programs full of violence and crime, which makes them anti-social. The pressure of consumerist society and peers also breeds anti-social behaviour. To add to it, the values of traditional culture are being lost and people are following the global culture, which is also considered anti-social by the orthodox elderly.

There are many solutions to this problem. To begin with, people have to learn to strike a balance between work and family life. Government should also fix the maximum hours a worker can work per week so that exploitation is not there in the job market. People should revert back to the old joint family system. This would be for the benefit of all. The children would learn moral values and the elderly would be well looked after. The negative effects of excessive consumerism should be taught to the people. Media can play a big role in highlighting the good points of the traditional and western culture so that the people can adopt good social values. Neighbourhood associations should be set up to connect people to each other.

Summing up, anti-social behaviour and mutual lack of respect in today’s times can be dealt with by taking simple measures, and individuals and governments should collectively take these steps.

Also Check:  Describe a town or city where you would like to live in the future

Ideas for Anti-Social Behaviour IELTS Essay

Check out this article: Impact of Family and Friends on Antisocial Adolescent Behavior

Social Media is making us Unsocial

Antisocial Behaviours and The Thoughts that Cause them

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6 minute read

Antisocial Behavior

Causes and characteristics, treatment.

A pattern of behavior that is verbally or physically harmful to other people, animals, or property, including behavior that severely violates social expectations for a particular environment.

Antisocial behavior can be broken down into two components: the presence of antisocial (i.e., angry, aggressive, or disobedient) behavior and the absence of prosocial (i.e., communicative, affirming, or cooperative) behavior. Most children exhibit some antisocial behavior during their development, and different children demonstrate varying levels of prosocial and antisocial behavior. Some children may exhibit high levels of both antisocial and prosocial behaviors; for example, the popular but rebellious child. Some, however, may exhibit low levels of both types of behaviors; for example, the withdrawn, thoughtful child. High levels of antisocial behavior are considered a clinical disorder. Young children may exhibit hostility towards authority, and be diagnosed with oppositional-defiant disorder . Older children may lie, steal, or engage in violent behaviors, and be diagnosed with conduct disorder . Mental health professionals agree, and rising rates of serious school disciplinary problems, delinquency, and violent crime indicate, that antisocial behavior in general is increasing. Thirty to 70% of childhood psychiatric admissons are for disruptive behavior disorders, and diagnoses of behavior disorders are increasing overall. A small percentage of antisocial children grow up to become adults with antisocial personality disorder , and a greater proportion suffer from the social, academic, and occupational failures resulting from their antisocial behavior.

Causes and characteristics

Factors that contribute to a particular child's antisocial behavior vary, but usually they include some form of family problems (e.g., marital discord, harsh or inconsistent disciplinary practices or actual child abuse , frequent changes in primary caregiver or in housing, learning or cognitive disabilities, or health problems). Attention deficit/hyperactivity disorder is highly correlated with antisocial behavior. A child may exhibit antisocial behavior in response to a specific stressor (such as the death of a parent or a divorce ) for a limited period of time, but this is not considered a psychiatric condition. Children and adolescents with antisocial behavior disorders have an increased risk of accidents, school failure, early alcohol and substance use, suicide , and criminal behavior. The elements of a moderate to severely antisocial personality are established as early as kindergarten. Antisocial children score high on traits of impulsiveness, but low on anxiety and reward-dependence—that is, the degree to which they value, and are motivated by, approval from others. Yet underneath their tough exterior antisocial children have low self-esteem .

A salient characteristic of antisocial children and adolescents is that they appear to have no feelings. Besides showing no care for others' feelings or remorse for hurting others, they tend to demonstrate none of their own feelings except anger and hostility, and even these are communicated by their aggressive acts and not necessarily expressed through affect . One analysis of antisocial behavior is that it is a defense mechanism that helps the child to avoid painful feelings, or else to avoid the anxiety caused by lack of control over the environment .

Antisocial behavior may also be a direct attempt to alter the environment. Social learning theory suggests that negative behaviors are reinforced during childhood by parents, caregivers, or peers. In one formulation, a child's negative behavior (e.g., whining, hitting) initially serves to stop the parent from behaving in ways that are aversive to the child (the parent may be fighting with a partner, yelling at a sibling, or even crying). The child will apply the learned behavior at school, and a vicious cycle sets in: he or she is rejected, becomes angry and attempts to force his will or assert his pride, and is then further rejected by the very peers from whom he might learn more positive behaviors. As the child matures, "mutual avoidance" sets in with the parent(s), as each party avoids the negative behaviors of the other. Consequently, the child receives little care or supervision and, especially during adolescence , is free to join peers who have similarly learned antisocial means of expression.

Different forms of antisocial behavior will appear in different settings. Antisocial children tend to minimize the frequency of their negative behaviors, and any reliable assessment must involve observation by mental health professionals, parents, teachers, or peers.

The most important goals of treating antisocial behavior are to measure and describe the individual child's or adolescent's actual problem behaviors and to effectively teach him or her the positive behaviors that should be adopted instead. In severe cases, medication will be administered to control behavior, but it should not be used as substitute for therapy. Children who experience explosive rage respond well to medication. Ideally, an interdisciplinary team of teachers, social workers, and guidance counselors will work with parents or caregivers to provide universal or "wrap-around" services to help the child in all aspects of his or her life: home, school, work, and social contexts. In many cases, parents themselves need intensive training on modeling and reinforcing appropriate behaviors in their child, as well as in providing appropriate discipline to prevent inappropriate behavior.

A variety of methods may be employed to deliver social skills training, but especially with diagnosed antisocial disorders, the most effective methods are systemic therapies which address communication skills among the whole family or within a peer group of other antisocial children or adolescents. These probably work best because they entail actually developing (or redeveloping) positive relationships between the child or adolescent and other people. Methods used in social skills training include modeling, role playing, corrective feedback, and token reinforcement systems. Regardless of the method used, the child's level of cognitive and emotional development often determines the success of treatment. Adolescents capable of learning communication and problem-solving skills are more likely to improve their relations with others.

Unfortunately, conduct disorders, which are the primary form of diagnosed antisocial behavior, are highly resistant to treatment. Few institutions can afford the comprehensiveness and intensity of services required to support and change a child's whole system of behavior; in most cases, for various reasons, treatment is terminated (usually by the client) long before it is completed. Often, the child may be fortunate to be diagnosed at all. Schools are frequently the first to address behavior problems, and regular classroom teachers only spend a limited amount of time with individual students. Special education teachers and counselors have a better chance at instituting long-term treatment programs—that is, if the student stays in the same school for a period of years. One study showed teenage boys with conduct disorder had had an average of nine years of treatment by 15 different institutions. Treatments averaged seven months each.

Studies show that children who are given social skills instruction decrease their antisocial behavior, especially when the instruction is combined with some form of supportive peer group or family therapy . But the long-term effectiveness of any form of therapy for antisocial behavior has not been demonstrated. The fact that peer groups have such a strong influence on behavior suggests that schools that employ collaborative learning and the mainstreaming of antisocial students with regular students may prove most beneficial to the antisocial child. Because the classroom is a natural environment, learned skills do not need to be transferred. By judiciously dividing the classroom into groups and explicitly stating procedures for group interactions, teachers can create opportunities for positive interaction between antisocial and other students.

See also Antisocial personality disorder ; Conduct disorder ; Oppositional-defiant disorder ; Peer acceptance

Further Reading

Evans, W. H., et al. Behavior and Instructional Management: An Ecological Approach. Boston: Allyn and Bacon, 1989.

Landau, Elaine. Teenage Violence . Englewood Cliffs, NJ: Julian Messner, 1990.

McIntyre, T. The Behavior Management Handbook: Setting Up Effective Behavior Management Systems . Boston: Allyn and Bacon, 1989.

Merrell, K. W. School Social Behavior Scales . Bradon, VT: Clinical Psychology Pub. Co., 1993.

Redl, Fritz. Children Who Hate : The Disorganization and Breakdown of Behavior Controls. New York: Free Press, 1965.

Shoemaker, Donald J. Theories of Delinquency: An Examination of Explanations of Delinquent Behavior , 2nd ed. New York: Oxford UP, 1990.

Whitehead, John T. and Steven P. Lab. Juvenile Justice: An Introduction. Cincinnati, OH: Anderson Pub. Co., 1990.

Wilson, Amos N. Understanding Black Adolescent Male Violence: Its Prevention and Remediation. Afrikan World Infosystems, 1992.

Additional topics

• Antisocial Personality Disorder - Treatment
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Psychology Encyclopedia Diseases, Disorders & Mental Conditions

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Rebuilding Communities: Why It’s Time to Put Anti-Social Behaviour Back on the Agenda

Paper 26th April 2022

Harvey Redgrave

Anti-social behaviour is often written off as a “low-level” nuisance and therefore considered less deserving of political attention than other types of criminality. 

This is a mistake. The way to think about anti-social behaviour is not as a series of isolated incidents but as a pattern of behaviour that is almost always repetitive and oppressive, often directed at victims who are vulnerable and live in more deprived areas, and is often a prediction of more serious offending later down the line. 

That is why I have always believed that a proper policy response to anti-social behaviour is fundamentally a question of social justice: it is about trying to rebalance the system so that it protects those who are least likely to be equipped with the resources to deal with it themselves.

Our approach in government was informed by a profound but simple insight: that our criminal justice system, which has evolved around the principle of protecting the rights of the accused, is woefully ill equipped for dealing with anti-social behaviour.

Of course, many of the behaviours we wanted to stamp out – aggressive drunkenness, drug-dealing and vandalism – were and have long been criminal offences. In theory, each case can be dealt with by the criminal-law process: the police bring a charge, the CPS prosecutes and the court passes a sentence.

But as anyone who works in this area knows, that isn’t what happens in practice. In the real world, so-called low-level crimes are never prosecuted because the sheer weight of process required to secure a conviction means it is just not worth the police hours and resources. 

That is why we expended so much capital on dealing with the issue: equipping local agencies with new enforcement powers; ensuring intensive support was available to the most troubled and chaotic families; and, most importantly, guaranteeing that every community would have access to a neighbourhood policing team. 

Harvey’s paper details how, during the past decade, much of the architecture that had been established has since been progressively diluted, with powers weakened and visible local policing scaled back. In addition, incidents of anti-social behaviour appear to have been recategorised as public-order offences, further diminishing their significance.

Do not misunderstand me: this is not about going back to the past. What was right for then won’t necessarily be right for today. Problems evolve and so must the policy response.

But what this paper illustrates is a fundamental lack of direction at the top of government. What are the principles that guide this government’s approach to anti-social behaviour? What are the signature policies? It is fine to argue that anti-social behaviour is a local issue but without a push from the centre, there isn’t enough pressure in the system and you end up with drift.

The impact is well documented here: a stark decline in public confidence in the police and the shocking finding that only a quarter of people who experience anti-social behaviour say they have bothered to report it. Our system relies on the consent and cooperation of victims and witnesses. Once they lose faith in it, the entire system risks grinding to a halt.

All of this speaks to what I perceive to be a bigger issue: a decline in law and order, which is seriously damaging our country. Unless people are able to live free of fear, the very possibility of life in a community is undermined. If there is a sense the social norms that bind us together are fraying – that rights have been divorced from obligations – and, worse, that the government is indifferent, this is when despair and bitterness set in. 

In time, I hope our paper will provide something of a turning point in the debate about anti-social behaviour and local policing.

Executive Chairman

Having previously been confined to academic debates within criminology, [_] the issue of anti-social behaviour (ASB) was thrust into the political limelight during the 1990s, partly in response to fears that the traditional mechanisms for dealing with such behaviour – family, religion and community – had been weakened.

In the UK, anti-social behaviour was defined in statute in 1998 as behaviour that was “likely to cause harassment, alarm or distress”. To date, no legislation has attempted to break down this broad definition or provide a list of specific behaviours. However, in practice the definition covers a wide range of actions from the dropping of litter on a street to the running of crack-houses.

Strong and secure communities are the essential foundation from which individual potential is realised, quality of life is maximised and other social and economic wellbeing is secured. What makes a strong community isn’t complicated: decent public services, welcoming physical environments and - perhaps most significantly – safety and the ability to live free from fear. Sadly, in too many parts of Britain today, there is a sense that these things have been eroded and undermined.

If this government has a single defining mission, it is to “level up” areas of the country that have previously been left behind. Of course, that is partly about economic reforms necessary for jobs and prosperity but, equally important, are improvements to public services, the public realm and action to tackle ASB and disorder, not least through visible and responsive local policing.

ASB has often been dismissed as “low-level crime”’ and thus less deserving of national policy attention. This is fundamentally mistaken. ASB is often experienced less as a series of isolated incidents and more as a pattern of repetitive behaviour that intensifies over time, causing misery and distress to its victims and the wider community. If left unchecked, it can spiral and turn into more serious crime. In short, a serious policy response to its manifestation would seem critical to any government seriously committed to levelling up areas of the country previously left behind.

Yet, for most of this decade, ASB has been all but ignored by this government, having fallen victim to the fallacy that since it is a “local issue”, it can be entirely delegated to local agencies and that central government has no role to play in tackling it. To make matters worse, neighbourhood policing has been quietly eroded. While many forces continue to deliver some version of neighbourhood policing, its level of resourcing, form and function look very different depending on where you happen to live. This has left the public confused about what they can expect from their local policing service.

We know that one of the issues most central to people’s sense of belonging and pride in the place in which they live is whether or not they feel safe from ASB and crime, and, relatedly, whether they feel able to call upon a strong local-policing presence. This paper sets out a route map for achieving this.

Key Findings

ASB remains an issue of huge public concern. New polling undertaken for this paper has found that a third of people surveyed (32 per cent) think ASB is a big problem where they live.

Despite making “levelling up” its defining mission, this government has been largely silent on ASB.

Its primary contribution was a single white paper entitled “Putting victims first” in 2012, which, if anything, diluted available enforcement powers while establishing a “community trigger” – a tool that few have heard of, let alone used.

At the same time, neighbourhood policing has been allowed to fall into decline, which appears to have dented public confidence. There is a clear correlation between people’s confidence in the police and the decline in visible neighbourhood policing.

Our polling also indicates that the majority of the surveyed public are not confident in how the police and local authorities respond to matters of ASB. Of those who experienced or witnessed ASB in the past year, only 26 per cent said they reported it and only 41 per cent were satisfied with the response they received.

When asked to choose which aspects of local policing matter most to them, the public clearly prioritise responsiveness and accessibility: the top priority is 999 calls being answered, followed by officers that are “approachable and friendly” and a “definite response to all reports of crime and ASB”.

Recommendations

The government should consult on a new local-policing contract, which sets out minimum levels of expectation on visibility, accessibility and responsiveness.

The Home Office should ensure that the police-officer-uplift programme is used to guarantee a minimum level of neighbourhood policing (measured as a proportion of the total workforce), designed around the principles outlined above.

A new white paper setting out a national framework for ASB response is needed. The Home Office should also commission an independent body to undertake a review of the effectiveness of the interventions and powers introduced in 2014, and consult with police officers and local-authority practitioners on the use of existing enforcement powers.

The government should publish guidance making clear that the following circumstances will trigger some kind of parenting or family-based intervention: children excluded from school, persistent truancy, a child found behaving anti-socially or committing crime, and parents themselves involved in drugs or crime.

Anti-social behaviour (ASB) was defined in 1998 as one that “caused or was likely to cause harassment, alarm or distress” although no legislation since has attempted to break down this definition any further. The Crime Survey for England and Wales (CSEW) measures people’s perceptions of levels of anti-social behaviour in their local area according to the following seven strands.

Teenagers hanging around on the streets.

Rubbish or litter lying around.

People using or dealing drugs.

Vandalism, graffiti and other deliberate damage to property.

People being drunk or rowdy in public places.

Noisy neighbours or loud parties.

Abandoned or burnt-out cars.

Local authorities too have adopted their own definitions of ASB, and these were often drawn up by Crime and Disorder Reduction Partnerships (CDRPs) set up after the Crime and Disorder Act 1998. Other examples of ASB include prostitution, hate crime, aggressive begging and illegal street trading.

Where Criminality and Anti-Social Behaviour Meet

ASB occupies the space where criminal and civil law overlap. The legal definition uses concepts from both. Much of what we consider to be anti-social could be covered by criminal law, but there are civil remedies too.

An array of criminal offences can apply to ASB: for example, graffiti can constitute criminal damage under section 1 of the Criminal Damage Act 1971 while being drunk and disorderly is an offence under section 91 of the Criminal Justice Act 1967. This has led some critics to argue that the concept of ASB is too broad and legally unnecessary.

However, criminal law can be a blunt tool. In practice, it has often been difficult to deal with low-level ASB through the courts either because the burden of proof cannot be reached or it is not in the public interest to do so. Therefore, civil and informal remedies are often more practical as a way to deal with the problem.

The Scale of the Problem

Evidence on ASB trends is mixed. The CSEW shows a marked decrease in people’s perceptions of ASB as a “very big” or “fairly big” problem over the past ten years. Overall, 7 per cent of people reported that ASB was a very big problem in 2019/2020 compared with 14 per cent in 2009/2010.

The percentage of people who say that ASB is a very big or fairly big problem has fallen since 2009/2010

Source: CSEW (year ending March 2020)

Similarly, the number of ASB incidents reported to the police has fallen over the past decade from 3.5 million incidents in 2009/2010 to 1.3 million incidents in 2019/2020.

These figures don’t tell the whole story, however. When asked about their direct experience of ASB, 40 per cent said they had experienced or witnessed such behaviour in their local area in 2019/2020. This was up from 27 per cent in 2014/2015.

Direct experiences of ASB have been on the rise in local areas since 2014/2015

Moreover, while reported incidents of ASB have fallen over the past decade, these figures should be treated with caution. Police officers report that many forces have reclassified ASB as public-order offences, with analysis revealing these offences have more than tripled since 2012/2013. As will be shown later in the paper, there is also evidence that a significant majority of the population do not report ASB at all.

Police-recorded public-order offences, which now incorporate some ASB, have more than tripled in England and Wales

Source: CSEW (year ending December 2020)

The Effects of the Pandemic

During the Covid-19 pandemic, reported incidents of ASB have increased significantly within England and Wales. In the year ending March 2021, the police recorded two million incidents, an increase of 48 per cent compared with the previous year. The largest increases correlated with some of the major lockdowns during both spring 2020 (for example, there was a 83 per cent rise in incidents between April and June 2020 compared with the same quarter in 2019) and January to March 2021. The Office for National Statistics (ONS) reported this was likely to “reflect the reporting of breaches to public-health restrictions”. [_]

Similarly, research undertaken by Crest Advisory and the Police Foundation about police demand during the pandemic found there was an increase in ASB incidents in comparison with other offences. During times outside the pandemic, ASB typically comprises between 8 and 9 per cent of all incident demand but it has increased to a peak of 17 per cent during the pandemic. [_] ASB spiked during the first lockdown and did not return to pre-pandemic levels until after March 2021, since when it has dipped. This is likely a reflection of the fact that most of us were restricted to our homes and therefore more likely to experience and witness such incidents.

Why It Matters

In recent years, ASB has received less focus as an issue of national political importance but there are several reasons why tackling it ought to be a priority for the government. First, minor crime and disorder are not only clear drivers of criminality and disorder but are also indicators of more serious, future crime, therefore affording an early opportunity to prevent it. Second, there is evidence that the level of ASB in a local area is one of the primary factors that determines people’s quality of life, wellbeing and sense of community. ASB, particularly when it is repeated during a prolonged period of time, can erode feelings of public safety and undermine community resilience. Third, ASB disproportionately affects the most vulnerable in society and so any effort to level up must take the issue seriously.

The Spreading of Disorder

Minor crime and ASB are drivers of additional crime and disorder. The consequences of this link for public policy are crucial because they show that intervening to reduce ASB is an opportunity to prevent more serious crime before it occurs. As far as back as 1982, social scientists James Q Wilson and George L Kelling theorised in their “Broken Windows” essay that if a window in a building is broken and left unrepaired, this will send “a signal that no one cares, and so breaking more windows costs nothing”. [_] They argued that unchecked minor crimes and signs of disorder would lead to more ASB and more serious crime and thus fixing small problems would avoid bigger problems occurring down the line.

A History of Broken Windows

The broken windows theory gained a number of prominent champions, including former Mayor of New York City Rudy Giuliani and former New York City Police Commissioner William Bratton. The latter’s “zero-tolerance” policing strategy coincided with a fall of 36 per cent in serious-crime rates in New York.

Many social scientists subsequently attacked the theory, [_] arguing that this fall could have been a direct result of other factors including demographic changes, the slowdown in the crack-cocaine epidemic and economic initiatives that coincided with the zero-tolerance policing tactics (combined with consistent attempts to remove signs of disorder) that had also been developed by the theory’s proponents.

However, a 2008 empirical-research study conducted in the Netherlands appeared to add weight to the theory, finding that people became more disobedient in environments plagued by litter and graffiti. They would be more tempted to trespass, drop litter and even steal money if they perceived it was okay to break the rules from within the environment. The authors of the study concluded: “There is a clear message for policymakers and police officers: Early disorder diagnosis and intervention are of vital importance when fighting the spread of disorder.” [_]

More recently, a systematic review in 2015 by Anthony Braga, Brandon Welsh and Cory Schnell found that policing strategies focused on disorder had a statistically significant (if modest) impact on reducing all types of crime. However, the authors stressed this positive effect was driven more by place-based, problem-oriented interventions, such as hotspot policing, than by interventions targeting individual disorderly behaviour. [_]

To this day, the evidence base around broken windows remains contested. However, the weight of evidence would suggest there is a statistically significant effect from policing disorder.

Most criminologists and social scientists agree the onset of criminality is often preceded by ASB, which can manifest in different ways. For example, a drug gang taking over a property to sell drugs generates a great deal of ASB in the immediate term and is also likely to be a predictor of serious violence, as documented in our previous paper .

The link between ASB and crime is also supported by evidence from police-recorded crime statistics, which show that areas with the highest-reported disorder are correlated with areas of highest actual criminal activity.

Comparing the rate of recorded crime (per 1,000 people) with level of public-order offences per police-force area (2021)

Source: ONS

Quality of Life and Community Wellbeing

Not only does minor crime and disorder fuel further crime and disorder, it also sends a signal to the community that the local area is unsafe. While certain minor crimes may be considered less severe in the traditional sense, their accumulated impact on the public’s perceived risk of being a victim of crime may be far more pronounced. This phenomenon, which has become known as the “signal crimes perspective”, [_] describes this type of crime as any criminal incident that brings about a change in the public’s behaviour and/or their beliefs about their own security. A signal disorder is an act that breaches normal conventions of social order and signifies the presence of other risks. A signal disorder may be social, for example noisy youths, or physical, such as vandalism.

There is also evidence that rising ASB is contributing to the decline of connection and belonging within communities. In a 2021 report by Power to Change, it was noted that signs of neighbourhood decline such as empty buildings could contribute towards a “downward spiral of crime, anti-social behaviour and a loss of pride in place”. [_] Similarly, polling conducted for a 2022 report by the think-tank Onward revealed that when people were asked why local pride had declined in their area, the most popular response was a rise of 43 per cent in ASB. [_]

Considering the strong connection between ASB and how people feel about the community in which they live, it is all the more surprising that the government’s white paper on “Levelling Up the United Kingdom” contained such little focus on the issue.

ASB Affects the Most Vulnerable

Dealing with ASB is a question of social justice. The people most likely to be victims tend to live in the most deprived communities. In the figure below, we map reported concern about ASB against household income to show how people in the lowest-income decile groups are almost three times as likely as those in the highest to be concerned.

Percentage of respondents indicating high levels of awareness of ASB versus their household incomes

Anti-social behaviour (ASB) has not been central to this government’s law and order agenda. This has been reflected in the lack of political attention the issue has received, certainly when compared to the previous decade.

In early 2022, the government published its long-awaited white paper, “Levelling Up the United Kingdom”, which attempted to put flesh on the bones of what many have perceived to be the central mission of this administration. However, the white paper was primarily focused on reforms to boost economic productivity and skills rather than to reduce and crime. Aside from the already announced police officer uplift, a £50 million Safer Streets Fund administered to Police and Crime Commissioners appeared to be the sole and tangible policy pledge for dealing with ASB. This funding equates to less than £1,500 for every neighbourhood in England and Wales. [_] The white paper also sets what many will consider to be an unambitious target: to see neighbourhood crime fall by 2030.

The government clearly recognises the impact of ASB can be devastating for victims and the communities in which they live. However, ministers appear to have fallen victim to the fallacy that since ASB is primarily a "local" concern, it is purely a matter for local areas to deal with. In her foreword to the government’s 2012 “Putting victims first” white paper (to date, the only one specifically focused on ASB), former Home Secretary Theresa May made clear how she viewed the issue: “The mistake of the past was to think that the government could tackle antisocial behaviour itself. However, this is a fundamentally local problem that looks and feels different in every area and to every victim.”

This represents muddled thinking. It is true that ASB is a local issue, experienced in different ways by different communities, and that local practitioners are best placed to determine how to tackle it on the ground, rather than civil servants sitting in Whitehall. However, central government still has a responsibility to set the framework in which local areas operate – making clear what outcomes are expected as well as the levers and resources that will be made available to tackle the issue. However, no such framework has ever been set out.

Given the above, it is perhaps unsurprising that much of the architecture established over a decade ago has been subsequently diluted or dismantled. That architecture can broadly be divided into three parts: [_]

The establishment of local partnerships charged with preventing ASB.

Equipping local agencies with new enforcement powers designed to tackle persistent perpetrators.

Measures to turn around the lives of the most problematic families.

This chapter assesses recent developments against each of these three areas.

Local Partnerships

Successive governments have understood that partnerships are crucial in the fight against ASB. Crime and Disorder Reduction Partnerships (CDRPs) were introduced by the Labour government in 1998 to do just this. CDRPs placed local agencies under a statutory duty to cooperate in crime and disorder reduction in their local-authority area. Statutory partners included the police, the local authority, NHS, fire service, probation service and housing associations. Under the previous Labour government, the Home Office made funding available for every CDRP to employ a dedicated ASB coordinator to ensure the issue was properly reflected in the CDRP audit, that each partnership had a ASB strategy and it was delivered, and that a named person acted as a point of contact for central government.

Since 2010, CDRPs – or Community Safety Partnerships (CSPs) as they have been renamed – have ceased to be an effective mechanism for driving action on ASB. First, the focus of many CSPs began to shift away from ASB, edged out by newer competing priorities including the management of harm and vulnerability. [_] (This was also partly a consequence of the Home Office removing the expectation that local plans needed to include a focus on ASB.)

Second, this shift in focus coincided with a significant reduction in the resources allocated to and the relevance of CSPs. Much of their funding was rolled into the Police Main Grant and handed over to Police and Crime Commissioners so that they could deliver their police and crime plans over larger, police-force-level geographies.

The combination of funding insecurity (with cuts of up to 60 per cent to CSPs since 2010), staffing reductions in community-safety teams and the shift in strategic emphasis to the police-force level has left a mixed and fragmented national picture. Many CSPs have been left to wither away, unable to fulfil their statutory obligations. [_]

Enforcement Powers

A central insight by the previous Labour government was that the criminal-justice system was a blunt and largely ineffective instrument in the response to ASB. The nature of ASB – often involving repeated low-level harassment – means it is unlikely to secure a criminal conviction via the courts: a process that typically takes many months and requires a very high evidential standard of proof. Hence the desire to use alternative and swifter means, such as the civil system, to give local agencies new enforcement tools for tackling ASB. To that end, a range of new measures were introduced to punish perpetrators, including Anti-Social Behaviour Orders (ASBOs), parenting and dispersal orders, crack-house closure powers, fixed-penalty notices and other powers.

However, the Conservative-led government introduced new legislation in 2014 that aimed to “radically streamline” ASB-enforcement powers, reducing them from eighteen to six; replace the ASBO and its related orders with measures that more effectively addressed the offending behaviour of individuals; and create new mechanisms for victims to be more involved in the response, such as the “community trigger”.

Consolidating the Powers Available

Concerned that the powers to tackle ASB had become too complex, the government proposed the creation of six new ones to absorb the 18 that existed at the time.

How ASB enforcement powers were consolidated in 2014

Source: House of Commons Library

While the objectives – both to consolidate powers and to provide greater flexibility to agencies on the front-lines – had a clear logic, the lack of a clear national framework for implementing these new powers is likely to have impeded their effectiveness. The government removed any requirement for those implementing enforcement to share any information on their use of the new powers. As a result, there is no longer any centrally published and accredited data, which means we do not have an accurate picture of when and how these powers are being used or who is being affected by them across England and Wales.

Replacing the ASBO

The 2014 Anti-social Behaviour, Crime and Policing Act abolished the ASBO and in its place created a new civil injunction. There are two main differences between the two. First, breaching an ASB civil injunction does not constitute a criminal offence. Second, in addition to prohibiting the behaviours, civil injunctions can require individuals to take part in “positive requirements”, for example an alcohol-awareness course.

There were certainly valid criticisms of ASBOs from the speed of the process involved (sometimes, several months) to the relatively high number (around half) that were breached. Despite this, they were nonetheless clearly understood by the public and had become synonymous with a national desire to tackle the problem. The fact that a breach of an ASBO constituted a criminal offence allowed the system to send a strong signal about unacceptable norms of behaviour and the consequences that would follow.

It is far from clear that the civil injunction achieves similar levels of clarity and there are concerns that the dilution of criminal sanctions may have undermined levels of deterrence. [_] Again though, the lack of robust data on the use and efficacy of the new powers makes an objective assessment impossible.

New Ways for Victims to Influence Action

The government was concerned that in tackling ASB, local agencies did not adequately focus on the needs of victims and, too often, victims reported these problems without a response. To remedy that, the government introduced:

A new out-of-court disposal available to the police called the “community resolution” for which victims are provided an opportunity to influence how their perpetrator is punished.

A new duty on police, local authorities and some other partners to take action to deal with persistent ASB, known as the so-called community trigger.

Community resolutions were designed to give victims a say in how their perpetrator was punished but they have proved controversial. For example, the Magistrates Association has argued that they have resulted in inconsistent outcomes for perpetrators and victims, and these inconsistencies may undermine the legitimacy of the justice system. [_] A recent review of out-of-court disposals suggested there is a lack of data and oversight surrounding the use and effectiveness of community resolutions (despite their making up more than half of out-of-court disposals in England and Wales) while limited enforcement around the conditions set may have led to them being applied inappropriately and in ways that enhance the risk to victims. [_]

The community trigger was intended to provide a mechanism by which victims could require local services to review the handling of their ASB case. In line with ministers’ belief in flexibility locally, the legislation put a duty on local services to agree how to run the trigger and convey it to the local community. Research carried out by the charity ASB Help, however, has found that in practice very few local authorities or police forces have communicated this new power to the public, meaning that awareness of the trigger is low and many victims who would be entitled to activate it are unaware of its existence. Moreover, despite a legal requirement to publish annual data on the use of the trigger, many local authorities have failed to do so and there is confusion around the threshold (the number of complaints) required to activate it. The charity’s report concluded: “The community trigger has proved to be little more than a bureaucratic exercise, creating more paperwork, draining already tight public resources, and yet still not bringing desperately needed respite for victims.” [_]

With no national repository of good practice or learning, there are legitimate concerns about the quality of the entire process.

Troubled Families

One of the central pillars of Labour’s approach to ASB was creating and rolling out interventions targeted at the small number of challenging families responsible for a disproportionate share of that behaviour. Following the publication of the “Respect action plan” in 2006, a national network of Family Intervention Projects (FIPs) was established.

FIPs used an assertive and persistent style of working to challenge and support families to address the root causes of their behaviour whether through anger management, parenting support or addressing educational problems. There were different ways in which the service could be delivered: outreach support to families in their own home; support in temporary (non-secure) accommodation located in the community; and 24-hour support in a residential core unit where the family lived with project staff. Early evaluations showed that FIPs were successful in reduction: while 61 per cent of families were reported to have engaged in four or more types of ASB when they started working with a FIP, this had reduced to 7 per cent when they exited the project. [_]

As it turned out, this was the one part of the previous government’s ASB agenda that the Conservative government decided to build on, rather than dilute. Following the London riots in 2011, David Cameron made a pledge to “turn around the lives of the 100,000 most troubled families”. A new project called the Troubled Families Programme was established under the leadership of Louise Casey and underpinned by £400 million worth of investment, delivering a similar set of interventions. In 2019, when the programme was evaluated, the results were positive and showed statistically significant reductions in the proportion of families involved in ASB, following the intervention. [_] Since 2019, however, the programme has been rebranded and lost much of its original focus.

While the lack of data makes meaningful evaluation difficult, it is hard not to conclude that there been a weakening of policies to tackle ASB over a period of more than ten years. Local partnerships have become less effective, enforcement powers have been diluted (and less transparent) and, after an initial boost, interventions to deal with troubled families have lost focus. This is proven by data showing that the proportion of people who have confidence the authorities will take robust action on ASB has fallen since 2014/2015, after several years of steady rises.

Percentage of people who agreed that the police and the local council have been dealing with the ASB issues that matter in the local area

As ever, this is partly a story of declining resources. But equally, if not more, important has been the lack of focus and priority afforded to the issue of ASB by central government, which has removed an important pressure from the system particularly at a time when local agencies are facing competing demands.

In the next chapter, we assess how the government has fared on the other core plank of an ASB strategy: visible neighbourhood policing.

To a large degree, the government’s stance on neighbourhood policing has followed a similar pattern to its policies on anti-social behaviour (ASB): it is a matter for Police and Crime Commissioners rather than central government. In practice, this has led to a hollowing out of neighbourhood policing as experienced by local communities.

The modern history of neighbourhood policing in England and Wales started with the National Reassurance Policing Programme, which ran in 16 pilot sites between 2003 and 2005. The programme set out to address the “reassurance gap” or the mismatch between falling crime rates and the public’s perception that crime was going up. The approach drew on the “signal crimes” perspective, which held that specific but varying types of crime and disorder – including some incidents not traditionally considered “serious” – could disproportionately convey negative messages to individuals and communities about their security. The implication for the police was that by identifying and targeting the crimes with the strongest local signal values (particularly ASB at the time), they could reduce fear, improve confidence and reassure the public.

The programme was built on three principles:

Providing a visible and accessible policing presence.

Involving communities in identifying priority problems.

Tackling these in collaboration with other agencies and the community through a problem-solving approach.

Evaluation in the pilot sites showed that the approach improved public perceptions of how crime and ASB were dealt with, feelings of safety and confidence in the police. Although it had not been a specified aim, the programme was also found to have had a positive impact on crime, with survey measures showing a decline in victimisation in the community.

Prior to the 2005 general election, the Labour government pledged to ensure that every area in England and Wales would have a dedicated neighbourhood policing team by 2008, supported by more than £50 million of ring-fenced funding and provision of 25,000 Police Community Support Officers (PCSOs). In hindsight, this proved to be the zenith of neighbourhood policing. What followed has been a period in which the concept of a universal neighbourhood-policing offer has been eroded.

In 2016, Her Majesty’s Inspectorate of Constabulary and Fire and Rescue Services (HMICFRS) found that while all forces still allocated at least some resources to the prevention of crime and ASB through neighbourhood teams, there was now considerable variation and inconsistency in how different forces deliver neighbourhood policing. Increasingly, forces had shifted to an integrated or hybrid model, whereby neighbourhood policing was being dissolved into general local policing and/or response policing (with neighbourhood teams used to service reactive demand). [_]

Similarly, in a 2018 report on neighbourhood policing, the Police Foundation documented how several forces had sought to balance competing demands by adopting a more general or hybrid approach in which local police officers performed both response and neighbourhood tasks. [_]

Given the funding pressures that police forces were facing, the shift to a hybrid model made sense from an efficiency perspective although it contained risks from an effectiveness perspective. There is consistent testimony from frontline police officers that a workload containing significant amounts of reactive police work is unsuited to also delivering core neighbourhood-policing activities, such as community engagement and partnership-working, which tend to be more proactive. [_] This is not only a matter of the time that reactive tasks take up but also their high unpredictability, which can in turn undermine efforts to make and keep appointments and commitments.

Realising the drawbacks of hybrid models, a number of forces have subsequently chosen to designate smaller, functionally discrete policing teams to neighbourhood or local preventative duties and to insulate them (partly or wholly) from reactive demand. However, the price of greater functional distinctiveness has been a further shift away from universal neighbourhood policing towards a more narrowly defined, targeted offer, for example one that is limited to high-risk areas.

The shift away from universal neighbourhood policing has been accelerated by a significant reduction in the share of PCSOs within the workforce, with the money diverted to employ more fully warranted officers.

The number of Police Community Support Officers (PCSOs) as a proportion of the total police workforce

Source: Home Office

Inevitably, given the shift in focus described above, there has been an erosion of the traditional outputs associated with neighbourhood policing: community engagement, visibility, community intelligence gathering, local knowledge and proactive prevention.

Variability

Our localised system of policing means that chief constables have a great deal of discretion over how to interpret the priority given to neighbourhood policing as well as the form and function it takes.

The data show a very mixed picture in terms of the resourcing and prioritisation of neighbourhood policing. This ranges from Avon and Somerset, which dedicates 2.5 per cent of its police officers to neighbourhood policing, to Wiltshire, which allocates 51 per cent. In total, there are now 24 forces that allocate less than 10 per cent of their police officers to neighbourhood policing – more than double the nine forces that did so in 2012. [_]

Number of neighbourhood police officers per 10,000 people (2021)

Source: Home Office, Police Workforce

Over the past decade, neighbourhood policing has encompassed a broader and more varied set of practices than was the case in 2008. In a 2018 report, [_] the Police Foundation documented some of the ways in which that diversity manifested itself:

Workforce mix: Some forces (for example, those in rural areas) delivered neighbourhood policing by relying on PCSOs while others had reduced this proportion and chosen instead to depend on fully warranted officers

Scope of provision: While a small number of forces attempted to retain a universal offering, most forces sought to deliver a narrower, more targeted offer, for example by focusing on areas of the highest risk.

Focus: Some forces continued to approach neighbourhood policing in traditional terms, in other words, largely focused on community engagement, visibility and reassurance, while others sought to define it more broadly, encompassing “harm reduction” and the management of vulnerability.

Partially in response to some of these concerns, the College of Policing published guidance on the delivery of neighbourhood policing in 2019. [_] However, these guidelines “embed a version of neighbourhood policing predominantly oriented towards crime and demand reduction”. [_] This represents a fundamental change in direction from the original premise of neighbourhood policing, which was a distinct (and universal) specialism focused on reassurance, legitimacy and cooperation. As will become apparent in the next chapter, it is far from clear whether this shift is aligned with the public’s priorities.

Impact on Public Confidence

Until the mid-2000s, public confidence in the police service – as measured by the Crime Survey for England and Wales (CSEW) – remained remarkably stable, with approximately half of British adults rating their local policing as, at least, “good”. Between 2006 and 2016, public confidence rose significantly before it started to decline.

Levels of overall public confidence in the police begin declining from 2017

What might explain this recent fall in confidence? One possible explanation is that policing has become less visible, with fewer officers on the streets. As the figure below demonstrates, this appears to be reflected by trends in public perception, which show a similar pattern to the confidence data (perceptions of police visibility rise in the mid-2000s before falling back, albeit before the fall in public confidence).

Percentage of people who said they saw foot patrols on the streets once a week or more (visibility)

In addition to declining visibility, another driver of falling confidence would be the belief that the police are less responsive to local concerns. Again, data suggest this is indeed the case, with a decline in the number of people reporting both that the police understand and deal with local concerns since 2014/2015.

Figure 12 – Percentage of people who believe that the police understand and deal with local concerns (responsiveness)

One can see a similar pattern in the number of officers in neighbourhood roles, with a dramatic fall since 2015/2016. In Michael Barber’s “Strategic Review of Policing in England and Wales”, an explicit connection is made between trends in public confidence, perceptions of police visibility and the rollout of neighbourhood policing. [_] Of course, correlation does not equate to causation but the consistency of the trends is striking. This interpretation would also be consistent with research showing links between public confidence and police visibility, and with the overall number of police officers. [_]

The number of police officers in neighbourhood policing roles in England and Wales has fallen recently from a peak in 2015/2016

Sufficient international evidence confirms that visible and accessible policing can “have positive effects on citizen satisfaction, perceptions of disorder and police legitimacy”. [_] For example, one recent randomised control trial in the United States concluded that a “single instance of positive contact with a uniformed police officer can substantially improve public attitudes toward police, including legitimacy and willingness to cooperate”. [_]

Public Satisfaction Is Down

Analysis of attitudinal data captured by the CSEW reveals that the weakening of policy on ASB combined with the erosion of neighbourhood policing has undermined the public’s confidence. Since 2014/2015, when the Anti-social Behaviour, Crime and Policing Act was introduced and neighbourhood policing numbers began to substantially decline, there have been noticeable falls in the number of people reporting the following:

Confidence that their local police and council were focusing on the ASB and crime issues that matter.

The visibility of the local police patrol.

That the police understand and deal with local concerns.

There are other data to support these trends. For example, the proportion of incidents in which victims were satisfied with the police has fallen over the past decade (from 37 per cent to 32 per cent). [_]

While these figures tell us what the public are unhappy about, they don’t necessarily tell us what the public want to see. That is the subject of the next chapter.

To inform our research, the Tony Blair Institute commissioned a public poll from JL Partners asking people about the scale of the anti-social behaviour (ASB) problem, how well they think local services deal with it and their priorities for local policing. The findings provide stark reading for the government.

Our survey confirms that ASB is of significant concern to the British public. When asked about the scale of the problem in their local area, around a third (32 per cent) of respondents identify it as a “big problem” where they live while more than three-quarters (81 per cent) say it is a problem of “some sort”.

Question to respondents: “Thinking about your experience of where you live, how big of a problem is anti-social behaviour?”

Source: JL Partners

The demographic group that appears most concerned about ASB is young people. Our findings reveal that 45 per cent of people aged between 18 and 24 believe it is a “big problem” in their area (compared with 32 per cent overall). This contrasts sharply with the experience of those aged over 65. Only 18 per cent of this demographic identify ASB as a “big problem”.

Question: “Thinking about your experience of where you live, how big of a problem is anti-social behaviour?” (Responses categorised by age group)

When we consider the regional differences, we see that the greatest concern is reported in London. Almost half the respondents (47 per cent) in the capital believe that ASB is a “big problem” where they live. This is higher than the national average (32 per cent) and contrasts sharply with people in the East of England region (where only 19 per cent recognise it as a big problem). Respondents in the North West (41 per cent) and North East (43 per cent) also identify ASB as a “big problem” in their local areas.

Reporting ASB and the Response of Local Services

More than four in ten respondents (42 per cent) report having had a direct experience of ASB in the past year, a similar level to the 40 per cent measured by the Crime Survey for England and Wales.

Question: “Have you personally experienced or witnessed ASB in the last 12 months?”

In terms of who the public have reported ASB to when they witnessed or experienced it during the past year, the survey shows that more than two-thirds (69 per cent) chose the police while less than half (43 per cent) went to their local authority.

However, when it came to reporting experiences of ASB, the levels were much lower. Only a quarter of people who experienced or witnessed it (26 per cent) reported it to the police or their local authorities. Low levels of reporting are most evident among the young people polled. Only 16 per cent of those aged under 25 who experienced an issue of ASB reported it, compared to 30 per cent of respondents aged between 45 and 54.

Of those who said that they had experienced or witnessed ASB in the last 12 months, the poll asked: “Did you report it?”

Of the people who did report issues of ASB, their experience and satisfaction with the outcome has been highly variable. Only 41 per cent of respondents were satisfied with the response they received while 39 per cent had an unsatisfactory experience. Of greater concern, more than a fifth (22 per cent) admitted they had been very unsatisfied with the response they had received.

Of those who did report ASB, the poll asked: “Were you satisfied with the response that you received after you reported the ASB?”

What the public would like to see from their local police.

In our survey, we asked respondents to prioritise (with a rank out of 10) the elements of local policing that matter most to them, along with an assessment of how well that service is currently being provided (also ranked out of 10).

When it comes to these priorities, “answering 999 calls rapidly” remains the most important aspect of the job (scoring an average of 8.6 out of 10 in terms of importance) according to respondents. This is followed by officers that are “approachable, friendly and professional” (8.1 out of 10) and then ensuring a “definite response to all reports of crime and ASB” and “keeping victims and witnesses informed about their case” (both scored 7.9 out of 10).

Two-part question: “Thinking about how the local police spend their time, 1) score the following in terms of how important it is to you” and 2) "score the following in terms how well you think it is provided by the police"

In terms of people’s perceptions of the level of service they currently receive, the police score best in terms of their response to 999 calls, with an average of 6.4 out of 10 on this task. However, the police score only 5.9 out of 10 on being approachable and friendly. More concerning, a very low proportion of the public feel that the police are doing a good job in providing a definite response on crimes and ASB (4.8 out of 10). The police score lowest with 4.1 out of 10 when it comes to a “visible presence on the streets”, a finding that chimes with the decline in neighbourhood policing we have already discussed.

Polling Backs Our Findings

This polling reinforces our central argument in this paper: in recent years, ASB has not received a great deal of political attention or media coverage but it is viewed by the public as a matter of serious public concern. The fact that such a low proportion of survey respondents (26 per cent) experiencing ASB report it to the authorities suggests a near-complete collapse in confidence in the system to deal with the problems. Our polling also confirms that the public would like to see a local police offering that is responsive, accessible and visible. The force is currently struggling to fulfil any of these objectives.

Polling: Sample Details

Polling conducted by JL Partners for the Tony Blair Institute looked at the importance of the issue of anti-social behaviour to the public, how likely they were to report it, and what they expect from the police. The polling was conducted among a representative sample of 2,024 adults from 4 to 5 April 2022 and weighted to be representative of the population of Great Britain.

Anti-social behaviour (ASB) is often seen as a low-level nuisance – a type of sub-crime – which is somehow less deserving of political attention than more serious offences. This is a mistake. While single incidents can seem trivial in isolation, this overlooks the fact that this behaviour is almost always repetitive and oppressive, often directed at victims who are vulnerable and who live in some of the most deprived parts of the country. The impact is cumulative: when sustained over a period of time, it can have a long and lasting impact on individuals, families and the local communities that have experienced this behaviour. It affects people’s mental health. It makes them want to move home. And collectively, it hastens a sense of local decline, which in turn undermines incentives to invest in the community while hindering regeneration opportunities. That is why it is so important the issue of ASB is tackled quickly and effectively.

For the past decade, ASB has effectively been ignored by the government. Local partnerships have lost focus, enforcement powers have been weakened and action against troubled families has stalled.

At the same time, neighbourhood policing – the bedrock of the British consent-based policing model and a prerequisite for any serious response to ASB – has been eroded. And the visibility of police on the streets has declined across the board. While most police forces have retained some type of neighbourhood-policing offer, the form that it takes and the level of resourcing it receives look very different depending on where you happen to live. This has undermined confidence in the police and left the public confused about the level of service they have a right to expect.

This is not an argument against localism or for the return of top-down control. Locally elected Police and Crime Commissioners and practitioners will continue to be better placed than civil servants to understand what action is required to tackle ASB and other issues of concern within communities. But a local approach should not be confused with an abrogation of responsibility – central government still has a crucial role to play in providing the framework, levers and resources in which localism can flourish.

The polling carried out for this paper illustrates the public’s priorities: when asked to choose from a list of functions, they want a local police team that is responsive, visible and accessible. Below we sketch out what that could look like in practice. We hope it will provide the basis of a new local-policing contract, combining clear minimum standards with the flexibility necessary to allow practitioners the ability to tailor their responses to local needs.

Recommendations: Neighbourhood Policing

Neighbourhood policing is a central pillar of any serious response to ASB and, as this report has illustrated, an important driver of public confidence more broadly.

A New Local-Policing Contract

The lack of clarity and certainty about what to expect from the local police, particularly in terms of the response to ASB, is in danger of creating confusion and undermining confidence.

We recommend that the government consults on the creation of a new local-policing contract in every neighbourhood based on the priorities identified by the public in our polling. At the least, this should include minimum standards on the following three factors:

Responsiveness: How rapidly the police respond to incidents and calls for their service.

Visibility: The extent to which police spend time on patrol.

Accessibility: The extent to which officers are easily contactable and the level of face-to-face interaction whether via police stations, surgeries or online.

To improve transparency and accountability, the government should also publish scorecards, enabling the public to assess the performance of their local-neighbourhood team against a basket of comparable metrics.

Greater Consistency of Approach

There is enormous diversity in how neighbourhood policing is delivered today both in terms of its resourcing, and the form and function it takes. The College of Policing produced guidance in 2019 but it lacked detail on key questions of substance (resourcing) and appeared to encourage a further shift away from neighbourhood policing’s original remit, which was a specialism focused on reassurance, engagement and resilience.

The government should work with the college and the National Police Chiefs’ Council to clarify national expectations around the approach taken to neighbourhood policing, with respect to the chosen remit, form and function. Specifically, this should clarify:

The principal of universal coverage: Every area of the country should be covered by a neighbourhood-policing team.

Functional distinctiveness: Emphasising proactive prevention, confidence and community resilience rather than getting diverted into broader policing aims of harm reduction and vulnerability.

PCSOs: Specifying their role especially in relation to ASB and neighbourhood policing.

Protecting the functions of neighbourhood policing is clearly not cost free, particularly during a time when the police are managing a range of competing demands from serious violence to cyber-related fraud.

The Home Office should ask police forces to guarantee a minimum level of neighbourhood policing (measured as a proportion of the total workforce), designed around the principles outlined above. This will involve deploying a significant proportion of the additional officers recruited since 2019 into neighbourhood policing.

Recommendations: ASB strategy

If the government is serious about “levelling up”, it will need to devote a lot more attention to both understanding the nature and scale of ASB and to setting a clear direction on the action it expects local agencies to take in responding to the problem. A national strategy on ASB will require action at all levels of government, from top to bottom.

Pressure From Above

The government should publish a white paper setting out a national framework for tackling anti-social behaviour, to include the following elements:

Strengthening of enforcement powers: Clearly, any strengthening of enforcement must be supported by an evidence base, which is sorely lacking. We recommend the government commissions an independent body to undertake an urgent investigation into the effectiveness of the interventions and powers it introduced in 2014. Additionally, the government should conduct a consultation with police officers, local-authority practitioners and victims about the use and effectiveness of existing enforcement powers and where they might need to be strengthened, with a view to improving the speed with which such powers can be introduced. Finally, the government should commit to greater transparency by ensuring that local agencies are required to record their use of available powers.

Renewed emphasis on intensive support for troubled families: After an initial push during the early 2010s, action on parenting and families has stalled more recently. The government should publish guidance making clear that the following set of circumstances will trigger some type of parenting or family-based intervention: exclusion from school, persistent truancy, a child found behaving anti-socially or committing crime, and parents themselves involved in drugs or crime. These circumstances should trigger a formal response coordinated by the local authority that ensures the family gets help.

Local governance and accountability: Community Safety Partnerships (CSPs) for tackling ASB have lost focus and increasingly lack the power to drive change. The government should examine options for reinvigorating CSPs and establish structures that ensure closer local working of neighbourhood policing and local-authority services. This could be achieved by refocusing CSPs around ASB and low-level crime; or nominating a local-authority officer as a neighbourhood-police liaison for every team to cover all joint action needed to resolve neighbourhood problems and provide feedback to the public; or ensuring that at every neighbourhood-policing public meeting, local-authority officers are present to ensure that problems raised by the public can be resolved in one forum.

These recommendations aren’t just important as a means of protecting the victims of ASB, they are also necessary to fundamentally rebuild the social fabric that binds our communities together. Of course respect must come from within communities – it cannot be conjured through legislation and government diktat. But central government must do its bit too: providing the direction, resources and powers to ensure wrongdoing is detected and victims are supported. That is the very least the public has the right to expect.

Lead Image: Getty Images

Charts created with Highcharts unless otherwise credited.

During the 1970s and 1980s, the term “anti-social behaviour” (ASB) was used primarily by criminologists to describe a whole range of deviant behaviour (illegal or otherwise), which departed from social norms. For example, see

Anti-Social Behaviour

. McGraw-Hill Education (UK).

Crime Survey for England and Wales, year ending March 2021,

https://www.ons.gov.uk/peoplepopulationandcommunity/crimeandjustice/bulletins/crimeinenglandandwales/yearendingmarch2021#anti-social-behaviour

Police Foundation and Crest, “Policing the pandemic”, Jan 2022,

https://64e09bbc-abdd-42c6-90a8-58992ce46e59.usrfiles.com/ugd/64e09b_14779c385bff4461aef5eb378f8cd31e.pdf

https://www.theatlantic.com/magazine/archive/1982/03/broken-windows/304465/

For example, see

https://news.northeastern.edu/2019/05/15/northeastern-university-researchers-find-little-evidence-for-broken-windows-theory-say-neighborhood-disorder-doesnt-cause-crime/

https://www.newscientist.com/article/dn16096-graffiti-and-litter-lead-to-more-street-crime/

https://cebcp.org/evidence-based-policing/what-works-in-policing/research-evidence-review/broken-windows-policing/

https://www.cardiff.ac.uk/crime-security-research-institute/publications/research-briefings/the-signal-crimes-perspective

Nick Plumb, Ailbhe McNabola and Vidhya Alakeson, “Backing our Neighbourhoods: making levelling up work by putting communities in the lead”, Power to Change, 2021.

https://www.ukonward.com/wp-content/uploads/2022/03/Good-Life-PDF.pdf

There are 34,753 lower layer super output areas (LSOAs) in England and Wales so £50 million divided between them equates to less than £1,500 per neighbourhood.

https://policyexchange.org.uk/wp-content/uploads/2016/09/a-state-of-disorder-feb-10.pdf

Menichelli, 2018.

Police Foundation, Strategic Review of Policing, March 2022,

https://www.mirror.co.uk/news/uk-news/theresa-condemned-over-weak-shake-up-1940722

Justice Committee report on children and young people in custody, 2020,

https://publications.parliament.uk/pa/cm5801/cmselect/cmjust/306/30602.htm

Danny Shaw and James Stott, “Making the criminal justice system work better: how to improve out-of-court disposals and diversion schemes”, January 2022.

https://asbhelp.co.uk/wp-content/uploads/2013/08/The-Community-Trigger-Empowerment-or-Bureaucratic-Exercise-Sept16.pdf

Anti-Social Behaviour Intensive Family Support Projects: An evaluation of six pioneering projects for families at risk of losing their homes as a result of anti-social behaviour, Department for Communities and Local Government, 2006.

https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/786891/National_evaluation_of_the_Troubled_Families_Programme_2015_to_2020_family_outcomes___national_and_local_datasets_part_4.pdf

https://www.justiceinspectorates.gov.uk/hmicfrs/wp-content/uploads/state-of-policing-2016.pdf

https://www.police-foundation.org.uk/2017/wp-content/uploads/2010/10/TPFJ6112-Neighbourhood-Policing-Report-WEB_2.pdf

Police workforce England and Wales statistics - GOV.UK (www.gov.uk)

https://assets.college.police.uk/s3fs-public/2020-11/NPG_supporting_material_supervisors.pdf

https://www.policingreview.org.uk/wp-content/uploads/srpew_final_report-1.pdf

The Police Foundation, “A New Mode of Protection”, 2022.

https://www.college.police.uk/research/what-works-policing-reduce-crime/visible-police-patrol

See Yesberg et al, “Police visibility, trust in police fairness, collective efficacy”, 2021,

https://journals.sagepub.com/doi/full/10.1177/14773708211035306

. Also Gill et al, 2014.

Peyton et al, 2019.

Article Tags

• Research article
• Open access
• Published: 22 October 2021

Risk and resource factors of antisocial behaviour in children and adolescents: results of the longitudinal BELLA study

• Christiane Otto 1 ,
• Anne Kaman 1 ,
• Michael Erhart 1 , 2 , 3 ,
• Claus Barkmann 1 ,
• Fionna Klasen 1 ,
• Robert Schlack 4 &
• Ulrike Ravens-Sieberer   ORCID: orcid.org/0000-0002-2031-095X 1  

Child and Adolescent Psychiatry and Mental Health volume  15 , Article number:  61 ( 2021 ) Cite this article

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Antisocial behaviour is a common phenomenon in childhood and adolescence. Information on psychosocial risk and resource factors for antisocial behaviour are important for planning targeted prevention and early intervention programs. The current study explores risk and resource factors of antisocial behaviour in children and adolescents based on population-based longitudinal data.

We analysed longitudinal data from the German BELLA study ( n = 1145; 11 to 17 year-olds) measured at three measurement points covering two years. Latent growth analysis, linear regression models and structural equation modelling were used to explore cross-sectional and longitudinal data.

Based on baseline data, we found that stronger self-efficacy and worse family climate were each related to stronger antisocial behaviour. Longitudinal data revealed that more severe parental mental health problems, worse family climate at baseline, deteriorating family climate over time, and more social support were each associated with increasing antisocial behaviour over time. We further found a moderating effect for family climate.

Conclusions

Our study provides important exploratory results on psychosocial risk, resource and protective factors in the context of antisocial behaviour in children and adolescents, which need confirmation by future research. Our exploratory results point in the direction that family-based interventions for antisocial behavior in children and adolescents may benefit from considering the family climate.

Introduction

Antisocial behaviour is a key symptom and subtype of conduct disorder (CD) as defined by DSM-5 and ICD-10. Antisocial behaviour in children and adolescents can be characterized by symptoms such as being verbally and physically harmful to other people, violating social expectations, engaging in behaviours such as delinquency, vandalism, theft, and truancy, or having disturbed interpersonal relationships, whereby antisocial behaviour among young people is very heterogeneous [ 1 , 2 ].

Antisocial behaviour and associated conduct disorder are among the most common behavioural problems in childhood and adolescence. According to a systematic review of the global epidemiology of conduct disorder, gender-specific prevalence rates world-wide are relatively stable over time indicating that among 5 to 19 year-olds 3.6% (3.3% to 4.0%) males and 1.5% (1.4% to 1.7%) females are affected [ 3 ]. That is, boys are more than two times more likely to be diagnosed with conduct disorder, characterised by heterogeneous patterns of antisocial, aggressive or defiant behaviours, than girls. Symptoms of antisocial behaviour and associated conduct disorder often emerge during preschool years and are most prevalent during middle childhood and adolescence. While antisocial behaviour in childhood is often characterised by milder symptoms such as lying, stealing at home and truancy, more severe symptoms such as aggressive and delinquent behaviour increase during adolescence [ 4 ]. In approximately 50 % to 85 % of children and adolescents with an early onset conduct disorder, serious behaviour problems persist into adulthood [ 5 ]. A childhood conduct disorder characterised by antisocial behaviour can be a premorbid condition for a antisocial personality disorder in adulthood [ 2 ].

Patterson et al. [ 6 ] assume that the etiology and the course of antisocial behaviour from childhood through adolescence are results of a multifactorial process. According to Dishion and Patterson [ 4 ], relationship dynamics, behaviour settings, self-regulation, and the cultural and community context are the main domains involved in the development of antisocial behaviour. On the other hand, recent research has shown that genetic and environmental influences are also of great importance in this context [ 7 , 8 ].

Antisocial behaviour and associated conduct disorder often co-occur with other mental disorders, most commonly with attention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), depression and anxiety disorder [ 5 , 9 , 10 , 11 ]. Furthermore, antisocial behaviour is associated with significant impairments as well as adverse consequences and health outcomes in adulthood such as low educational achievement and unemployment [ 12 ], alcohol and drug dependence [ 13 , 14 ], criminality [ 15 ], teenage pregnancy [ 13 ] and psychosocial malfunctioning [ 16 , 17 ]. Moreover, adolescent conduct disorder has a significant impact on the subjective overall health [ 13 ]. Taken together, children who exhibit antisocial behaviour are not only affected by impairments in various life domains, but may also cause significant distress in others, which emphasises the high public health relevance of this behavioural problem.

In order to prevent the adverse consequences and impairments associated with antisocial behaviour, targeted prevention and early intervention strategies for children and adolescents under risk are required. Understanding the factors related to the development of antisocial behaviour can help to inform experts planning prevention and intervention. According to the literature, these factors are usually classified into personal, familial, and social risk and resource factors. Risk factors increase the probability of a negative mental health outcome, whereas resource factors support a positive development. Factors that strengthen the mental health of children when being exposed to risks are defined as protective factors [ 18 , 19 , 20 , 21 ].

While psychosocial risk factors for antisocial behaviour are comparably well studied, studies on resource factors are still rare. Most previous research has focused on the role of familial risk factors. Several cross-sectional and longitudinal studies have found family conflicts [ 22 ], coercive or hostile parenting [ 23 , 24 ], inconsistent discipline and poor supervision [ 25 ], parental strain [ 24 ], as well as unhealthy family functioning [ 26 ] to be associated with antisocial behaviour in children and adolescents. Further, living in disrupted families, meaning that the child is permanently or temporarily separated from a biological parent, may contribute to the development of antisocial behaviour [ 24 ]. On the other hand, positive parenting behaviours that are characterised by involvement, support and guidance have been related to prosocial behaviours through anger regulation in adolescents [ 25 ]. Previous studies have further revealed that a family history of mental health problems [ 22 , 24 ] as well as a parental chronic disease [ 27 ] are associated with the development of childhood antisocial behaviour and delinquency.

Furthermore, cross-sectional and longitudinal studies found protective effects of self-efficacy on antisocial behaviour in children and adolescents [ 28 , 29 ]. Self-efficacy is a concept that describes the perception of one’s own ability to achieve goals [ 30 ]. Research findings indicated that children and adolescents’ perceptions of self-efficacy for resisting peer pressure are associated with a reduction of antisocial behaviour [ 28 , 29 ].

Concerning social factors related to antisocial behaviour, Farrington [ 24 ] has identified the interaction with antisocial peers as important risk factor, while prosocial involvement and having good social skills may support children’s prosocial behaviour [ 22 ]. Moreover, studies have found associations between antisocial behaviour and academic failure as well as low educational achievement, although the direction of these associations is not clear [ 22 , 24 ]. In terms of socioeconomic factors, cross-sectional studies have demonstrated associations of low family income, low parental education and poor housing with antisocial behaviour in children and adolescents [ 24 , 26 , 31 ]. Further, there is evidence of an association between migration background and more pronounced antisocial behaviour [ 32 ].

Overall, a number of previous studies focused on specific risk, resource and/or protective factors associated with antisocial behaviour. However, most of these studies analysed only cross-sectional data. Moreover, in most studies only direct associations of risk and resource factors with antisocial behaviour have been examined, although research has shown that risk and resource factors can interact in different ways [ 33 ].

The present study explores cross-sectional and longitudinal effects of the risk factor parental mental health problems and individual, familial, and social resource factors on the state and change in antisocial behaviour in children and adolescents over time based on data of a German population-based sample. We expected that parental mental health problems (risk factor) and self-efficacy, family climate, and social support (resource factors) are not only associated with initial antisocial behaviour, but also with the change in antisocial behaviour over time. Following the approach proposed by Masten [ 18 ], we expected that resource factors might have the potential to act as protective factors. Therefore, we further explored whether the examined resource factors act as protective factors moderating the association between the risk factor parental mental health problems and antisocial behaviour initially and over time.

Based on the literature we had the following expectations concerning cross-sectional data:

Stronger parental mental health problems (risk factor) are associated with stronger antisocial behaviour in children and adolescents.

Higher self-efficacy, better family climate and more social support (resource factors) are each associated with less antisocial behaviour.

Children and adolescents who are not living with both biological parents, whose parents have a chronic disease, and whose parents report more severe strain show stronger antisocial behaviour.

Boys, older children and adolescents, those with a lower SES, and children and adolescents with a migration background show stronger antisocial behaviour.

We had the following expectations concerning our analyses of longitudinal data:

Increasing parental mental health problems (risk factor) are associated with increasing antisocial behaviour in children and adolescents over time.

Increasing self-efficacy, family climate and social support (resource factors) are each associated with decreasing antisocial behaviour over time.

Further, we had the following expectations concerning interactions between risk and resource factors:

High self-efficacy, a good family climate and good social support (resource factors) each attenuate the detrimental effect of parental mental health problems (risk factor) on antisocial behaviour.

Increasing self-efficacy, family climate and social support (resource factors) each attenuate the detriemental effect of increasing parental mental health problems (risk factor) on the change in antisocial behaviour over time.

We analyzed data from the longitudinal BELLA study [ 34 ]. The BELLA study is the mental health module of the German National Health Interview and Examination Survey for Children and Adolescents (KiGGS) [ 35 ]. In the BELLA study data on mental health, health-related quality of life, and associated risks and resources in German children, adolescents, and young adults have been collected. The KiGGS and BELLA study are conducted in close cooperation; baseline assessments of both studies took place from 2003 to 2006. From the KiGGS baseline sample ( n = 17,641 children and adolescents aged 0 to 17 years) a subsample was drawn for the BELLA study by random ( n = 2942 children and adolescents, 7 to 17 years old). The team of the BELLA study informed these children and adolescents and their parents about the study and asked for their participation. The final BELLA baseline sample included n = 2863 (response rate: 97.3%) children and adolescents (aged 7 to 17 years) and their parents. Further measurement points of the BELLA study were conducted with n = 2423 of the BELLA baseline participants (84.6%) taking part in the 1-year follow-up (2004 to 2007) and n = 2190 (76.5%) of the baseline participants taking part in the 2-year follow-up (2005 to 2008). Data for the BELLA study was gathered by means of computer-assisted telephone interviews and subsequent paper-pencil questionnaires. Trained interviewers conducted the telephone interviews following structured guidelines, regular supervisions were provided by a child and adolescent psychologist. Participants received a small incentive in the form of a 5 Euro gift card. Self-reported data was collected from participants aged at least 11 years, and parent-reported data from one parent of each participant. Standardised, psychometrically sound and internationally tested measures were administered (if available). The ethics committee of the University Hospital Charité in Berlin and the Federal Commissioner for Data Protection in Germany both gave their approvals for the BELLA study. More details on the design and methods of the longitudinal BELLA study are published providing detailed information on the sampling of the BELLA study (which results from the larger KiGGS survey) [ 36 ] and drop out analyses for BELLA follow-up assessment; already reported drop out analyses indicated that participants with lower SES or migration background were more often lost to follow-up assessments, but gender, community size, region (Eastern vs. Western Germany), parent-reported general health or parent-reported mental health scores at baseline were not related to drop-out status [ 34 ].

Participants

We analysed data from the first three measurement points of the BELLA study (baseline, 1-year and 2-year follow-ups) in the present study. We could include cases in our analyses, if (i) data gathered only at baseline were completely available (on age, gender, socioeconomic status (SES), migration status, single parent family, step parent, parental chronic disease, and parental strain) and if (ii) longitudinally measured data were available for at least one measurement point (on antisocial behaviour and comorbid symptoms of depression, generalised anxiety, and ADHD, on parental mental health problems, self-efficacy, family climate, and social support). Further, cases were only analysed if the same parent had fulfilled the parent questionnaire at each measurement point. The final sample consisted of n = 1145 children and adolescents aged 11 to 17 years at baseline.

Sociodemographic variables

We determined age (in years), gender, the SES and migration status at baseline. The SES was measured in the KiGGS study with the parent-reported Winkler-index [ 37 ] which gathers information on education, profession and income of both parents. We used the sum-score of the Winkler-index (range: 3 to 21, with higher values indicating better SES) in the following analyses. For sample description only, we categorised the sum-score to differ between participants with low (scores from 3 to 8), middle (scores from 9 to 14) and high SES (scores from 15 to 21) [ 38 ]. Migration status was determined in the KiGGS study according to Schenk [ 39 ], if (i) the child or adolescent had immigrated to Germany and had at least one parent born in a country other than Germany, or if (ii) both parents immigrated to Germany or did not hold German citizenship.

Familial and parental risks

At baseline the family structure was assessed in the KiGGS study asking the parents with whom the participating child or adolescent lived at home (response options = with both biological parents, with the mother (and her partner), with the father (and his partner), with grandparents or other relatives, with step- or foster parents or in a children’s home). For the following analyses, we recoded this variable to identify children and adolescents who did not live with both biological parents (code: 1) versus those who did (code: 0). In the baseline assessment of the BELLA study, parents were asked for chronic diseases/disabilities and fulfilled a short questionnaire on parental strain. We gathered the responses to both items on chronic diseases/disabilities (“Do you have a chronic disease (e.g., asthma, diabetes, rheumatism) or disability?” and “Does your partner have a chronic disease (e.g., asthma, diabetes, rheumatism) or disability?”) and a created a new variable indicating whether at least one parent of the child or adolescent had a chronic disease or disability (code: 1), or whether no parent was affected (code: 0). To measure parental strain, we used 11 items asking for the particular burden caused e.g., by housekeeping, financial problems, job-related issues, being a single parent, or by caring for an ill family member [ 19 ]. Parents rated the perceived strain for each burden by means of a 5-point response scale (0 = “none” to 4 = “very strong”). For our analyses, we calculated a mean over all items with a higher score indicating more severe parental strain.

• Antisocial behaviour

We assessed antisocial behaviour in children and adolescents by parent-reports at each measurement point based on the German version of the well-established Child Behavior Checklist (CBCL) [ 40 , 41 ]. The CBCL offers a subscale on delinquency including 13 items (“Behavior of your child:”, e.g., “Steals at home”, “Lying or cheating”), each offered with three response options (0 = “not true” to 2 = “very true or often true”). We calculated the mean across the items with a higher mean indicating more severe antisocial behaviour. Acceptable internal consistency was found for this scale in the sample under analysis (Cronbach’s α ranged from 0.70 to 0.73 across measurement points).

Comorbid symptoms of attention deficit hyperactivity disorder (ADHD), depression, and generalised anxiety

We measured comorbid symptoms in children and adolescents longitudinally at each investigated measurement point. We recoded items if necessary and calculated means for each symptom scale with higher values indicating stronger symptoms.

Parent-reported symptoms of attention deficit hyperactivity disorder (ADHD) were assessed based on the Conners Global Index (C-GI) [ 42 , 43 ]. In the BELLA study, a German version of the C-GI was developed and administered [ 44 , 45 , 46 ]. For the present analyses, the C-GI subscale restless-impulsivity was used including overall seven items on inattention (e.g., “inattentive, easily distracted”), hyperactivity (“fidgeting”) and impulsivity (“excitable, impulsive”). Each item was offered with a 4-point response scale (0 = “not true at all” to 3 = ”very much true”). Acceptable to good internal consistency was found for the C-GI scale restless-impulsivity in the investigated sample (α ranged from 0.77 to 0.81).

Self-reported depressive symptoms were assessed by means of the German version of the established Center for Epidemiologic Studies Depression Scale (CES-DC) [ 47 , 48 ]. This measure gathers emotional, cognitive and behavioural aspects of depression (e.g., “I thought my life had been a failure”) with overall 20 items, each presented with a 4-point response scale (0 = “not at all” to 3 = “a lot”). Good internal consistency was given for the CES-DC in our sample (α ranged from 0.81 to 0.87).

Self-reported symptoms of generalised anxiety were measured based on a German version of the Screen for Child Anxiety Related Disorders (SCARED-D) [ 49 , 50 , 51 ]. The scale on generalised anxiety of the SCARED-D includes 9 items (e.g., “I worry about being as good as other kids”) offered with a 3-point response scale (0 = “not true or hardly ever true” to 2 = “very true or often true”). The internal consistency for this scale was good in our sample (α ranged from 0.81 to 0.85).

Risk and resource factors

We measured risk and resource factors longitudinally, at each measurement point. Items were recoded if necessary, and scores across the items of each scale were calculated. We calculated means for scale scores with a higher mean indicating more pronounced self-efficacy, better family climate, better social support or stronger parental mental health problems, respectively.

The risk factor parental mental health problems was measured by parent-reports using the Symptom-Check List 9-item Short version (SCL-S-9) [ 52 ], which is a short version of the SCL-90-R [ 53 ]. The SCL-S-9 serves to assess a wide range of psychopathologic symptoms with each item belonging to one dimension of the original SCL-90-R (i.e., somatization, obsessive-compulsive, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism). Each of the nine items of the measure are presented with a 5-point response scale (0 = “none at all” to 4 = “very severe”). Good internal consistency was found for the SCL-S-9 in the investigated sample (α was 0.81 at each measurement point).

The individual resource factor self-efficacy in children and adolescents was measured by self-reports using the General Self-Efficacy Scale (GSE) [ 54 , 55 ]. The GSE includes 10 items (e.g., “If I am in trouble, I can usually think of a solution”) provided with a 4-point response scale each (0 = “not at all true” to 3 = “exactly true”). The internal consistency was good for the GSE in our sample (α ranged from 0.81 to 0.83).

The familial resource factor family climate was measured by self-reports based on the German Family Climate Scale (FCS) [ 56 ]. The FCS represents the German adaptation of the Family Environment Scale (FES) [ 57 ]. We administered eight items of the FCS in the BELLA study which are related to active recreational organization and cohesion (e.g., “In our family everybody cares about each other’s worries”) and presented with a 4-point response scale each (0 = “not true” to 3 = “exactly true”). Acceptable to good internal consistency was given for the administered FCS in the investigated sample (α ranged from 0.78 to 0.82).

The social resource factor social support was assessed via self-reports gathered from children and adolescents. For administration in the BELLA study, eight selected and translated items from the Medical Outcomes Study Social Support Survey (SSS) [ 58 ] were administered. The administered items measure how frequent specific types of support are available (“How often is the following type of support available for you if you need it?” e.g., “Someone who listens”) and are provided with a 5-point response scale each (0 = “none of the time” to 4 = “all of the time”). The internal consistency was good to excellent for this short version (SSS-short) in our sample (α ranged from 0.88 to 0.91).

Data analysis

Latent growth modelling is often used to investigate changes in behaviours [ 59 ]. By means of a latent growth model (LGM), two latent parameters are estimated with the intercept representing the initial state of a variable under analysis at baseline and the slope reflecting the change in this variable over time. In the present study, we used this approach and followed a two-step analysing procedure. We started by calculating a LGM for each construct which was longitudinally measured (i.e., antisocial behaviour, the investigated risk and resource factors, and symptoms of comorbid disorders). Goodness of fit was assessed via the root mean square error of approximation (RMSEA) and the comparative fit index (CFI) for each LGM. We then used intercepts and slopes resulting from LGMs in linear regression models. By means of regression Model A0, we explored effects of the initially measured risk and resource factors on initial antisocial behaviour. By means of Regression Model B0, we explored effects of initially measured risk and resource factors as well as effects of the changes in these constructs over time on the change in antisocial behaviour over time. In each of these models we considered the following covariates: sociodemographic information (i.e., age, gender, SES, and migration status), data on familial and parental risks (i.e., living with at least one non-biological parent, parental chronic disease, and parental strain), and data on comorbid symptoms (of depression, generalised anxiety, and ADHD). In order to explore associations between the considered constructs and antisocial behaviour age-group specifically, we re-run both regression models separately for 11 to 13 year-olds and for 14 to 17 year-olds.

By means of two further regression models, we explored whether the investigated resource factors (i.e., self-efficacy, family climate and social support) serve as protective factors in terms of moderating the relationship between the risk factor parental mental health and antisocial behaviour in children and adolescents. Regression Model A1 was conducted based on baseline data adding interaction effects between parental mental health problems and each resource factor to Model A0. Model B1 was conducted adding all potential interaction effects between parental mental health problems and each resource factor to Model B0 using longitudinal data.

In each regression model, we used centered metric variables. Further, we interpreted standardised regression coefficients as correlation coefficients to allow rough interpretation of the strengths of detected associations ( r = 0.10 indicates a weak, r = 0.30 a medium and r = 0.50 a strong association).

We additionally calculated a structural equation model (SEM) focusing on the exploration of associations between longitudinally measured risk and protective factors, and antisocial behavior in order to evaluate the results found by means of regression Models A0 and B0. In the SEM, we specified direct paths from the intercepts of the risk and resource factors on the intercept and on the slope of antisocial behavior; direct paths from the slopes of the risk and ressources on the slope of antisocial behaviour were also specified and estimated according to the maximum likelihood criterion. The latent parameters of the risk and resource factors as well as the intercept and the slope of antisocial behaviour were freed to correlate. In line with the LGMs, we fixed time scores 0, 1 and 2 for the estimation of the slopes to reflect equidistant measurement points (with 0 representing the baseline assessment) [ 60 ], and we determined model fit.

Mplus 8 [ 60 ] was used for LGMs and for the SEM, IBM SPSS 26 for regression models.

The analysed sample included n = 1145 children and adolescents aged 11 to 17 years at baseline (Table  1 ). In this sample, about half of the children and adolescents were female, the mean age was about 14 years, about half of the participants lived in families with a medium SES (low SES: 19%, n = 219; medium SES: 51%, n = 587; high SES: 30%, n = 339), and 6% ( n = 71) of the children and adolescents had a migration background ( n = 37 were born in other countries, i.e., Russia ( n = 8), Kazakhstan ( n = 5), Bosnia and Herzegovina, Greece, Romania, and Ukraine ( n = 2 each), and Austria, Belarus, Brazil, Cuba, Czech Republic, Egypt, Finland, Kossovo, Luxembourg, Moldova, Paraguay, Poland, the Netherlands, the US, Turkey, and Uzbekistan ( n = 1 each); n = 34 were born in Germany with mother and/or father born in Poland and Russia ( n = 8 each), Turkey ( n = 7), Romania ( n = 3), Austria, China, Croatia, Egypt, France, Greece, India, Kossovo, Peru, the United Kingdom, and Serbia and Montenegro ( n = 1 each)). For each participant, the same parent completed the parent questionnaire in the BELLA study gathering information on parent-reported antisocial behaviour and ADHD in children and adolescents, on parental mental health problems, and parental strain. For 91% of the participants the mothers ( n = 1045), for 8% the fathers ( n = 87), and for 1% step-, foster- or grandparents ( n = 13) completed the parent questionnaire.

Results for Model A0 using cross-sectional baseline data are depicted in Table  2 . Findings indicated that stronger antisocial behaviour was related to older age and lower SES. Further, antisocial behaviour was more likely in children and adolescents who did not live with both biological parents and was associated with more severe parental strain. Moreover, stronger antisocial behaviour was related to more severe comorbid symptoms of ADHD, stronger depressive symptoms, and less symptoms of generalised anxiety. No effect was found for the risk factor parental mental health problems, but we found significant effects for two of the three investigated resource factors. More pronounced antisocial behaviour at baseline was associated with stronger self-efficacy and worse family climate. Detected effects indicated negligible to small associations of not living with both biological parents, comorbid symptoms of generalised anxiety and both resource factors with antisocial behaviour; we found small associations of age, SES, parental strain, and comorbid depressive symptoms, and a medium association of comorbid symptoms of ADHD with antisocial behaviour at baseline.

We added results of Model B0 using longitudinal data to Table  2 . Increasing antisocial behaviour was related to younger age, less parental strain (both at baseline), and increasing comorbid symptoms of ADHD over time. Increasing antisocial behaviour over time was further associated with more severe parental mental health problems (risk factor) at baseline, worse family climate (resource factor) at baseline, deteriorating family climate over time, and with more social support (resource factor) at baseline. Detected effects indicated a negligible to small association of initial parental mental health problems with the change in antisocial behaviour, and small associations for all remaining effects.

Please note, the fit was good for most LGMs according to the RMSEA and the CFI using guidelines for interpretation from Schermelleh-Engel et al. [ 61 ] (antisocial behaviour: χ² = 0.201, degrees of freedom (df) = 1, RMSEA= 0.000 (90 % Confidence Interval (CI): 0.000–0.060), CFI= 1.00; ADHD: χ² = 3.020, df = 1, RMSEA= 0.042 (CI: 0.000–0.100), CFI= 1.00; depressive symptoms: χ² = 0.025, df = 1, RMSEA= 0.000 (CI: 0.000–0.040), CFI= 1.00; generalised anxiety: χ² = 0.304, df = 1, RMSEA= 0.000 (CI: 0.000–0.064), CFI= 1.00; self-efficacy: χ² = 0.354, df = 1, RMSEA= 0.000 (CI: 0.000–0.065), CFI= 1.00; family climate: χ² = 0.901, df = 1, RMSEA= 0.000 (CI: 0.000–0.077), CFI= 1.00). However, the fit for the LGMs for parental mental health problems (χ² = 8.961, df = 1, RMSEA= 0.083 (CI: 0.040–0.137), CFI= 0.99) and for social support (χ² = 11.013, df = 1, RMSEA= 0.094 (CI: 0.049–0.147), CFI= 0.97) was not acceptable according to the RMSEA, but good in comparison to the baseline model according to the CFI. Correlations between intercepts and slopes were positive and small for generalized anxiety ( r =.10, p = .001) and depressive symptoms ( r = 0.23, p < 0.001), negative and small for family climate ( r = − 0.21, p < 0.001) and self-efficacy ( r = − 0.25, p < 0.001), negative and moderate for social support ( r = − 0.31, p < 0.001), ADHD ( r = − 0.36, p < 0.001) and antisocial behaviour ( r = − 0.41, p < 0.001), and negative and strong for parental mental health problems ( r = − 0.63, p < .001),

Results of age-group specific models can be found in Additional file 1 : Tables S1 and S2). Focusing on the risk factor parental mental health, we found no significant effect at all in our age-group specific analyses. For the investigated protective factors among 11 to 13 year-olds, lower initial social support was associated with more pronounced initial antisocial behaviour; further increasing self-efficacy, lower initial family climate, decreasing family climate, and higher initial as well as increasing social support were each associated with increasing antisocial behaviour over time. In 14 to 17 year-olds, lower initial family climate was associated with more pronounced antisocial behaviour and decreasing family climate was related to increasing antisocial behaviour over time.

Moreover, we calculated interaction models to explore corresponding effects for the resource factors on the association between parental mental health problems (risk factor) and antisocial behaviour. The results are offered in Additional file 1 : Table S3. We found no moderating effects for any investigated resource factor based on baseline data (Model A1). However, based on longitudinal data (Model B1) we detected a moderating effect indicating that family climate served as a protective factor; improving family climate over time attenuated the association between increasing parental mental health problems and increasing antisocial behaviour over time; the detected interaction effect indicated a small association (ß = − 0.10; p = 0.020).

Finally, we specified and calculated the SEM which had a good fit (χ 2 = 107.79, df = 59, RMSEA = 0.027 (CI = 0.019–0.035), CFI = 0.99). Under the assumption that the specified model represented a correct description of the relationships between observed variables and latent concepts, stronger initial parental mental health problems were associated with more pronounced initial antisocial behaviour (standardised path coefficient = 0.299, p < 0.001). Further, good initial familial climate was related to initially less antisocial behaviour (standardised path coefficient = − 0.179, p < 0.001). Moreover, improving familial climate was associated with decreasing antisocial behaviour over time (standardized path coefficient = − 0.283, p = 0.025). Finally, initial social support was associated with change in antisocial behaviour over time; the standardised path coefficient (0.241, p = 0.028) indicated that better social support was related to increasing antisocial behaviour over time. Figure  1 presents results of the SEM.

Structural equation model on risk and resource factors of antisocial behaviour in children and adolescents. Standardised estimates (standard errors) are presented, further paths among all intercepts and slopes of risk and resource factors were estimated in the model (not shown for presentation purposes). AB = antisocial behaviour, parent MHP = parental mental health problems, SE = self-efficacy, FC = family climate, SS = social support, CBCL = Delinquency subscale of the Child Behavior Checklist [ 40 , 41 ]; SCL-S-9 = Symptom-Check List Short version-9 [ 52 ]; GSE = General Self-Efficacy Scale [ 54 , 55 ]; FCS = eight-item score based on the Family Climate Scale [ 56 ]; SSS-s = short social support scale with eight items of the German version of the Medical Outcomes Study Social Support Survey [ 58 ]

The aims of the present study were to explore the cross-sectional and longitudinal associations between potential risk and resource factors, and antisocial behaviour in children and adolescents. We used latent growth modeling and linear regression models; additionally we calculated an SEM which provided consistent results based on our longitudinal data. Contrary to our expectation, we found no association between the risk factor parental mental health problems and antisocial behaviour at baseline. However, more severe parental mental health problems at baseline were related to increasing antisocial behaviour over time. Further, we detected associations between the examined resource factors and antisocial behaviour, namely that stronger self-efficacy and worse family climate were related to stronger antisocial behaviour at baseline. Additionally, worse family climate at baseline, deteriorating family climate over time, and more social support at baseline were each associated with increasing antisocial behaviour over time. We further detected a moderating effect for family climate on the relationship between parental mental health problems and antisocial behaviour over time. Moreover, as expected, older age, lower socio-economic status, not living with both biological parents, and more severe parental strain were each associated with stronger antisocial behaviour at baseline, whereas younger age and less parental strain were related to increasing antisocial behaviour over time. Future research is needed to confirm the results of our exploratory study.

In our analyses based on baseline data, the risk factor parental mental health problems did not predict initial antisocial behaviour. This finding is contrary to previous research indicating that parental mental health problems are an important risk factor for antisocial behaviour in children and adolescents [ 22 , 24 ]. A closer examination of the literature, however, reveals that previous studies mainly focused on specific parental mental health problems such as substance use problems or a family history of antisocial behaviour. The fact that we only investigated parental psychopathology in general, using a short screening questionnaire, may at least partly explain why we were not able to find the expected relationship. It may also be that parents who have mental health problems themselves are less aware of their child’s antisocial behaviour [ 62 , 63 ]. In our longitudinal model, however, more severe parental mental health problems were associated with increasing antisocial behaviour over time, but we could not confirm this finding in age-group specific analyses. Especially clinical research may contribute further information to evaluate the importance of considering especially parental mental health problems in treatments of child and adolescent antisocial behaviour.

In line with our expectations and previous research on familial influences [ 22 , 26 ], the resource factor family climate predicted antisocial behaviour in our study initially as well as over time. Children living in families with a worse family climate showed more pronounced antisocial behaviour. Moreover, a deteriorating family climate over time was associated with increasing antisocial behaviour over time. In our moderator model based on longitudinal data, we further found that improving family climate over time attenuated the association between increasing parental mental health problems and increasing antisocial behaviour over time. Therefore, the family climate can be understood as a resource and a protective factor in our study. Future research may confirm our exploratory findings, which seem to point in the direction that children and adolescents with antisocial behaviour may benefit particularly from family-based interventions that address unhealthy family functioning and promote family cohesion and communication. In line with our finding, previous research has shown that family-based interventions and parent training programs are effective in treating children and adolescents with conduct disorder, antisocial behaviour, and delinquency [ 64 , 65 ].

Moreover, as expected, we found an association between the resource factor self-efficacy and antisocial behaviour at baseline in our study. The direction of this association, however, was not as expected. Children and adolescents with stronger self-efficacy displayed more pronounced antisocial behaviour. Our result, however, is in line with the social-cognitive learning theory [ 66 , 67 ]. For instance, instrumental-aggressive behaviour (i.e., proactive aggression) can lead to individual success or gain (e.g., to dominance through intimidation of the weaker, material gain through theft, etc.) [ 68 ]. Results of the KiGGS baseline study point to the same direction. Youths who had proved to be perpetrators or multiple perpetrators of violence also reported more social support and higher self-efficacy expectations [ 69 ]. In this context, affected children may benefit from cognitive-behavioural therapies (CBT) in which they reflect on their behaviour and self-perception. Interestingly, we found only for 11 to 13 year-olds an association between increasing self-efficacy and increasing antisocial behaviour in age-group specific analyses. Future reseach should investigate this association further considering the mixed evidence on the development of self-efficacy in childhood and adolescence [ 70 ].

Our finding on the association between social support and antisocial behaviour points in a similar direction. Higher levels of social support were related to increasing antisocial behaviour over time and thus, social support did not appear as a resource factor in our study. These results should be interpreted with care, since the administered items do not explicitly refer to friends or peers. On the other side, our findings may reflect the supportive response of a healthy social environment on antisocial behaviour in children and adolescents. It could further be the case that high levels of support from friends and peers could encourage children in their antisocial actions, especially if the peers also behave antisocial [ 5 , 24 ]. A corresponding association had previously been observed in a study on violent youth [ 69 ]. It remains unclear to what extent the perceived social support we found in our study represents a resource rather than an effect of mutual stabilization through the association of deviant youth [ 71 ]. This may be subject to further research, especially since we found associations between social support and antisocial behaviour in age-groups specific analyses only among 11 to 13 year-olds. In this context, social skills training with at-risk children and adolescents may be effective in order to support social competencies and to promote prosocial behaviour. The effectiveness of social skills training for children who are at risk or display antisocial behaviour has been widely researched and proven in several studies [ 65 , 72 ].

Based on the analysis of baseline data, we further found that older age, lower socio-economic status, not living with both biological parents, and more severe parental strain were each associated with stronger antisocial behaviour, confirming results from previous studies investigating these relationships [ 4 , 24 , 26 ]. These findings underline the need for targeted early prevention and intervention programs in specific vulnerable groups, for example in socially disadvantaged communities. Moreover, we detected that increasing antisocial behaviour over time was related to less parental strain at baseline. Again, it may be that stressed parents are less aware of their child’s antisocial behaviour. In addition, the limited parental strain could possibly be linked to parental neglect, as adverse childhood experiences such as parental abuse and neglect have often been associated with antisocial behaviour in children [ 73 , 74 ]. Further research is needed to clarify this association. In contradiction to the theory and previous research [ 3 ], we found no effect of gender on antisocial behaviour. Future studies could examine whether the association between gender and antisocial behaviour has changed over recent years. Further, we found no effect of migration on antisocial behaviour in our study, which may be related to the fact that only 6% of the participants in our study had a migration background.

In terms of the comorbid mental health problems explored in the current study, we found that stronger antisocial behaviour in children and adolescents was related to more severe symptoms of ADHD and depression, which coincides with results of former research [ 10 , 11 ]. In our longitudinal model, we further found that increasing antisocial behaviour was related to increasing comorbid symptoms of ADHD. This finding may indicate that the symptoms of antisocial behaviour and ADHD are closely associated, interact and develop concurrently [ 75 , 76 ]. Contrary to previous research [ 11 ], stronger antisocial behaviour was also related to less symptoms of generalised anxiety in our sample. This deviation from previous studies may at least partly be due to the fact that we assessed antisocial behaviour by parent-reports and generalised anxiety by self-reports. However, our finding may not be surprising considering that antisocial behaviour is characterised by criminal and aggressive behaviour, which from a clinical perspective is not a common characteristic of anxiety disorder [ 6 ]. Future studies may wish to investigate this association further in greater detail.

This study has some limitations. First and foremost, the present study is only exploratory, future research is needed to confirm our findings and to analyse some above described aspects in more detail. Regarding the presented analyses, it should be further beared in mind that we could not test cause-effect relationships in our study. In order to provide a clear presentation, we considered antisocial behaviour as the successor and the risk and the ressource factors as antecendents while acknowledging that in reality the relationships between these concepts might be more complex and dynamic. Moreover, we could explain 35% of the variance in antisocial behaviour by means of our baseline model, but we could only explain 7% of the variance in the corresponding slope with our longitudinal model. Detected effects only indicate small associations between corresponding variables in our longitudinal model. These findings may reflect that we investigated a general population sample (with rather low levels of mental health problems, and rather good self-efficacy, family climate, and social support). Further, our study only covered a period of two years and the slope for comorbid depressive symptoms did not vary significantly across individuals. Future studies may aim to cover a longer period of time in the lives of children and adolescents. However, these results may as well indicate that the development of antisocial behaviour is associated with important factors that we did not consider in analyses. These factors may include parental substance use [ 22 ], genetic and environmental influences [ 7 , 8 ], personality patterns [ 77 ], intelligence [ 78 ] as well as neuropsychological correlates [ 79 ]. Future studies on risk and resource factors for antisocial behaviour may take these aspects into account. Furthermore, we only differentiated between children and adolescents who lived with both biological parents and those who did not. It must be critically noted that the group of children who did not live with both biological parents is very heterogeneous and included e.g., children who lived with their mothers and their long-term partners, or children who lived in welfare institutions. It is also conceivable that the family status could have influenced the participation rate. These aspects may be investigated in more detail in future studies.

The present study has several strengths. We analysed data of the German BELLA study, which is an important population-based longitudinal study on mental health and well-being of children and adolescents. The large sample size and the wide age range from childhood to young adulthood are considerable strengths. Moreover, we administered established measurement tools to assess the analysed constructs. We used self-reported data of children and adolescents to assess the resource factors as well as comorbid internalizing symptoms of depression and anxiety. Parental psychopathology, antisocial behaviour, and symptoms of ADHD were measured by parent-reports since research has shown that externalizing problems are better observable by parents [ 80 , 81 ]. We further included familial and parental risks as important covariates in our models. Lastly, using latent growth modelling and linear regression models, we were able to analyse changes in antisocial behaviour as well as changes in risk and resource factors over time.

Overall, the present exploratory study adds to the literature by investigating the longitudinal influences of psychosocial risk and resource factors on antisocial behaviour in children and adolescents. The results point in the direction that parental mental health problems may have detrimental effects on the development of antisocial behaviour. On the other side, a good family climate can have beneficial effects on the state and change in antisocial behaviour and can also act as a protective factor moderating the relationship between the risk factor parental mental health problems and antisocial behaviour over time. In view of the fact that antisocial behaviour is a common behavioural problem in childhood and adolescence, causing significant impairments in various areas of life, our results are relevant to clinical practice and should be confirmed by future research. To prevent impairments and long-term consequences, future prevention and intervention programs may benefit from focusing on enhancing social competencies as well as on promoting family functioning and cohesion, particularly in children of parents with a mental disorder.

Availability of data and materials

The datasets generated and analysed during the current study are not publicly available, but are available from the corresponding author on reasonable request.

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Acknowledgements

The authors thank all children, adolescents, and their parents who participated in this research for their time and involvement. Further, we would like to thank the Robert Koch-Institute for their ongoing support and co-operation as well as the members of the BELLA study group. Members of the BELLA study group are: Ulrike Ravens-Sieberer, University Medical Center Hamburg-Eppendorf, Hamburg, Germany (Principal Investigator); Claus Barkmann, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Monika Bullinger, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Manfred Döpfner, University of Cologne, Cologne, Germany; Beate Herpertz-Dahlmann, University Clinics, RWTH Aachen, Aachen, Germany; Heike Hölling, Robert Koch-Institute, Berlin, Germany; Fionna Klasen, University Medical Center Hamburg-Eppendorf, Germany, Christiane Otto, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Franz Resch, University of Heidelberg, Heidelberg, Germany; Aribert Rothenberger, University Medical Center Göttingen, Göttingen, Germany; Sylvia Schneider, Ruhr-University Bochum, Bochum, Germany; Michael Schulte-Markwort, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Robert Schlack, Robert Koch-Institute, Berlin, Germany; Frank Verhulst, Erasmus MC Sophia Children’s Hospital, Rotterdam, The Netherlands; Hans-Ulrich Wittchen, Technische Universität Dresden, Dresden, Germany.

Open Access funding enabled and organized by Projekt DEAL. The baseline, 1-year and 2-year follow-ups of the BELLA study have been financially supported by the German Science Foundation. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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CO supervised and conducted data cleaning and preparation in the BELLA study, coordinated the work on the manuscript, participated in developing the analysing design, performed all presented statistical analyses (except the SEM), and contributed fundamentally to drafting the manuscript and interpretation of the data. AK participated fundamentally in drafting the manuscript and interpretation of the data. ME supported fundamentally in the revision of the manuscript and performed the SEM calculation. CB supported in interpreting the data and revised the manuscript critically. FK supervised data cleaning and preparation in the BELLA study, participated in developing the analysing design for the presented anlyses, and revised the manuscript critically. RS is involved in the KiGGS study which is conducted in close cooperation with the BELLA study and revised the manuscript critically. URS is principle investigator of the BELLA study, conceived the study since its start, is responsible for its design, funding, general decisions of measurement, and revised the manuscript critically. All authors read and approved the final manuscript.

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Correspondence to Ulrike Ravens-Sieberer .

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The BELLA study was approved by the ethics committee of the University Hospital Charité in Berlin and the Federal Commissioner for Data Protection in Germany. All procedures performed in the BELLA study were in accordance with the 1964 Helsinki declaration and its later amendments. Children, adolescents and their parents needed to give written informed consent prior to participation in the BELLA study. Informed consent was gathered from all participating parents for themselves, from parents for each participating child, and from all participating children and adolescents aged at least 11 years.

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Additional file 1: table s1..

Predicting the initial state and change of antisocial behaviour in 11 to 13 year olds. Table S2. Predicting the initial state and change of antisocial behaviour in 14 to 17 year olds. Table S3. Resource factors moderating the relationship between parental mental health problems and antisocial behaviour in children and adolescents.

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Otto, C., Kaman, A., Erhart, M. et al. Risk and resource factors of antisocial behaviour in children and adolescents: results of the longitudinal BELLA study. Child Adolesc Psychiatry Ment Health 15 , 61 (2021). https://doi.org/10.1186/s13034-021-00412-3

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Responding to anti-social behaviour: Analysis, interventions and the transfer of knowledge

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This article examines contemporary responses to anti-social behaviour (ASB) in England and Wales. Drawing on empirical evidence, it examines how ASB problems are understood and prioritised by practitioners; the nature of the interventions developed and implemented to address problems; and the ways in which outcomes are evaluated. The article points to how systematic analysis of ASB problems is unusual and responses are usually reactive; there has been a focus on enforcement interventions rather than on the development of broader solutions to problems; and evaluation of outcomes is weak. These findings are discussed in relation to the development of the ASB agenda in England and Wales. Implications for solving problems are discussed.

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Bullock, K. Responding to anti-social behaviour: Analysis, interventions and the transfer of knowledge. Crime Prev Community Saf 13 , 1–15 (2011). https://doi.org/10.1057/cpcs.2010.19

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Published : 21 January 2011

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IELTS Writing Task 2: cause &solution- anti-social behavior and lack of respect to others

Addressing anti-social behavior.

ying_chen 3 / 5   Feb 20, 2018   #3 Hi Kuan, For the two questions type of essay, I agree with your current paragraph structure. -Introduction -Main paragraph: for first question -Main paragraph: for second question -Conclusion The only thing I'd suggest you can improve is in your conclusion session. Using "In conclusion", "to sum up" or other ending phrases and adding the summary in this session will give more overall picture for your article.

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• Crime, justice and law
• Crime prevention
• Impacts of anti-social behaviour on individuals and communities
• Home Office

Anti-social behaviour: impacts on individuals and local communities

Published 27 March 2023

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Executive summary

Background and context.

Despite often being described as ‘low-level crime’, existing evidence suggests anti-social behaviour ( ASB ) can result in a range of negative emotional, behavioural, social, health and financial impacts. These include negative mental health effects, avoidance behaviours and decreased economic productivity. While existing evidence explores what the impacts of ASB are, the Home Office commissioned Ipsos to conduct mixed methods research to better understand the impacts on victims and their wider community. Specifically, to:

• improve current understanding of the individual impacts of ASB on people who have experienced or witnessed it, including quantifying these impacts
• explore the wider impacts of ASB beyond the individual, such as impacts on the community and overall trust in institutions, including quantifying these impacts
• identify differences between ASB types and how this affects the level of impact on the individual and the wider community

This research can support intervention design, targeting support towards those individuals with characteristics linked to more severe impacts. Moreover, it can help to support future research, such as possible future work looking into the scale and costs of the impacts of ASB .

Key findings

Impacts of asb.

Demographics and personal circumstances were associated with different types of ASB that were likely to be experienced or witnessed. Those living in the most deprived areas were more likely to have experienced or witnessed ASB in the last 12 months compared to those in less deprived areas. Those with long-term physical or mental health conditions were more likely to have experienced or witnessed ASB in the last 12 months compared to those without the same conditions. As experiences of ASB were distributed disproportionately, impacts are also likely to be distributed disproportionately. Therefore, interventions could be more effectively targeted to support those groups disproportionately impacted.

ASB had impacted nearly all participants’ quality of life to some degree. This impact was greater when:

• ASB was personally experienced compared to witnessed [footnote 1]
• the ASB incidents were more frequent
• participants had certain personal or situational circumstances that increased their likelihood of experiencing ASB impacts; these included individuals with mental or physical health conditions, those living in more deprived areas and younger people, among others

This study helped to quantify the individual impacts of ASB . Emotional impacts were found among nearly all participants, with annoyance (for 56% of participants) and anger (for 42%) being the most widespread impacts across ASB types. Fear, loss of confidence, difficulty sleeping and anxiety were also common emotional impacts. While they were less commonly experienced (each by around a quarter of participants) , they were described as being more severe and longer lasting.

Many individuals also reported behavioural impacts as a result of ASB , with avoidance behaviours being the most regularly referenced. Around a third (36%) had avoided certain places, and around a quarter (24%) went out less often. Just under a fifth (17%) felt the need to change their travel habits as a result of experiencing or witnessing ASB .

Individual emotional and behavioural impacts were generally similar across types of ASB , however, there were certain types of ASB where different impacts manifested more than others. For example, those who experienced or witnessed people being intimidated/harassed were the most likely to report fear and loss of confidence, whereas those who experienced or witnessed youths/teenagers/groups hanging around were most likely to have reported avoiding certain places.

ASB also impacted wider communities [footnote 2] , both positively and negatively. Participants recognised that while ASB in general could reduce trust and a sense of community by making people avoid interaction, it could also bring people together by having a common cause.

Impacts did not tend to happen in isolation. Instead, they were highly linked between individual emotional and behavioural effects as well as interpersonal, network and community-wide dimensions. Often one impact served as a catalyst for others and created a knock-on effect. For example, a loss of confidence could lead to avoidance behaviours and then a decline in a sense of community. Therefore, ASB interventions targeted at an individual level will also likely be effective in easing community and wider-area impacts.

Demographics were a key factor in influencing the scale of impacts experienced by the individual. Those more exposed to ASB , those who live in more deprived areas or who have a mental or physical health condition were more likely to experience significant impacts. Moreover, younger people, those living in London or Cardiff, people from white ethnic backgrounds and people with higher incomes were more likely to experience a significant impact from ASB . Other factors, such as being pregnant or having children, also played a role in the severity of ASB impacts experienced.

The role of reporting and support

Whether an individual reported the incident, received support or was satisfied with the outcome also influenced – both positively and negatively – the degree of impact felt. Where experiences were negative, participants reported feeling annoyance, hopelessness and a loss of trust in reporting agencies. Similarly, participants felt the impacts they experienced worsened when they were not provided with support that they thought to be appropriate. There were very few differences between ASB types when it came to perceptions of reporting and support.

Those reporting ASB commonly had to gather additional evidence of the ASB taking place before agencies and organisations would take action. This was thought to be burdensome for victims/witnesses, and their avoidance behaviours generally continued while this process was happening. Those reporting incidents were also fearful of repercussions from perpetrators.

Agencies, organisations and those who experienced or witnessed ASB highlighted several ways in which the reporting process and support offered could reduce the negative impacts of ASB . This included timely responses and communication to make sure people feel listened to, options for anonymous reporting, support being delivered through different mediums, involving the community in the resolution process and a more connected formal support system.

1. Introduction

1.1 background.

Despite often being described as ‘low-level crime’ [footnote 3] , existing evidence suggests that ASB can result in a range of negative emotional, behavioural, social, health and financial impacts. ASB has been linked to personal harm including avoidance behaviours, changed routines and an impact on quality of life [footnote 4] . Other implications of ASB include negative mental health, such as living in fear and increased stress and anxiety, leading to experiences of panic attacks and depression. Furthermore, there is evidence to suggest that ASB is associated with negative impacts on the economy. These impacts relate to economic productivity, house prices, the success of local businesses and the prevalence of other crime types [footnote 5] .

ASB covers a wide range of activities. There are several ways in which the different types of ASB can be categorised and managed, including the police’s National Standard for Incident Recording ( NSIR ) [footnote 6] counting rules and the Crime Survey for England and Wales ( CSEW ) [footnote 7] ASB breakdown. In this study, the CSEW categories are used and adapted slightly (the full ASB category list can be found in Annex A ). This provides a more detailed breakdown of ASB types than the 3 categories included in the NSIR . Within this wide range, the impact between one ASB type over another can differ considerably.

There are limitations to the existing evidence base. While existing evidence explores what the impacts of ASB are, there is minimal evidence about how impacts vary across different types of ASB and how impacts interact with different demographics and characteristics. As well as this, available evidence tends to draw on limited sample sizes and is often outdated. These gaps limit the utility and prioritisation of interventions and victim support. By using a mixed methods approach and providing a comprehensive sample size, this research can go some way in filling these gaps and can support intervention design, targeting interventions at those with the most ‘at risk’ characteristics and prioritising types of ASB most likely to cause severe impacts. Moreover, it can help to support future research, such as possible future work into the scale and costs of ASB .

1.2 Research objectives

The Home Office commissioned Ipsos to conduct research to better understand the impacts of ASB on victims and their wider community. Specifically, this research sought to:

1.3 Methodology

1.3.1 summary of the fieldwork design.

To achieve these research aims and objectives, this study used a mixed methods approach, including:

• qualitative focus groups with victims and witnesses of ASB
• in-depth interviews with victims as well as agencies and organisations who respond to ASB
• a quantitative survey with the general public

This report focuses on findings from across the methodologies. An outline of what each of the research methodologies sought to achieve is summarised in Table 1.

Table 1: Summary of what each strand of quantitative and qualitative research aimed to achieve

1.3.2 Qualitative approach

All qualitative research was conducted between March and April 2022 and focused on 5 areas of interest, identified through analysis of police recorded incident data: Liverpool, Leicester, Newcastle upon Tyne, Cardiff and Westminster [footnote 8] .

The qualitative research was made up of 3 methods, including:

• focus groups with victims/witnesses
• in-depth interviews with victims/witnesses
• interviews with agencies and organisations

As with all qualitative research, the findings below may not be applicable to the general population. The high levels of prevalence of ASB and the diverse nature in which it is experienced means that, inevitably, not all impacts will be captured.

Ten focus groups across the 5 case study areas were conducted with victims/witnesses of ASB . Each focus group lasted 2 hours and was made up of 6 participants (60 participants in total). The focus groups provided active discussion between participants to:

• understand where experiences were similar or varied
• enable deliberation over the severity of various types of ASB
• discuss the impacts ASB had on them and those around them

To enable participants to discuss their experiences in this forum without high levels of distress, those who said they were impacted ‘a great deal’ when screened ahead of participating were offered an individual in-depth interview instead.

In-depth interviews with victims/witnesses were used to gain a deeper understanding of the impacts of ASB . A total of 50 one-hour interviews were conducted with victims from each of the 5 case study areas. Interviews focused on the impacts of ASB on them, those around them and their community, and how, if at all, trust in institutions has been affected.

In-depth interviews with agencies and organisations were conducted to better understand their thoughts of the impacts on ASB on individuals and their wider networks. Interview participants included representatives from local police forces, local authorities and housing associations. Thirty-five hour-long interviews were conducted with local agencies and organisations, and 5 hour-long interviews were conducted with national agencies and organisations.

Sample tables and discussion guides for each of the above approaches can be found in Annex B and Data collection materials (section 1) , respectively.

1.3.3 Quantitative approach

The quantitative survey was conducted via Ipsos’ online panel, ‘iSay’, between 13 and 23 March 2022. The survey collected responses from 2,500 participants living in England and Wales who had either personally experienced or witnessed ASB in the previous 12 months. These participants were asked to select the types of ASB they had experienced/witnessed from a set list of 13 ASB types (the full category list can be found in Annex A ). These were adapted, in collaboration with the Home Office from the CSEW , to provide a more detailed breakdown of types and for consistency as much as possible with other existing datasets. Sample information can be found in Annex B .

For national representativeness, overall survey data [footnote 9] was weighted to nationally representative proportions based on age, gender, region and Index of Multiple Deprivation ( IMD ) score [footnote 10] .

Participants were asked about their overall experiences of ASB in their local area, as well as the detailed emotional and behavioural impacts from the specific incidents they had experienced/witnessed. The full survey questionnaire can be found in Data collection materials (section 2) .

Statistical analysis was conducted to understand whether one overarching demographic factor was creating differences in perceptions, experiences and impacts. No single demographic factor was found to do this; instead, multiple factors played a role.

Unless otherwise specified, throughout this report, all statistical comparisons between stated figures are significant at the 95% confidence level. Where sample sizes are below n=50, these will be highlighted and should be interpreted with caution.

1.4 Report structure

Section 2: understanding whom asb impacts.

This provides an overview of the perceptions and experiences of ASB , including whether people perceived ASB as a crime. It also outlines the types of ASB participants have witnessed or experienced in the past 12 months to understand how impacts may be distributed.

Section 3: Understanding the impact of ASB on individuals

This explores the impact of ASB at an individual level, including considering the quality of life, emotional impacts, behavioural impacts, and instances where there is no impact on the individual.

Section 4: Wider impacts beyond the individual

This looks at the broader level of impact of ASB , including the impact on the personal network of victims, the impact at a community level and the structural impacts of it.

Section 5: Personal factors influencing ASB impacts

This explores in depth the factors that influence the impact of ASB . The factors considered range from personal characteristics such as age, gender and ethnicity, to broader factors such as region, levels of income and health.

Section 6: The impact of the response to reporting ASB

This looks at the role incident reporting to agencies and support has on the experience of the impacts of ASB , both negative and positive.

Section 7: Conclusions

This explores the insights that can be drawn from the research to inform policy and interventions.

Both qualitative and quantitative findings have been used throughout the report and are identified where used. Quotes from participants have been used to illustrate findings throughout the report. Quotes are attributed based on how participants define themselves and their experiences [footnote 11] .

2. Understanding whom ASB impacts

This Section explores how the perception and experience of ASB vary among different demographic groups. It, therefore, allows for a better understanding of how the impacts of ASB tend to be distributed among different groups of people and how this can ultimately influence the level of impact ASB has on an individual and their wider network. It concludes that there is a need to tailor interventions for relevant demographic factors to account for the varying impacts and type of support required.

Key findings:

There were several factors that influenced perceptions and experiences of ASB . Those that contributed to negative perceptions included the extent to which ASB was considered a problem in the local community, the level of deprivation in the local area and health-related factors. This suggests that interventions to support those experiencing/witnessing ASB should target these core groups and account for their needs.

Across most types of ASB , men were more likely than women to have personally experienced ASB . Women were more likely to have witnessed ASB .

There was recognition that what is classed as an ASB incident is subjective depending on the incident and the individual experiencing/witnessing it. The highest earners (£45K and above annual income) were more likely than those with a lower income to view ASB incidents as a crime. There was more acceptance of ASB among the youngest age group (those aged 18 to 34) who were more likely to view incidents they experienced/witnessed as ‘normal’ behaviour.

The extent to which ASB was seen as a problem at a local level differed greatly by demographics such as age, gender, region and personal circumstances. While the youngest (those aged 18 to 34) were more likely to interpret incidents as ‘normal’ behaviour, they were also more likely than those aged 35 and above to feel that ASB is a ‘very/fairly big’ problem in their local area. This suggests that they have a consistently high exposure to incidents.

2.1 Differences in perceptions of ASB

2.1.1 defining asb.

Across the qualitative research, agencies, organisations and individuals who have experienced or witnessed ASB were asked how they would define ASB and then shown the Anti-social Behaviour, Crime and Policing Act 2014 definition [footnote 12] . The views of agencies, organisations and members of the public typically aligned with the definition, describing ASB as behaviour that disrupted standards of living, or that caused distress or nuisance to others.

However, the nuances of how this definition was interpreted varied. Both agencies/organisations and victims/witnesses recognised that the causes and meaning of nuisance or distress could be subjective depending on the individual experiencing or witnessing it.

‘I think different officers [housing officers, Community Safety Partnership officers] would define ASB in different ways.’ Stakeholder, local authority, Leicester

‘It’s a difficult one because everyone has their own interpretation.’ Witnessed and experienced ASB, male, 24, Newcastle upon Tyne

Moreover, qualitative participants perceived different types of ASB to sit on a scale of severity. This was also reflected in the survey findings, where participants had inconsistent views on which types of behaviour would be considered ‘normal’, anti-social or a crime Figure 2.1 . While some behaviours had greater consensus, all 13 types of behaviour were viewed as ‘a crime’, ‘anti-social but not a crime’ or ‘normal behaviour’ to varying degrees.

Survey participants were more likely to perceive people using/evidence of drugs (71%) and vandalism (65%) as a crime. On the other hand, ASB related to the community was more commonly perceived as anti-social but not a crime, such as loud music/noise (75%), inconsiderate behaviour (73%), youths/teenagers/groups hanging around (68%) and drunken behaviour (67%). The boundary at which ASB becomes a crime was less clear for sexual ASB [footnote 13] . Two-in-five of those who had experienced/witnessed sexual ASB (44%) believed this type of behaviour to be a crime, and a similar proportion (47%) believed it to be anti-social but not a crime.

The variety in how the types of ASB are perceived is likely to influence the ways in which those who witness or experience each type respond. For example, those who experience or witness types that are more commonly perceived as a crime may be more likely to report it to the police. This should be considered when measuring the prevalence of ASB types. The variety of perceptions is also likely to influence the type of impact felt by participants, with those considered a crime likely to have deeper, longer-term impacts.

Figure 2.1: Perceptions of different types of ASB as a crime, anti-social but not a crime or ‘normal’ behaviour (%)

• Base size: All who have witnessed/experienced type of ASB in last 12 months and answered the question: people using/evidence of drugs (523), vandalism (516), sexual ASB (116), vehicle-related ASB (585), people being intimidated/harassed (464), environmental ASB (432), problems with out-of-control dogs (195), aggressive begging (321), nuisance neighbours (477), drunken behaviour (505), inconsiderate behaviour (673), youths/teenagers/groups hanging around (712), loud music/noise (534).

2.1.2 Demographic differences when defining ASB

The survey highlighted demographic factors, including income and age, that influenced perceptions of what should be defined as ‘normal’ behaviour, ASB or a crime.

Those in the highest annual income bracket (£45K and above) were more likely to view the incidents they experienced or witnessed as a crime, while those with a lower income were more likely to view the incidents they witnessed as anti-social but not a crime, or ‘normal’ behaviour.

Age also emerged as a factor that influenced perceptions of ASB . The survey results showed that ASB was more normalised among the youngest age group (those aged 18 to 34) than it was for those in the older age groups. These respondents were more likely to view incidents they had experienced and/or witnessed related to youths/teenagers/groups hanging around, drunken behaviour, vandalism, inconsiderate behaviour, people using/evidence of drugs and environmental ASB as ‘normal’ behaviour compared to those who were in the older age groups. Across all the same incidents, those aged 35 and over viewed these as either anti-social but not a crime, or a crime rather than as ‘normal’ behaviour. The qualitative research aligned with this, with older participants tending to associate ASB with younger people being inconsiderate and smoking, drinking and fighting.

This suggests that income and age are likely to influence the extent to which an impact is felt from different types of ASB . This may also influence the likelihood of reporting the incident.

2.1.3 Demographic differences in perceptions of ASB as a local problem

Survey results showed mixed perceptions of the extent to which ASB was considered a problem within the participant’s local area. As seen in Figure 2.2, almost half (47%) indicated that they perceived ASB to be a ‘very’ or ‘fairly’ big problem in their local area, while 50% of respondents viewed ASB as ‘not a very big problem’ or ‘not a problem at all’ in their local area [footnote 14] . Despite this mixed picture, there was a greater consensus among respondents that levels of ASB had increased. More than half (59%) indicated that they thought ASB had gone up ‘a lot’ or ‘a little’ over the last few years in their local area, with only 8% thinking it had gone down ‘a lot’ or ‘a little’.

Figure 2.2: Levels of perception of ASB as a problem in the local area (%)

• Base size for Q1 and Q2: All (2,500).
• Base size for Q3: Those who said ASB in their area has gone up or down in the last few years (1,667).

Perceptions of the extent to which ASB was considered to be a problem in local areas varied based on certain demographics and characteristics. These demographics may influence the extent to which an impact from ASB is felt as well as the likelihood of reporting the incident.

Age was key in determining views, with the youngest age group (those aged 18 to 34) being more likely to feel that ASB is a ‘very big’ or ‘fairly big’ problem in their local area (57%) than those aged 35 to 54 (50%) and those aged 55 and over (34%). This was despite the 18 to 34 age group being more likely to interpret ASB as ‘normal’ behaviour across a number of ASB types, as described above. Participants across the qualitative research with members of the public suggested that this could be a result of younger people being more exposed to ASB , making them more aware of instances. However, in contrast to this, those aged 18 to 34 were least likely to believe ASB had gone up ‘a little’ or ‘a lot’ in the last few years (53%) compared to those aged 35 to 54 (63%) and those aged 55 and over (60%). This suggests that exposure has been consistently high among this younger age group.

Perceptions also varied by gender, with more men (50%) indicating that ASB was a ‘very big’ or ‘fairly big’ problem in their local area compared to women (44%). Men were also more likely to believe that the level of ASB had gone up ‘a lot’ (25%) in their local area over the past few years than women (18%). This could be connected to the fact that more men reported personally experiencing ASB in the survey.

The quantitative survey showed that region also influenced perceptions of how much of a problem ASB was. At a regional level, participants who lived in London were most likely to consider ASB to be a ‘very big’ or ‘fairly big’ problem (63%), followed by participants in Wales and the North East of England (both at 53%).

Perceptions also varied based on the level of deprivation (based on IMD ) [footnote 15] . Figure 2.3 shows that the more deprived an area is classified to be, the more likely ASB is thought to be a problem locally. Qualitative interviews with agencies and organisations that worked in areas of higher deprivation suggested that this could be connected to wider socio-economic issues experienced in these areas. These include reduced access to services like youth clubs, higher levels of unemployment and substance abuse issues. This highlights the importance of viewing and responding to perpetrators and victims in the context of their own experiences.

‘There’s an absolute recognition that people who are perpetrating ASB are probably perpetrators because they’ve had adverse childhood experience, that they’ve been through some sort of trauma, that they’ve got mental health, drug, and alcohol issues.’ National stakeholder

‘Anti-social behaviour is almost always a product of the environment and the, kind of, socio-economic background, but also it comes from boredom. People do not take part in anti-social behaviour when they’ve got better things to do.’ Witnessed ASB, female, 31, Newcastle upon Tyne

Figure 2.3: Extent to which people think ASB is a problem in their local area by the level of deprivation (%) [footnote 16]

• Base size: All (2,500).

Personal circumstances, including social grades, housing circumstances and mental and physical health, also influenced perceptions of the extent to which ASB was a problem at a local level. Those classified as C2DE were more likely to believe ASB to be a ‘very big’ or ‘fairly big’ problem (56%) than those who are ABC1 (45%) [footnote 17] . Similarly, those who resided in a flat were more likely to believe ASB is a ‘very big’ or ‘fairly big’ problem (59%) compared to those who lived in a house (44%). This could be a result of living in closer proximity to others, and therefore a greater potential to be living in closer proximity to instances of ASB .

In terms of mental and physical health, more than a quarter (28%) of participants who had a long-term physical or mental health condition believed that the level of ASB had gone up ‘a lot’ over the past few years. This is compared to 18% of those who did not have the same conditions. Additionally, participants who had a long-term physical or mental health condition were more likely (51%) to believe their area had a ‘very big’ or ‘fairly big’ problem with ASB compared to those who did not suffer from the same conditions (45%). This indicates that vulnerabilities should continue to be a key consideration when responding to and supporting victims of ASB , particularly when related to mental and physical health.

2.1.4 Perceptions of the impact of coronavirus (COVID-19)

As shown in figure 2.2 , two thirds (67%) of survey respondents thought that the COVID-19 pandemic had played a role in the levels of ASB changing in their local area, and as a result, influenced the impact felt. In total, 56% of respondents thought it played a role in ASB going up ‘a lot’ or ‘a little’, while 11% thought it played a role in ASB going down either ‘a little’ or ‘a lot’. Qualitative interviews with individuals who had witnessed/experienced ASB suggested that the perceived increase was a result of an increased amount of time spent at home, meaning perpetrators had more time to commit ASB or that victims were more aware of incidents occurring around their homes. The perceived increase in ASB during the COVID-19 pandemic suggests that the impacts felt may also have increased.

Similar to other perceptions of ASB , opinions on the role of COVID-19 varied based on different factors. The survey showed that those living in a flat were more likely to believe that COVID-19 had caused an increase in ASB (63%) than those living in a house (55%). The qualitative research suggested that this was a result of being at home more and that those in a flat were in closer proximity to their neighbours than those in a house. Those in the highest annual income bracket of £45K and above (66%) also perceived ASB to have increased as a result of the COVID-19 pandemic more than those earning £15,000 to £44,999 (51%) and those earning up to £14,999 (50%).

2.2 Differences in experiencing/witnessing ASB

2.2.1 demographic differences in asb experienced/witnessed.

Participants involved in the research experienced and witnessed a broad range of ASB types, as can be seen in Figure 2.4. Youths/teenagers/groups hanging around was the most prevalent, with two in five (41%) survey participants having personally experienced or witnessed this type of ASB , followed by inconsiderate behaviour at 38% and vehicle-related ASB at 35%.

Figure 2.4: Types of ASB personally experienced or witnessed in the last 12 months in the local area

Several factors influenced perceptions and experiences of ASB , and therefore, the distribution of impacts. These included the extent to which ASB was considered a problem in the local area, and demographic factors including age, gender, level of deprivation in the local area and health-related factors.

The survey data highlighted a connection between participants’ perceptions of ASB as a problem in their local area and their experiences. While the mean number of types of incidents experienced or witnessed in the last 12 months in the local area was 3.7, this rose to 4.3 for those who believed ASB to be a ‘very big’ or ‘fairly big’ problem in their local area. This demonstrates a link between perceptions of ASB in the local area and personal experience.

Men (compared to women), those aged 18 to 34 (compared to those aged 35 and above), and people residing in the most deprived areas (compared to the least deprived) were significantly more likely to have personally experienced or witnessed ASB in the last 12 months according to the survey results. The less deprived the area, the less likely people were to have personally experienced or witnessed an ASB incident.

Those who had a long-term physical or mental health condition were also more likely to have personally experienced or witnessed ASB than those without the same conditions.

As a result of more commonly experiencing or witnessing ASB incidents, these groups are likely to disproportionately feel the impacts of ASB . This suggests that interventions to support those experiencing or witnessing ASB should target these core groups and account for their needs.

2.2.2 Witnessing compared to experiencing ASB

There was some variation as to which ASB types were more likely to be experienced or witnessed, as seen in Figure 2.5. In some cases, experiencing was more common than witnessing. Of those who had experienced/witnessed nuisance neighbours, 60% had personally experienced this rather than witnessed it. There were also higher proportions of experience with loud music/noise (57%), aggressive begging (56%), problems with out-of-control dogs (56%) and sexual ASB (56%). In other cases, witnessing was more common than experiencing. There were proportionally more people that had witnessed people using/evidence of drugs (69%), vandalism (62%), drunken behaviour (61%) and environmental ASB (61%), than people that had experienced these.

It is worth noting that some types of ASB were more commonly witnessed rather than experienced based on their very nature. For instance, people using/evidence of drugs and drunken behaviour are not behaviours that can inherently be targeted towards an individual and are, therefore, more likely to be witnessed rather than directly experienced by an individual. The trends discussed above reflect these expected splits. Attribution to whether an incident of ASB was experienced or witnessed was done by participants, meaning it is subjective.

Figure 2.5: Proportion of those who experienced compared to witnessed ASB , by type (%)

• Base size: All who have witnessed/experienced type of ASB in last 12 months and answered the question: nuisance neighbours (477), loud music/noise (534), aggressive begging (321), problems with out-of-control dogs (195), sexual ASB (116), people being intimidated/harassed (464), inconsiderate behaviour (673), vehicle-related ASB (585), youths/teenagers/groups hanging around (712), environmental ASB (432), drunken behaviour (505), vandalism (516), people using/evidence of drugs (523).

The survey found that personally experiencing ASB had a greater impact on individuals than those who were witnesses to it. The 4 most impactful types of ASB (sexual ASB , nuisance neighbours, problems with out-of-control dogs and loud music/noise, see sub-section 3.1.1 ) were all more commonly experienced rather than witnessed. Qualitative research suggested that experiencing ASB was more impactful because the incident felt targeted at them as an individual rather than it being an action that they had happened upon by chance. As such, it resonated with them more emotionally.

Survey results showed that some types of ASB were more likely to be personally experienced or witnessed by certain demographics. Across most types, men were more likely than women to have personally experienced ASB [footnote 18] . This was significantly so for drunken behaviour (38% for men compared to 29% for women), people using/evidence of drugs (30% for men compared to 22% for women) and environmental ASB (42% for men compared to 26% for women).

The support requirements for those who have experienced compared to witnessed ASB may vary, and therefore this should be considered when targeting support-based interventions.

2.2.3 Demographic/circumstantial differences in frequency of ASB experienced/witnessed

As illustrated by Figure 2.6, the quantitative survey showed nuisance neighbours (42%), environmental ASB (39%), people using/evidence of drugs (39%), aggressive begging and sexual ASB (both 38%) to be the types of ASB that were likely to happen most frequently (once a week or more often). In contrast, people being intimidated/harassed (55%) and vandalism (53%) were likely to occur less frequently (less often than once or twice a month).

Figure 2.6: Frequency with which different types of ASB are experienced/witnessed (%)

• Base size: All who have witnessed/experienced type of ASB in last 12 months and answered the question: nuisance neighbours (477), environmental ASB (432), people using/evidence of drugs (523), aggressive begging (321), sexual ASB (116), loud music/noise (534), problems with out-of-control dogs (195), vehicle-related ASB (585), youths/teenagers/groups hanging around (712), inconsiderate behaviour (673), drunken behaviour (505), vandalism (516), people being intimidated/harassed (464).
• Nets: Once a week or more = every day/almost every day; at least once a week. Once or twice a month = at least once a fortnight; at least once a month. Less often = a few times in the last 12 months; once in the last 12 months.

The data indicated several demographic factors that contributed to the frequency with which ASB types were experienced or witnessed. For example, across the different types of ASB , the general trend was that men were more likely than women to personally experience or witness an ASB incident ‘once a week or more often’. This was significantly so for vandalism (25% for men, compared to 14% for women), inconsiderate behaviour (31% for men, compared to 24% for women), people being intimidated/harassed (25% for men, compared to 14% for women), aggressive begging (44% for men, compared to 31% for women) and sexual ASB (49% for men, compared to 23% for women).

Age also interacted with the reported frequency of experiencing or witnessing ASB . Those in the oldest age group (aged 55 and above) were significantly more likely to have experienced/witnessed ASB ‘less often than once or twice a month,’ across most ASB types, apart from nuisance neighbours, environmental and sexual ASB , when compared to those aged 18 to 34.

Across most ASB types aside from environmental ASB , aggressive begging and sexual ASB , those who believed ASB to be a ‘very big’ or ‘fairly big’ problem in their local area were significantly more likely to have experienced/witnessed ASB at least once a week than those who believed ASB to be less of a problem or not a problem at all locally. Across these same ASB types, there was a link between impact on quality of life and ASB frequency. Those experiencing the most significant effect were more likely to have experienced/witnessed ASB at least once a week than those who had seen ‘little effect’. As such, those experiencing/witnessing ASB the most often are more likely to require community-based support to help tackle ASB within their local areas as well as additional targeted ongoing support from future interventions.

3. Understanding the impact of ASB on individuals

This Section explores the impact that different types of ASB can have on those who experience or witness it. The survey covered a range of impacts that can affect an individual’s quality of life, including emotional and behavioural impacts. These impacts were also explored at length in the interviews with the public, which provided detailed examples and nuance. Findings also highlight the connection that often exists between the range of ASB impacts experienced by victims.

• ASB had negatively impacted nearly all participants’ quality of life to some degree. This impact was greater when ASB was personally experienced compared to witnessed, when the ASB incidents were more frequent, or when victims had certain personal or situational circumstances that increased their likelihood of experiencing ASB impacts.
• The types of ASB that were most likely to have a significant impact on participants’ quality of life were sexual ASB , nuisance neighbours, problems with out-of-control dogs and loud music/noise.
• Findings from the quantitative survey suggested that those who experienced or witnessed sexual ASB experienced very profound impacts. Across all types of ASB , sexual ASB was associated with the highest proportion of participants who felt the quality of their lives had been significantly impacted. However, while speculative, the findings from the qualitative research suggest that this could be because of the misinterpretation of sexual ASB as sexual harassment, which could result in more severe impacts.

Annoyance and anger were the most common emotional impacts experienced across most types of ASB . Fear and loss of confidence were also common. More serious psychological effects, such as anxiety/panic attacks and depression, were experienced by around one in five of those who had experienced or witnessed ASB in the past year.

The most common behavioural impact across types of ASB was avoidance, which included avoiding certain places or situations, going out less often and changing travel plans. Just over half of participants reported avoidance behaviours as a result of ASB .

• There were several different ways that people who experienced/witnessed ASB had been impacted financially. These included the loss of employment/change of jobs, investment in security measures and investment in repairing damage caused by ASB .

3.1 Quality of life

3.1.1 impact on quality of life.

Almost all survey participants (92%) reported their quality of life being negatively impacted by ASB in some way [footnote 19] . However, the level of impact was not universal among these participants. As demonstrated in Figure 3.1, 36% said that the ASB incidents they encountered had ‘little effect’ on their quality of life, while 35% said it had ‘some effect’ and 21% reported it to have a ‘significant effect’ on their quality of life.

Figure 3.1: Degree of ASB impact on survey participants’ quality of life, across all types of ASB experienced/witnessed

When looking at the impact of ASB on individuals’ quality of life by type of ASB , there are several types which appear to have had a greater effect. For instance, Figure 3.2 illustrates that those who experienced or witnessed sexual ASB [footnote 20] , nuisance neighbours, problems with out-of-control dogs and loud music/noise were more likely to report a significant effect [footnote 21] on their quality of life compared to other types of ASB .

Figure 3.2: The impact of ASB on survey participants’ quality of life, per type of ASB (%)

• Base size: All who have witnessed/experienced type of ASB in last 12 months and answered the question: sexual ASB (116), nuisance neighbours (477), problems with out-of-control dogs (195), loud music/noise (534), people being intimidated/harassed (464), aggressive begging (321), vandalism (516), inconsiderate behaviour (673), environmental ASB (432), vehicle-related ASB (585), drunken behaviour (505), people using/evidence of drugs (523), youths/teenagers/groups hanging around (712).

Several factors influenced the extent to which quality of life was impacted. These included whether the ASB was experienced compared to witnessed, and the frequency. As such, these factors should be considered when designing and implementing support interventions for victims of ASB .

Figure 3.3 depicts the individuals who claimed that ASB had a significant impact on their life, broken down by whether they had experienced or witnessed the type of ASB . Those who had personally experienced ASB were the most likely to have felt a greater negative impact, compared to those who had only witnessed or those who had either witnessed or personally experienced it. For example, out of those who experienced vandalism, the majority (68%) had felt a significant effect, whereas a much smaller proportion of those who had witnessed only (5%) felt a significant effect.

The total of percentages for each type of ASB do not equal 100% as bases for each type of ASB include participants who had only personally experienced or witnessed that type of ASB in addition to participants who had either personally experienced or witnessed that type of ASB (which may include participants who have both personally experienced and witnessed that type of ASB ).

Figure 3.3: Type of encounter (experienced/witnessed) among survey participants who felt a significant impact on their quality of life from ASB , per type of ASB (%) [footnote 22]

Percentages are marked with an asterisk where the base size is below 50. Given the sample size these figures are based on, these findings should be interpreted with caution.

Base size: All answering about type of ASB who experienced significant impact. Sexual ASB : experienced (34), witnessed (3), experienced/witnessed (21); vandalism: experienced (62), witnessed (10), experienced/witnessed (44); nuisance neighbours: experienced (76), witnessed (16), experienced/witnessed (85); people using/evidence of drugs: experienced (40), witnessed (13), experienced/witnessed (39); problems with out-of-control dogs: experienced (36), witnessed (6), experienced/witnessed (20); drunken behaviour: experienced (51), witnessed (13), experienced/witnessed (26); loud music/noise: experienced (73), witnessed (12), experienced/witnessed (72); aggressive begging: experienced (40), witnessed (12), experienced/witnessed (37); people being intimidated/harassed: experienced (54), witnessed (11), experienced/witnessed (65); environmental ASB : experienced (36), witnessed (9), experienced/witnessed (43); inconsiderate behaviour: experienced (58), witnessed (21), experienced/witnessed (54); vehicle-related ASB : experienced (41), witnessed (19), experienced/witnessed (46); youths/teenagers/groups hanging around: experienced (38), witnessed (8), experienced/witnessed (51).

The frequency of ASB incidents also played a role in the severity of the impact on the quality of one’s life, with some types of ASB fitting this trend more than others. For instance, experiencing or witnessing nuisance neighbours typically occurs frequently, with 42% of those who experienced/witnessed this type of ASB stating that it happened once a week or more. This weekly experience with nuisance neighbours translated into a more severe effect on the quality of life, with 68% reporting a significant effect. Figure 3.4 depicts the breakdown of ASB frequency among survey participants who reported a significant impact from ASB . A smaller proportion of those who had experienced a significant impact had experienced the incidents less often, suggesting that higher frequency leads to a higher impact from ASB .

Figure 3.4: Frequency of ASB incidents among survey participants who felt a significant impact from ASB , per ASB type (%) [footnote 23]

• Percentages are marked with an asterisk where the base size is below 50. Given the sample size, these figures are based on, these findings should be interpreted with caution. 2.Base size: All who have witnessed/experienced type of ASB in last 12 months and who felt a significant impact from ASB : People using/evidence of drugs (92), aggressive begging (89), nuisance neighbours (177), environmental ASB (88), drunken behaviour (90), sexual ASB (58), problems with out-of-control dogs (63), loud music/noise (157), youths/teenagers/groups hanging around (97), inconsiderate behaviour (133), vehicle-related ASB (107), vandalism (116), people being intimidated/harassed (130).

These findings were also reflected in the qualitative interviews with individuals who had experienced types of ASB occurring frequently. Participants perceived ASB experienced frequently in the home (such as nuisance neighbours) to be particularly debilitating for one’s quality of life as well as their mental health as they felt there was no escape. This view was echoed by agencies and organisations who also perceived that not being able to escape the situation had a significant impact on individuals.

‘Again, it’s more the persistent anti-social behaviour where that’s a problem. We have a lot of people with anxiety and depression. So yes, it can have such a negative impact on somebody’s life and again, more so when it’s somebody who’s living in it and can’t leave. So, if it’s a neighbour dispute or if it’s something , it tends to be a lot more severe.’ Stakeholder, local authority, Leicester

3.1.2 Sexual ASB

Findings from the quantitative survey suggested that those who experienced or witnessed sexual ASB experience very profound impacts. Across all types of ASB , sexual ASB had the highest proportion of participants who felt their quality of life had been significantly impacted (47%) [footnote 24] . Additionally, those who experienced or witnessed sexual ASB had the third highest [footnote 25] number of emotional impacts per person (3.4 impacts on average per person) and the highest number of behavioural impacts per person (2.8 impacts) compared with all other types of ASB . To explore why the effects are so severe for sexual ASB , this sub-section considers what participants understood sexual ASB to be.

The definition of sexual ASB used in the research encompasses several different behaviours, including prostitution or: ranging from prostitution and evidence of prostitution, to finding used condoms and people committing inappropriate or indecent sexual acts in public. While this definition does not explicitly cover sexual harassment, it appears that many participants understood it as such. For example, when speaking about sexual ASB in the qualitative interviews, many reported inappropriate sexual comments or catcalling in the streets. In fact, most participants who mentioned sexual ASB appeared to confuse it with sexual harassment, specifically towards females.

‘Yes, like I said, I don’t know, it would be if they were surrounding you and intimidating you, them thinking it was funny, but it could have a real [impact], especially on an older person, perhaps. Or like what happened to my friend’s daughter, when she was sexually harassed. That is quite a big thing, isn’t it, especially if you’re 18.’ Witnessed ASB, male, 55, Leicester

‘I was jogging round the park and there was this young female in front of me and these 3 young boys, I’d say about 15, 16, just hurled, they said the most repulsive, derogative, horrible words to her.’ Witnessed and experienced ASB, male, 65, Westminster

Furthermore, as referenced in sub-section 2.1.1 , there were mixed feelings on whether sexual ASB should be classified as a crime. Nearly half (47%) found it to be anti-social, but not a crime and 44% deemed it to be a crime. The qualitative interviews highlighted that those who thought it should be a crime brought up the same themes of sexual harassment and male aggression, and more severe, longer-term impacts were discussed.

‘Sexual anti-social behaviour should be classed as crime, rather than ASB… Well, I think sexual anti-social behaviour sounds terrible, and it feels to me worse, and to be honest, it’s usually one way, isn’t it, as well? You know, it’s men against women.’ Witnessed ASB, male, 55, Leicester

These interpretations of sexual ASB provide greater context for the quantitative results, which suggest that those who experienced/witnessed sexual ASB experience very severe impacts from it. The findings from the qualitative research suggest that this could in some part be due to the misinterpretation of sexual ASB as sexual harassment, which could result in greater impacts. In future research designs, references to sexual ASB could be amended to reduce participant confusion by adding a caveat to the end of the definition, indicating that sexual ASB does not include sexual harassment or catcalling.

3.2 Emotional impacts

3.2.1 overview of emotional impacts.

Emotional impacts were experienced almost unanimously by people who had witnessed/experienced ASB . As demonstrated in Figure 3.5, more than 9 in 10 (93%) of people experienced at least one emotional impact. During the qualitative interviews, participants also described feeling multiple emotional reactions simultaneously, indicating that these emotions were not mutually exclusive.

Figure 3.5: Emotional impacts from ASB , across all types of ASB [footnote 26]

The most common emotional impacts were annoyance (with 56% of participants experiencing this as a consequence of ASB ) and anger (42%). Fear and loss of confidence were also common, with a quarter of participants stating they had felt these emotions due to ASB experienced or witnessed in the last year (25% and 24%, respectively).

Qualitative research demonstrated that many of the emotional reactions had a corresponding behavioural impact or action (behavioural impacts are discussed in more detail in sub-section 3.3 ). For instance, in qualitative interviews, fear and loss of confidence were often linked to behavioural actions such as avoidance, as participants changed their routines to make sure they did not need to go to certain places where they were afraid of encountering ASB .

‘And, also, when I go for a run now, I’ll go along the road rather than down through the [location removed] just in case there are any gangs down there.’ Witnessed ASB, female, 42, Newcastle upon Tyne

Less commonly reported emotional impacts included difficulty sleeping (22%), anxiety/panic attacks (19%), shock (18%), depression (15%), embarrassment/shame (13%), loneliness/isolation (10%) and crying (9%). While less commonly experienced, these impacts are likely to manifest themselves with more depth psychologically and were described in the qualitative interviews as being more distressing than many of the more commonly experienced emotional impacts.

Across both the survey and interview findings, it was apparent that the emotional impacts were more prevalent in relation to certain types of ASB . The following sub-sections explore the range of emotional impacts that survey and interview participants reported experiencing in relation to the different types of ASB .

3.2.2 Annoyance and anger

Annoyance and anger were the most common emotional impacts experienced for most types of ASB . Across all types, 56% and 42% of participants said they experienced these impacts, respectively. These 2 emotional impacts tended to be merged by participants in the qualitative interviews, although anger was seen as slightly more severe whereas annoyance was more of a mild frustration.

Annoyance was particularly high for nuisance neighbours (66%), inconsiderate behaviour (61%) and environmental ASB (60%). This annoyance was also linked with feeling immediate frustration with the situation.

‘I was very frustrated when I roll over dog poo with a pushchair. That’s really, really horrible.’ Witnessed ASB, female, 27, Leicester

Participants explained their annoyance, stating that it tended to be a result of perpetrators acting selfishly or with a disregard for others.

‘I think you can tell in my voice. It just raises my blood pressure a little bit… because they’re putting what they think is their views above everybody else’s.’ Witnessed ASB, male, 55, Leicester

Anger was also particularly high among many of the same types of ASB . For instance, of those who experienced or witnessed nuisance neighbours, 48% reported feeling angry, which was significantly higher than for all other types. Additionally, anger was also the most common emotional impact for people who witnessed or experienced being intimidated/harassed (42%), inconsiderate behaviour (42%), vehicle-related ASB (42%), environmental ASB (41%), problems with out-of-control dogs (38%) and vandalism (38%).

One individual who witnessed a dog being killed by another out-of-control dog explained how the incident induced anger at the fact that other dog owners did not seem to care or feel responsible for their actions.

‘Yes, it made me extremely upset for the dogs, and for the lady, that we witnessed her lose her dog. It made me very angry that there are owners out there that just don’t care enough about their dogs, and other people’s dogs.’ Witnessed ASB, female, 33, Leicester

3.2.3 Fear, loss of confidence, anxiety and depression

Other common emotional impacts were fear, loss of confidence, anxiety and depression, which tended to be interlinked. Fear often caused individuals to lose confidence or develop anxiety, which led them to be more isolated (see sub-section 3.2.6 ) and depressed.

Fear and loss of confidence were each experienced by about a quarter of participants who experienced/witnessed ASB in the past year (25% and 24%, respectively). Feelings of fear and loss of confidence were often linked with corresponding avoidance behaviours – with participants explaining that these feelings caused them to avoid certain places or situations, go out less often and change travel habits.

Fear was a widespread emotional reaction, particularly for people being intimidated/harassed (35%), problems with out-of-control dogs (32%) and sexual ASB (26%). For example, one individual experienced being intimidated/harassed on multiple occasions and also having a brick thrown through her window. This caused her to feel extremely scared and afraid of being at home.

‘I was shaken for ages afterwards. I felt really shaken up, you know, very shaken for a while after.’ Experienced ASB, female, 62, Cardiff

Another example came from an individual who had witnessed out-of-control dogs, and an incident where a dog attacked and injured another dog, which made her fearful of walking her dog.

‘So, that scared me, and it was on my mind all the time. What if that had been my old boy? They’d have killed him; they’d have definitely killed him without a doubt. So, it made me wary of walking there.’ Witnessed ASB, female, 59, Cardiff

Fear also manifested when there was a concern about backlash or potential dangers from perpetrators. In qualitative interviews, victims discussed that fear of retaliation from the perpetrator had deterred them from reporting and involving the police (see sub-section 6.1 for further detail). This fear also led to avoidance behaviours, such as making the individual afraid to leave the house as they worried about perpetrators confronting them.

‘I think the worst thing in that situation is if the culprits ever find out that you’re the person who’s actually spoken to the police or whatever because then they make your life hell, do you know what I mean? They end up doing whatever, and then you’re afraid to go out, you know, because you think, God, they’re usually in groups anyway, so you might go out and not come back home. A form of bullying, isn’t it?’ Experienced ASB, female, 62, Cardiff

Loss of confidence was most likely to be reported among those who experienced/witnessed people being intimidated/harassed (31%), youths/teenagers/groups hanging around (26%) and sexual ASB (25%).

For those who encountered youths/teenagers/groups hanging around, many felt unsafe and intimidated by their presence. This resulted in a lack of confidence in returning to the areas where it occurred and into their local areas/neighbourhoods. As a result, victims spoke of changing travel routes and taking additional precautions, such as not going out alone. Further information on behavioural impacts can be found in sub-section 3.3 .

‘I do get nervous when I see loads of gangs outside walking the streets. You don’t know what they’re going to do, so I guess the impact is it is a bit nervous, but I am looking to move, because I’ve been there nearly 2 years now. I do want to move.’ Witnessed ASB, female, 26, Cardiff

‘You get that, sort of, lingering anxiety. You’re checking over your shoulder and looking around as you are leaving your home or as you go about your day. For a while, I’ve felt, the best thing to do is leave the neighbourhood as quickly as possible. I just felt that I wasn’t able to lead a safe neighbourhood life and was aware that was a really sorry affair to have to have this in mind.’ Experienced ASB, male, 55, Westminster

Furthermore, one participant spoke about experiencing intimidation or harassment due to their race or the way they look, causing them to lose confidence to go to places they normally visited. The experience and resulting impact reflected that of a hate crime [footnote 27] , which sees many overlaps with this type of ASB . This reflects a broader issue in how victims/witnesses and agencies/organisations distinguish ASB from other forms of crime, such as hate crime.

‘It affected me immensely because I didn’t expect in the 21st century when I’m going out to be racially or verbally abused because of the way I look. The way I dress, who I hang out with, my religion whatever this, that and the other. It seems to be more violence rather than just shouting across the street and I’ve had to change the places that sometimes I used to go to but I don’t go anymore. In the winter especially I might decide not to go out that night because I don’t feel comfortable.’ Experienced ASB, male, 42, Liverpool

Anxiety typically materialised as feelings of nervousness, vulnerability, distress and paranoia, which were perceived by qualitative participants to be severe and long-term emotional impacts. Anxiety/panic attacks were highest for those who had experienced/witnessed people being intimidated/harassed (23%), sexual ASB (22%) and nuisance neighbours (20%), but were also generally prevalent across other types.

Participants also felt anxiety after experiencing/witnessing aggressive begging (15%). Similarly, feelings of anxiety were also induced after experiencing or witnessing vandalism (10%). Qualitative participants highlighted how feelings of paranoia and of possibly being followed caused them to feel distressed.

‘I felt like I had anxiety, it was very distressing. When I walked back onto the road and I was walking really, really fast, trying to get into my car. I didn’t even go to the shop, I thought, “No, I’m not going to go into the shop, just in case [the man begging] is following me”.” Experienced ASB, female, 50, Leicester

‘It just made me anxious, and you know, like, I’m constantly looking out the window. You know? My wife even says, “What are you doing?” I say, “I’m just looking, I’m just looking”, and you know I’ll go outside and just make sure everything’s alright. So, I’m just paranoid constantly, do you know what I mean?’ Witnessed and experienced ASB, male, 45, Leicester

Several participants thought ASB had been a catalyst for their mental health worsening. One participant already had anxiety and explained how experiencing intimidation/harassment made him feel much more vulnerable and generally less resilient.

‘Just because I’m prone to anxiety, it ramped up the anxiety and then, maybe, made me feel less resilient in the coming months. You can’t measure these things, necessarily, there are no concrete links but as, somebody who is, sort of, sensitive to that kind of thing then it’s not a welcome factor in your life.’ Experienced ASB, male, 55, Westminster

Depression was often linked to fear/anxiety and loss of confidence as well. Participants reported that anxiety or fear of a potential experience of ASB caused people to lose confidence and stay inside more, which ultimately caused them to feel more depressed. As with anxiety, this was considered to be a deeper psychological impact that left a lasting impression on the quality of life of those it affected.

The types of ASB most likely to cause depression were some of the same types as those associated with the highest number of effects overall. Depression was a frequently reported impact of sexual ASB (27%), nuisance neighbours (19%), people being intimidated/harassed (18%) and out-of-control dogs (18%).

Those who felt depressed after experiencing or witnessing ASB described their emotional state as feeling discouraged, drained and dispirited.

‘I don’t want to go anywhere. I feel like I just want to stay in, while I’m constantly looking out the window. It makes me anxious. I just don’t want to do anything. I’d rather stay in. Even my mum comes up to see me twice a week. It does make me depressed, because I don’t go out, you know, very often anyway, but I just really feel like I don’t want to go out anymore.’ Experienced ASB, female, 56, Cardiff

3.2.4 Difficulty sleeping

Around one in five participants experienced difficulty sleeping (22%). This was a frequently reported impact of loud music/noise and nuisance neighbours, with 42% and 34% of those who had experienced/witnessed these types of ASB reporting this effect, respectively.

‘I lose sleep over it, basically. If I haven’t got into a proper sleep, you know, when they drop something, it can wake me up. And then, once I’m awake, I’m awake and I’m not going back to sleep for maybe an hour or two.’ – Experienced ASB, female, 41, Westminster

Lack of sleep can have an impact on one’s work or studies by causing a lack of productivity. Participants described how they did not function well at work after a bad night’s sleep. Further insight on the impact on employment and education can be found in sub-section 3.3.4 .

‘If I don’t get a good night’s sleep it’s not great. I could be functioning better at work, whatever I’m doing, so it does have that impact on my life there.’ Experienced ASB, female, 34, Westminster

3.2.5 Embarrassment/shame

Embarrassment or shame were less commonly experienced emotional impacts. However, these emotional impacts were relatively higher for those who encountered sexual ASB (28%), aggressive begging (16%), people being intimidated/harassed and drunken behaviour (both 14%).

Some qualitative participants felt a sense of shame or embarrassment about their neighbourhood or local area, rather than personally. They reported being ashamed to invite friends or family over in case they encountered ASB and not feeling proud of living in their local area.

3.2.6 Loneliness/isolation

One in ten people (10%) reported feeling loneliness/isolation after experiencing/witnessing ASB , making it one of the less common emotional impacts. It was most typically felt for those who witnessed/experienced sexual ASB (16%), nuisance neighbours (14%) and being intimidated/harassed (11%).

Despite this being a less common impact, qualitative participants who experienced this emotional impact highlighted that the effects were severe; they also described feeling as though they did not belong, in some cases leading them to want to leave the area.

‘ASB makes you feel unwelcome, like you’re not wanted or loved, you don’t feel you belong there. You’re left with so many questions in your head when you don’t know who is doing it or why – it does affect your emotional wellbeing. You don’t feel safe there all the time and you don’t know what is going to happen next. I’ve felt like this for the 3 years I’ve lived here, and I’ve been planning on leaving for the past year.’ Witnessed and experienced ASB, male, 46, Liverpool

This highlights how the impacts of ASB are interconnected. In this case, feeling unsafe led to avoidance behaviours, which caused feelings of loneliness and isolation. In turn, the community can become more insular, decreasing the level of local community cohesion. Community impacts of ASB are discussed further in sub-section 4.2 .

3.2.7 Other emotional impacts

Other emotional impacts on individuals included shock, which was experienced by 18% of those who had experienced or witnessed ASB in the past year. Shock was most likely felt for being intimidated/harassed (28%), sexual ASB (25%) and out-of-control dogs (21%). Shock was more often an initial reaction to the incident, which dissipated with time or repeat encounters with the ASB , as the incidents became more normalised for the victim. Given the short-lived nature of this impact, qualitative participants did not discuss it in detail.

Crying/tears was also reported by 9% of those who experienced/witnessed ASB in the last 12 months and was slightly more typical for participants who experienced or witnessed people being intimidated/harassed (15%), nuisance neighbours (13%) and out-of-control dogs (13%). The qualitative interviews highlighted how this materialised as a side effect of other emotional reactions such as shock, anxiety/panic attacks, fear and depression.

There were a small number of other emotional impacts that were not explored in the quantitative survey but were discussed qualitatively. One of those was a feeling of powerlessness or exhaustion. This tended to materialise when there was no resolution after ASB incidents had been reported and was also seen as a reason for not reporting incidents altogether. Participants expressed their helplessness after learning that nothing could be done about the ASB in their area. More often, the lack of resolution and response from the authorities to whom it had been reported could increase the feelings of powerlessness participants felt since they were dismayed with the lack of repercussions. Further information on this can be found in Section 6 .

3.2.8 Physical health problems

A small number of participants (8%) reported developing physical health problems due to the ASB they had experienced. Insights from the qualitative research with victims and agencies indicated that this was commonly tied to emotional impacts such as anxiety provoked by experiencing or witnessing ASB . Participants and frontline agencies/organisations highlighted that experiencing or witnessing ASB tended to have a triggering and cascading effect on some victims’ mental health and subsequently physical health. For example, stress-related issues could result in heart conditions or concerns.

Physical health problems were most likely to develop from sexual ASB (19%), nuisance neighbours (11%), people being intimidated/harassed and problems with out-of-control dogs (both 10%). Interviews with victims and agencies revealed physical health problems including a loss of sleep and heart issues as a result of increased levels of stress. As an example, one frontline stakeholder spoke of how ASB could increase stress levels and ultimately impact physical health.

‘I think mental health takes a huge hit… a lot of people are constantly victimised as a result of anti-social behaviour… then [that] has a negative impact on their wellbeing. Their mental wellbeing, and physical wellbeing, actually, I know one of the victims has suffered quite heavily with heart problems over stress.’ Stakeholder, local authority, Leicester

While less common, those who did experience physical health problems tended to do so for a longer period of time. This was particularly the case for people who were dealing with nuisance neighbours – with 65% of people who felt this impact saying that it had impacted them either for more than a few weeks or that it was still happening [footnote 28] . This was a similar case for people being intimidated/harassed (56%).

3.3 Behavioural impacts

3.3.1 overview of behavioural impacts.

Two-thirds (66%) of those who experienced or witnessed ASB in the past 12 months had changed their behaviour or experienced behavioural changes as a result of the incident(s). As demonstrated in Figure 3.6, the most prevalent behavioural impact was avoidance, with 51% of all participants stating that they had experienced at least one of the avoidance behaviours listed [footnote 29] . Qualitative research demonstrated that this tended to manifest in actions such as people avoiding specific neighbourhoods or areas late at night, taking the long way home, or taking taxis instead of walking.

Figure 3.6: Survey participants’ behavioural impacts from ASB , across all types of ASB

Taking actions to improve one’s safety following experiencing/witnessing ASB incidents was also a commonly reported impact. Nearly one in five (18%) stated that the ASB caused them to take extra security precautions such as installing alarms or investing in CCTV cameras.

Impacts on either work or studies were experienced by 17% of individuals who had experienced or witnessed ASB in the past 12 months. This was a total figure combined from several individual impacts, including being less productive (9%), needing to take time off (6%), losing or changing jobs (4%) or leaving the workforce altogether because of ASB (5%).

Across all elements of the research, it was apparent that the behavioural impacts were more prevalent in relation to certain types of ASB . The following sub-sections explore the range of behavioural impacts that survey and interview participants reported experiencing in relation to the different types of ASB .

3.3.2 Avoidance

The most common behavioural impact across types of ASB was avoidance. Just over half (51%) of survey participants reported avoidance behaviours as a result of ASB , which include avoiding certain places or situations (36%), going out less often (24%) and changing travel plans (17%).

Avoiding certain places or situations was the most common behavioural reaction across all types of ASB . It was highest in response to youths/teenagers/groups hanging around, with 37% expressing that experiencing/witnessing this type of ASB led to this behaviour. This was followed by drunken behaviour (35%), people being intimidated or harassed (34%), problems with out-of-control dogs (33%), people using/evidence of drugs (31%) and sexual ASB (29%). Around a quarter of those who experienced/witnessed aggressive begging and inconsiderate behaviour also expressed that they have since avoided places or situations (26% and 25%, respectively).

The interviews with victims/witnesses highlighted that this was often linked to the emotional impacts of feeling afraid, a lack of confidence, or anxiety (see sub-section 3.2 ). Many participants reported feeling fearful of facing the perpetrators or were worried that it would be dangerous or unsafe to be in close proximity to where an incident occurred.

It was also suggested that avoidance behaviours looked very similar regardless of which type of ASB was experienced or witnessed. Many victims reported avoiding certain areas of their town as they commuted home, or avoiding walking or exercising in certain areas (for example, particular parks, neighbourhoods or streets) where they felt incidents were likely to occur. Avoiding certain areas also involved changing travel plans, such as driving to avoid walking down a street where ASB had previously occurred. Many did not permit their children to play in certain areas or would not let them play unattended. This was rooted in fear and informed by their own experiences, experiences of those in their personal network or from their own perceptions of areas that were susceptible to being used for ASB .

Participants also noted the greater impact that ASB had on their social lives. Participants sometimes avoided socialising in their immediate communities and discussed how it felt like there was a reduced sense of community as a result. This highlights the interconnectedness between an individual’s own emotional responses, the behaviours and actions they take as a result, and the knock-on effects this can have on the community and wider area. Participants also thought that ASB in their communities was being perpetrated by people who recently moved to their area or people that they did not know, suggesting that those known in the community were less likely to be perpetrators.

‘When there were really, really big groups of them, I would actively avoid walking out of my cul-de-sac and down there. Even though that’s right outside my little, kind of, cul-de-sac, I never feel completely safe. So, I don’t tend to socialise in my immediate community.’ Witnessed ASB, female, 31, Newcastle upon Tyne

Going out less often was most relevant for those who had experienced or witnessed people being intimidated/harassed (27%), sexual ASB and problems with out-of-control dogs (both 24%), but was expressed across a range of ASB types, especially by those who typically encountered the ASB close to home.

Many victims either did not want to leave home due to depression or anxiety, or due to safety concerns. This was intensified when it was after dark, or if they had typically faced evidence of ASB upon leaving their homes, such as people using drugs or evidence of drugs.

‘I find in the evenings, I’m a bit reluctant to walk down, because there’s people taking drugs, there’s the laughing gases, the little pellets all on the floor. Beer cans. And even in the parks, it is quite bad. So, I think when it gets dark, I’m a bit reluctant to leave the house now.’ Witnessed and experienced ASB, male, Leicester, focus group

Changing travel plans was slightly less common but was still experienced by nearly one-fifth of participants surveyed (17%). It was seen across all types of ASB but was highest among the same 3 types as for going out less often (sexual ASB at 25%, problems with out-of-control dogs at 24% and people being intimidated/harassed at 22%).

Participants explained how ASB encounters caused them to exercise more caution than they previously would have. For instance, many took taxis home, drove instead of walking or did not travel alone. One qualitative participant who regularly encountered people using/evidence of drugs near her housing estate would make sure that she got dropped off directly outside her home to avoid coming into contact with this form of ASB .

‘I’ve got to make sure I get a cab back home because the cab’s going to drop me at my door.’ Experienced ASB, female, 41, Westminster

In another example, a participant feared going out on their own after experiencing ASB , especially where the event might occur again. As a result, they would change their travel plans to make sure they would not go by themselves.

‘Mentally it did affect me, because I don’t like going out on my own, especially to the post office and stuff.’ Experienced ASB, female, 50, Leicester

3.3.3 Taking extra security precautions

Another behaviour change carried out by 18% of participants was taking extra security precautions for their homes or routines. The proportion of participants who took these sorts of actions was highest for people who had personally experienced or witnessed sexual ASB (21%) and others being intimidated/harassed (16%). Further to this, 15% of those who experienced/witnessed youths/teenagers/groups hanging around, people using/evidence of drugs, nuisance neighbours or problems with out-of-control dogs took extra security precautions due to the incidents.

Qualitative interviews highlighted that, in practice, this involved taking precautions such as investing in CCTV or other security devices, installing alarms, as well as choosing to live somewhere with greater security measures (such as in a flat that had a porter on duty at all hours). Others made sure to leave lights or the television on to make it appear that they were home. The rationale for these actions was often to deter potential perpetrators or for personal safety.

‘So, I think I have to watch out for my own safety, and that’s why… I prefer living in a manned apartment. Like, 24/7 manned apartment with a porter, and I would not feel comfortable living, say, in a house on my own.’ Witnessed and experienced ASB, female, 52, Westminster

These behavioural impacts were the most likely to incur an immediate financial burden or effect on individuals, due to the investments they had to make to improve their personal or property security. Participants pointed out that these costs built up, posing a financial burden.

‘When I first moved here there had been car thefts in streets… that sort of encouraged us to spend money in getting a garage… We went and bought dog signs saying, “Warning of dogs.”… We had bikes stolen, so we’ve had to invest in sheds now to keep them in and invest in locks.’ Experienced ASB, male, 22, Newcastle upon Tyne

3.3.4 Impact on employment or education

Overall, 17% experienced an impact on their employment or education as a result of ASB . This was made up of a combination of different impacts, including being less productive (9%), taking time off (6%), leaving the workforce early (5%) and a loss/change of jobs (4%).

Being less productive when working or studying was related to difficulty sleeping and was a foreseeable impact from experiencing or witnessing nuisance neighbours (14% reporting this effect) and loud music/noise (11%). Several participants noted the disruption from nuisance neighbours specifically, explaining how it caused tiredness at work.

‘[It] affects me because she obviously makes me sleep deprived and then I’m just annoyed for the whole day and I’m up at 6 in the morning for work and stuff and then it stresses me out… I’m tired in work, I don’t want to go to work and stuff like that.’ Witnessed ASB, female, 24, Liverpool

The proportion of participants who took time off from their work or studies (6%) or lost employment or changed jobs (4%) as a result of ASB was much smaller compared to other behavioural impacts experienced. However, the impact was perceived to be substantial. Qualitative evidence demonstrated how working on streets where ASB was a regular occurrence was a motivator to change jobs. Aggressive begging was found to have a key impact on loss of employment or changing jobs, with 12% of those experiencing or witnessing it stating this had happened to them after.

‘When I was closing the store, I had quite a few people coming up to me asking for money… I had to have 2 associates with me when I close the store because I need security around me.’ Experienced ASB, female, 24, Liverpool

3.3.5 Moving home (within area or to a new area)

Around one in ten participants who had experienced ASB in the past year had moved home as a result of the ASB they experienced. This was made up of those moving to a new area (6%) and moving within the same area (5%).

Moving within the same area was a slightly more common impact as a result of sexual ASB (14%) and aggressive begging (8%) than for other types of ASB . This was similar to moving to a new area, where sexual ASB (17%), problems with out-of-control dogs (11%), aggressive begging, nuisance neighbours and environmental ASB (8% each) were the most common types to have this impact.

Some qualitative participants who had experienced nuisance neighbours considered moving house, although had not gone through with it yet. They tended to highlight practical reasons behind the delay in their move, such as owning their home or waiting for the availability of other housing association accommodations. Other participants referenced how they may be inclined to move if they were in different stages of life, notably that they would move when they got older to avoid the stresses of experiencing or witnessing ASB . To a lesser extent, matters of principle had stopped some from moving. These participants thought that they should not be pushed to the extent of leaving their homes.

‘As you get older, you know, your needs and objectives change and for me, yes, in the future that’s something that I would consider.’ Witnessed ASB, male, 36, Leicester

3.3.6 Longevity of individual behavioural and physical impacts [footnote 30]

The duration of the impacts from ASB was related to the frequency of the ASB experienced or witnessed. This was evidenced both quantitatively and qualitatively.

As mentioned in sub-section 2.2.3 , the types of ASB that were most likely to be experienced/witnessed at least on a weekly basis included nuisance neighbours (42% experiencing/witnessing this ASB at least once a week), environmental ASB (39%), people using/evidence of drugs (39%) and aggressive begging (38%). These types of ASB all had long-lasting impacts (especially for avoidance behaviours) where a high proportion of those experiencing these types of ASB was still avoiding certain places or social situations. For example, 47% of those experiencing or witnessing nuisance neighbours, 42% of those experiencing or witnessing people using/evidence of drugs and aggressive begging, and 36% of those experiencing or witnessing environmental ASB were still avoiding places or social situations.

Avoidance (avoiding certain places or situations), going out less often, changing travel plans and taking extra security precautions were the behaviours that tended to remain the longest and were the most common overall.

Avoiding certain places or situations had a long-lasting behavioural impact on inconsiderate behaviour (with four out of five (80%) reporting avoiding certain places for more than a few weeks or that they are still doing it following the incident), as well as people being intimidated/harassed (78%) and problems with out-of-control dogs (77%).

Going out less often was also a behaviour that lasted for longer than a few weeks or was still ongoing for about three quarters (76%) of those who experienced/witnessed inconsiderate behaviour, as well as drunken behaviour (74%) and people being intimidated/harassed (72%).

The duration of the impacts seemed to have a connection with the length of the reporting process (if pursued with agencies or organisations). Often, this process was extremely lengthy, requiring individuals to relive their experiences, which took a considerable amount of time and energy. More information on this can be found in Section 6 .

3.4 No individual impacts

Only 6% of survey respondents said that ASB had no impact on their quality of life. Furthermore, only 7% stated that they felt no emotional impacts. However, a larger group, one third (33%) reported no behavioural impacts as a result of the ASB incident(s).

The same factors that affected the severity of impacts also played a role in whether the individual experienced impacts from the ASB at all. Factors included whether the individual experienced or witnessed ASB , as well as the frequency at which they witnessed or experienced it. For instance, one participant explained that since he only witnessed the ASB , and as it did not affect him directly, it did not have an impact on him.

‘Not really. The case where the person spat on my colleague, that obviously got [me] a bit angry as you rightly would, someone doing that, but apart from that, it’s just day to day really. Isn’t it? The couple that were being abused, I mean that wasn’t nice to see but I don’t think it affected me mentally or physically or anything like that. No is the honest answer. Nothing really affected me.’ Witnessed ASB, male, 38, Westminster

Often, when participants claimed that the ASB had no impact on them, they perceived themselves to simply be less vulnerable to the impacts of ASB than others in different circumstances might be. They, therefore, did not believe it had any noticeable effect on them. Similarly, other participants tended to normalise the ASB , noting that it is ‘just something that happens’ or rationalising that they used to participate in similar activities when they were younger.

‘I didn’t particularly consider myself vulnerable. I’m also from quite a working-class background. When I was a teenager, I too drank in fields. I’m from a similar background, so I’ve never really felt massively intimidated.’ Witnessed ASB, female, 31, Newcastle upon Tyne

Some individuals did not even realise that ASB had impacted them until discussing it at length in the interview when participating in this research, suggesting that the impact was minor. As such, they had not sought or received support.

4. Wider impacts beyond the individual

This Section explores the impacts of ASB that go beyond the individuals who have experienced or witnessed it, including their personal networks, their communities and more broadly their perceptions of institutions.

• ASB caused both emotional and behavioural impacts on victims’ personal networks. These impacts were broadly in line with those seen on an individual level. Family and friends of victims felt worried, anxious and fearful. Behavioural impacts were commonly reported as avoiding certain areas and changing plans.
• At a community level, ASB was most commonly found to weaken the sense of community through making people anxious to interact. However, in some cases, ASB also brought communities together by giving them something to rally around.
• ASB also had wider impacts. Participants highlighted a loss of trust in institutions such as the police and local authorities, a sense of decline in the reputation of their area and feeling a negative impact on notions of morality and society.
• The impacts from ASB were highly intertwined across individual emotional and behavioural effects as well as personal networks and community-wide dimensions. Often, one impact served as a catalyst to others and created a knock-on effect.

4.1 Impacts of ASB on personal networks

4.1.1 overview of impacts on personal networks.

The impacts of ASB extend beyond the individual who personally experienced or witnessed the incident, also impacting their personal network, including their families, friends and neighbours. The emotional responses felt by family and friends were similar to those felt by the individual themselves.

From a behavioural perspective, avoidance was also reported. In the qualitative research, many participants described how friends and family members did not want to visit their homes or neighbourhoods where they may encounter ASB , or often chose alternative travel routes or methods to avoid feeling unsafe. These impacts, as related to different types of ASB , will be explored in the following sub-sections.

4.1.2 Emotional impacts on personal networks

In terms of emotional impacts on the individuals’ networks, many participants detailed how they were worried their loved ones would be affected.

Qualitative interviews found that a victim’s family and friends tended to experience worry and anxiety about the victim’s wellbeing due to the ongoing nature of ASB . Family members and friends more commonly expressed worry or anxiety about those who were vulnerable, such as older relations or those who had physical health problems. For example, one participant worried about her elderly parents’ safety due to a high number of youths/teenagers/groups hanging around and people doing drugs in the park that they walk in.

‘My Mum’s in a wheelchair at the moment, and Dad would often push Mum… but I’m not happy with it. I’ve heard of elderly people getting quite a lot of abuse. I really worry about my Mum and Dad who are in their late 70s. I don’t want people calling them names.’ Witnessed ASB, female, 42, Newcastle upon Tyne

Some qualitative participants felt fearful for their relations or friends, as well as themselves. This was commonly experienced when they had experienced or witnessed an ASB incident in the area their relation or friend lived in, making them fearful to spend time in the area.

4.1.3 Behavioural impacts on personal networks

Some relatives and friends of victims exhibited avoidance behaviours due to the risk of heightened ASB in the area.

Victims were more cautious about inviting friends or family over to their homes because of the risk of their personal networks experiencing or witnessing ASB . Moreover, participants thought this was mirrored by networks’ themselves, with some suggesting that friends and family did not want to come to their homes or neighbourhood. Instead, friends and family would avoid the area completely so as not to be put at risk of encountering ASB . Similarly, others said that family members, friends or colleagues were more cautious when visiting, choosing to change travel plans to take the journey during daylight hours or opting to take a taxi instead of public transport or walking.

‘So, even my Mum gets wary of coming up to my house sometimes. My other family hardly come up because they know how rough the street is.’ Witnessed and experienced ASB, female, 26, Newcastle

It had a particular impact on elderly relatives or friends visiting, who were also perceived by participants to have a lesser willingness or ability to deal with the impacts. These personal networks would rather avoid visiting than encounter the ASB .

‘My grandparents just stopped coming here years ago because he [a neighbour] said quite horrible things to my grandparents after they parked outside our property… But he unfortunately went for my grandad physically. And my nan was in the car at the time, and they never bothered to come to this area after that.’ Experienced ASB, female, 24, Cardiff

Younger generations and children were also affected. The fear held by some parents or carers was translated into avoidance impacts on children. For example, some children were stopped from playing outside or in designated play areas due to parents’ concerns about the risk of encountering ASB .

In extreme cases, physical assault on friends/family members occurred when trying to confront or stop incidents of ASB from happening. For example, a case was highlighted where a participant’s son tried to challenge 3 youths/teenagers who were behaving anti-socially towards him and they responded by causing him severe physical harm.

‘To touch on the point of do you challenge these teenagers? Well, in my own experiences – don’t because, I’d say, just over 12 months ago, my son, who was 22 at the time, was provoked by three 11-year-olds. And he said something to them, and their response was to turn around and stick a knife in him.’ Experienced ASB, female, 66, Cardiff

The survey also highlighted that ASB could result in victims or witnesses arguing with family members or friends. This was experienced by one in ten of those who experienced or witnessed ASB in the past year. Although this was a less common impact, it was slightly more prevalent for sexual ASB (with 18% who experienced this type of ASB reporting this impact) and nuisance neighbours (with 13%). Qualitative interviews highlighted that lack of sleep resulting from nuisance neighbours tended to be a major trigger for this behavioural impact.

‘I live with my partner so, yes, we did have a couple of rows because I was, like, tired and I was being aggressive because I just needed my sleep and I’m terrible if I don’t get my sleep, I can’t function.’ Witnessed ASB, female, 57, Newcastle upon Tyne

4.2 Impacts of ASB on communities

4.2.1 overview of impacts on the community.

Many of the impacts of ASB on individuals build up over time. Where impacts were felt by multiple individuals, it contributed to a reduction in the feeling of community.

Participants were asked to think about how ASB impacted their local area. In the quantitative survey, ‘local area’ was described as being within 15 minutes’ walking distance from where they lived. Qualitatively, this was left open to interpretation, but participants tended to focus on the area within walking distance of their homes.

More than a quarter of survey participants (27%) stated that ASB caused a decline in their levels of trust in others/their community. Qualitative interviews also reflected this. Participants perceived their communities to lack cohesion and suggested that the reputation of their local area had declined due to ASB .

In contrast, others thought their community had been brought together due to ASB incidents, with many examples given of how individuals in a community had come together to combat ASB . As demonstrated in the qualitative victim interviews, this community cohesion was perceived as sharing a common goal (such as stopping the ASB ), keeping each other safe and communicating with one another about what was happening in the community.

The idea of ASB and crime in the local area becoming normalised was discussed. Both agencies/organisations and victims observed a self-perpetuating cycle where observers of an incident believed it to be accepted, and therefore observers were more likely to replicate the behaviours.

4.2.2 Negative community impacts

For some victims, ASB had immediate emotional implications related to their community, such as annoyance and anger [footnote 31] towards others in their community. More than half of the participants (58%) felt either of these emotions extremely or very strongly across ASB types. This was felt more strongly for those witnessing or experiencing nuisance neighbours (79%) and loud music/noise (74%).

The quantitative research found that a quarter (27%) of those who experienced/witnessed ASB reported that it made them feel a loss of trust in others/in the community. This was most commonly felt by participants who experienced or witnessed being intimidated/harassed, problems with out-of-control dogs and sexual ASB , each at 29%. Environmental ASB and nuisance neighbours also contributed to these feelings, both at 28%.

Qualitative participants reinforced how ASB resulted in a loss of trust in the community, describing how they perceived ASB as a cause of community breakdown. This was described in various ways by participants. Several discussed the decline of community engagement due to the presence of ASB . For instance, some said that the community stopped behaving like a community because people did not leave their homes as much and thus did not communicate with their neighbours.

‘I think it stops people behaving like a community. I think people retreat to their own house a lot, there isn’t an awful lot of community feel. People don’t want to be out when there’s fireworks going off, people don’t want be out when they’re in danger of bumping into crowds of people.’ Witnessed ASB, female, 59, Cardiff

Agencies and organisations described fear as being the main factor for the lack of communication and community breakdown for some participants. They reported that victims were afraid to engage with others in their community to discuss ASB as they were fearful that this might get back to the perpetrators and result in repercussions.

‘The community’s more scared. People won’t go out. People will not report things because they’re too frightened to and it’ll get worse and worse.’ Stakeholder, local authority, Cardiff

Most qualitative participants desired a community with a friendly and engaging environment but were not sure that it could exist in their own community. Feelings were that other people did not interact or integrate as a result of ASB . In some cases, fear and mistrust of others also disrupted community cohesion.

Fear of repercussions from confronting or reporting ASB also led to social apathy , which was also perceived to hinder community cohesion. Qualitative participants discussed how others in the community seemed apathetic towards the ASB that was going on in their community, with no one willing to do something about it.

‘People go about their business, they don’t say hello to people, they put their heads down, they go home, lock their doors and that, they don’t integrate like they used to, and I think it’s become like that as well with people think, “Oh, it’s not my problem, let somebody else report it”.’ Witnessed ASB, female, Liverpool, focus group

Related to social apathy , there was a tendency for members of the community to normalise ASB . This was often related to feelings of hopelessness, whereby participants felt as though nothing would be done to improve ASB in their community, so they felt they had to accept it. Some described the normalisation as a reinforcement cycle in that when individuals saw others commit acts of ASB and get away with it, they assumed they could too. Others described the normalisation as complacency among communities whereby people stopped caring and therefore perpetrators of ASB took advantage.

‘If people see people committing those anti-social acts, then they can normalise it. They think, “I can do that, so I’m going to do that on my street, maybe I can copy that” and it quickly progresses to other areas.’ Witnessed ASB, male, 29, Westminster

One stakeholder mentioned the concept of the ‘Broken Window Theory’ [footnote 32] in relation to this tendency for communities to normalise ASB . Broken Window Theory was an academic concept devised in 1982 that proposed broken windows as a metaphor for disorder in communities. The theory suggests that disorder and incivility within a community are likely to lead to further disorder and incivility, as it becomes normalised and deemed socially acceptable behaviour.

‘I think it’s the ‘Broken Window effect’. I think that has come into it. It’s been recognised in research papers in the past. But, yes, it’s possibly living with it, accepting the behaviour, they’ve become acclimatised to it.’ Stakeholder, police, Cardiff

As described above, the normalisation of ASB can send communities into a negative cycle of not reporting it, and becoming increasingly indifferent.

4.2.3 Positive community impacts

The qualitative research also demonstrated that ASB could have a positive impact on some communities in that it can bring people together. Multiple participants noted these positive effects in relation to people coming together either to try to stop the ASB in their community, share information and look out for one another’s safety, or to commiserate and support each other.

There were several examples regarding coming together to stop ASB . For instance, one community came together to file a collective complaint about a local shop that was selling alcohol to underage children, with one neighbour leading the group.

‘She’s the one that goes round and, like, keeps abreast of all the information and tells us what’s happening so that we can take the appropriate steps. I think without that one woman, kind of, leading the charge, we’d be in a much more reactive position with all that kind of stuff and we’d probably be victim a lot more to anti-social behaviour.’ Witnessed ASB, female, 31, Newcastle

For sharing information or keeping one another safe, participants mentioned using the ‘NextDoor’ Neighbour app, which allows people in a local area to announce if there is any ASB occurring. Others mentioned discussing ASB and sympathising with neighbours via Facebook groups.

4.3 Wider impacts of ASB

Wider impacts, including impacts beyond the immediate community, were also found. The main impacts highlighted were loss of trust in institutions, reputational decline and a decline in morality within the area.

Over a quarter (27%) of survey participants reported feeling a loss of trust in institutions due to the incident(s) they experienced/witnessed. This was highest in relation to more systemic issues such as people using/evidence of drugs (29%), sexual ASB (22%) and aggressive begging (21%), as well as more confrontational situations such as nuisance neighbours (25%) and people being intimidated/harassed (23%). Qualitative participants suggested that societal institutions could have done more to prevent ASB caused by systemic issues occurring. Moreover, they thought that institutions could have done more in the reporting and resolution process to combat their negative experiences of confrontational situations. Furthermore, loss of trust in institutions was the most severely felt emotional reaction for those who experienced/witnessed vandalism (76%), environmental ASB (76%) and youths/teenagers/groups hanging around (69%).

Qualitative participants highlighted that this was also intensified in cases where a lack of action from the authorities resulted in even less trust. In other words, a negative response to reporting ASB could worsen impacts and reduce the trust in institutions. These effects are briefly described below and further elaborated on in Section 6 .

People’s trust in the police was diminished by incidents such as police failing to arrive when called or arriving too late so that the perpetrator had already fled. Additionally, there was a perception among many participants that the police were not interested in ASB or that they were preoccupied with alternative duties.

‘My faith in police isn’t very good. I’ve only ever used them for anti-social behaviour stuff. I had an incident with one of our properties recently, they were growing cannabis in the property, so I rang the police about it and they didn’t even come out and check it.’ Witnessed ASB, male, 62, Cardiff

Across ASB types, participants also reported a loss of trust in the local authority due to a lack of proactive action on ASB issues.

‘Yes, it probably has given me, you know, less of trust with the council just because of, again, you know, my experiences with the nuisance neighbours, and okay, yes, I’ve not reported the street drinking etc., but yes. I’m thinking if it still continues then something’s not really done about it.’ Witnessed ASB, male, 36, Leicester

Others reported that their area had suffered from reputational decline, explaining that ASB had caused communities to ‘go downhill’. Qualitative participants described their local area as having a bad reputation. In some cases, they avoided telling others where they lived to avoid judgement .

‘I think socially as well, when you tell someone where you live, they’re a little bit, like, “Oh, really?” People don’t really like the area or have high hopes for the area anyway, socially.’ Witnessed ASB, female, 27, Leicester

Furthermore, the reputation of an area impacts housing prices. Some participants felt that the ASB in their area had contributed to house prices falling.

Lastly, some participants reflected on the effect that ASB had on overall morality and social development, noting that the presence of ASB in an area sets a bad example for children. Specifically, one participant who worked with children, said that from her experience, ASB solidified a lack of social awareness among youth.

‘Unless the changes [are] made, you can read as much as you like about being a good person, but actions speak louder than words, and people are getting away with things because they’re a bully, or because they’re being anti-social and they don’t think the rules apply to them.’ Witnessed ASB, female, 42, Newcastle upon Tyne

4.4 The interconnectedness of ASB impacts

The impacts of ASB on individuals, their personal networks or communities, and wider areas were not seen to be mutually exclusive. Individual emotional impacts tended to have knock-on effects on behavioural impacts, impacts on friends, families, or communities/the wider area, as well as contributing to the wider impacts of ASB . Themes derived from victim interviews have been used to illustrate this interconnectedness. These are not intended to be an illustration of the exact knock-on pattern each impact will have but act as examples of the chain of impacts that participants have experienced.

Figure 4.1 demonstrates how fear and loss of confidence from ASB could result in people avoiding places or situations more over time, causing a perceived degradation in community cohesion since there is less community interaction. Ultimately, this was perceived to lead to reputational decline and the area being known as a place that does not have a strong sense of community.

Figure 4.1: Example one of the interconnectedness of ASB impacts

In another example (Figure 4.2), difficulty sleeping (due to noise-related ASB ) was said to result in arguments with family or compel people to move homes away from the community, leading to a high number of residents leaving. Eventually, with enough people leaving the area, this was perceived to lead to a drop in property prices.

Figure 4.2: Example 2 of the interconnectedness of ASB impacts

Lastly, as shown in Figure 4.3, ASB could cause a decline in levels of trust in others and foster an environment of mistrust where people go out less often and engage in their communities less. This lack of trust could translate into social apathy – caring less about others and assuming that ASB is ‘just something that happens’ in the area. This normalisation of ASB was ultimately perceived to lead to what some participants described as moral decline, meaning a lesser overall sense of morality in the area.

Figure 4.3: Example 3 of the interconnectedness of ASB impacts

This demonstrates that impacts were not likely to happen in isolation. Instead, they were highly intertwined across individual emotional and behavioural effects as well as interpersonal, network and community-wide dimensions. Often one impact served as a catalyst for others and created a knock-on effect. Thus, ASB interventions targeted at an individual level will also likely be effective in easing community and wider area impacts, and vice versa. This should be considered when trying to understand and measure the effectiveness of future interventions.

5. Personal factors influencing ASB impacts

Personal, situational and demographic factors had a role in determining which impacts were felt more severely and by whom. These included age, gender, region/geographic area, income level/deprivation, pre-existing mental or physical health conditions as well as being pregnant/having children. Understanding which groups experience a more substantial impact allows interventions to be more effectively targeted. This Section explores how each of these factors influences the impact felt by victims/witnesses of ASB as well as highlighting where this may be driven by the types of ASB experienced.

• Demographics were a key factor in the scale of impacts experienced by the individual. Based on the national survey, those that were more likely to experience a significant negative impact from ASB included younger people (those aged 18 to 34), men, those living in London or Wales, people from white ethnic backgrounds, people with higher incomes and those who lived in more deprived areas.
• Personal and circumstantial factors also played a role in the severity of ASB impacts. Those who had pre-existing mental or physical health conditions, those who were pregnant and those who had children all experienced greater ASB impacts.
• There was a perception among many qualitative participants that the elderly faced more severe consequences of ASB . However, survey data demonstrated that younger people (those aged 18 to 34) were more likely to feel a significant negative impact from ASB compared with other age groups overall. This was likely driven by the types of ASB they more commonly experienced (aggressive begging and sexual ASB ).
• A paradox was observed in more deprived areas. While ASB tended to be more prevalent, fewer incidents were reported to the relevant agencies and organisations. More affluent communities were perceived to be less tolerant of ASB , whereas more deprived communities tended to accept a higher level of ASB .

There was a perception among many qualitative participants that the elderly faced more severe consequences of ASB . However, survey data demonstrated that younger people (those aged 18 to 34) were more likely to feel a significant negative impact from ASB compared with other age groups overall. Nearly 3 in 10 (29%) participants in this age group reported feeling a significant negative impact on their quality of life from ASB , whereas 22% of those aged 35 to 54 and 10% of those who were aged 55 and over indicated the same.

The younger age group (those aged 18 to 34) were significantly more likely to encounter aggressive begging (25% compared with 21% overall) and sexual ASB (15% compared with 9% overall). As sexual ASB has some of the greatest impacts overall, this type of ASB being more likely to be experienced by a younger age group could offer some explanation as to why the younger age group experienced more significant negative impacts.

Despite these results from the quantitative survey, qualitative interviews with victims showed that there were still perceptions of a heightened effect of ASB on the elderly. This perception both came from elderly people themselves as well as family members. One participant described how ASB impacted him more as he got older.

‘Well, it is fear, it is fear. When you get in your 70s, it doesn’t matter how fit you think you are, you’re no match for, you know, a budding 15-year-old, even, who thinks he’s a Mike Tyson or somebody. You might think you can handle that but trust me.’ Witnessed and experienced ASB, male, 70, Leicester

This could be related to the perception of older people being more vulnerable, perhaps due to physical or mental health reasons. Participants noted that they thought this made them a particular target for all types of ASB .

‘I would say in terms of most affected probably, sort of, from an age point of view, I’ll guess 40, 45 and above. I think more so towards the elderly. I think, you know, those that are more vulnerable I guess partly are more likely to be targeted.’ – Witnessed ASB, male, 36, Leicester

In terms of gender, men (25%) were significantly more likely to report significant impacts from ASB compared to women (15%) [footnote 33] . This can be somewhat explained by the types of ASB they experience. Men were more likely than women to experience and witness people being intimidated/harassed [footnote 34] and were also more likely to encounter problems with out-of-control dogs [footnote 35] . These types of ASB had some of the greatest impacts on quality of life overall.

5.3 Ethnicity

People from white ethnic backgrounds were generally more likely compared to the total (at 21% [footnote 36] ) to report a significant impact from ASB than other ethnic groups. However, this comparison should be treated with caution as base sizes among other ethnic groups are low.

While people from white ethnic backgrounds reported the most impact from ASB , other ethnic groups reported having experienced or witnessed more types of ASB . For instance, people from black ethnic backgrounds had experienced or witnessed a significantly higher number of different types of ASB (an average of 4.8 types of ASB per person) than people from white ethnic backgrounds (an average of 3.7 types of ASB per person). People from black ethnic backgrounds were also more likely to have experienced or witnessed loud music/noise (44% compared with 31% overall), aggressive begging (41% compared with 21% overall), problems with out-of-control dogs (29% compared with 14% overall) and sexual ASB (22% compared with 9% overall).

There was a perception from participants who were from black, Asian or minority ethnic backgrounds that they were more likely to be targets of ASB (as well as being targeted for crimes such as racism and hate crimes which were perceived to have similarities with ASB ). This could offer an explanation as to why those from black ethnic backgrounds experienced more types of ASB . Due to sample limitations, there was limited data from both the quantitative and qualitative research on how other ethnic groups may have been impacted by ASB .

‘People always pick an easy target, don’t they, someone who’s a bit different, someone who wouldn’t fight back, so the types of people we tend to deal with persistent ASB are vulnerable people, it might be people with mental health problems, might be people with different ethnic backgrounds to the norm in the area. And that obviously overlaps massively with hate crime.’ Stakeholder, police, Liverpool

5.4 Region/geographic area

The survey demonstrated that a range of regional/geographic characteristics influenced the level of impact experienced as a result of ASB . Participants from London and Wales were statistically more likely to experience substantial impacts on their quality of life than those in other regions.

London residents experienced greater ASB impacts than those living in other regions across England. Of survey respondents who lived in London, 29% felt a significant impact on their quality of life from ASB (compared with 21% overall). Qualitative interviews suggested that this could be a result of higher population density, with closer proximity to neighbours, making incidents of ASB more difficult to avoid.

The survey showed that those living in Wales were also more likely than average to experience a significant impact on quality of life, with 32% of those who experienced or witnessed ASB in the past year stating that it had a significant effect. Qualitative participants suggested that reduced transport links and a lack of support services in Wales’ rural areas could play a role.

5.5 Level of income/deprivation

As highlighted in sub-section 2.2.1 of this report, the level of deprivation or income in a specific area appeared to influence the degree to which ASB was prevalent there. Those residing in the most deprived areas (based on IMD ) [footnote 37] were more likely to have personally experienced or witnessed ASB in the last 12 months according to the survey results. People in these same areas were also more likely to have experienced a significant impact from ASB on their quality of life compared to those who lived in the least deprived areas [footnote 38] – with 23% experiencing a significant impact in both IMD areas 1 and 2 compared with 16% in IMD area 5. Several agencies and organisations offered various explanations for this. Some mentioned that deprived areas tended to have a lot more issues within the community that triggered ASB , usually emerging from particular properties.

‘We do get quite a lot of community impact-based issues, especially, I would say, mainly around a specific property, so if we’ve got a property that there are high levels of anti-social behaviour and crime, then we can see that community-wide impact.”’ Stakeholder, local authority, Leicester

Other agencies and organisations pointed to the lack of financial or time resources that individuals had to leave the area. Organisations within these areas were also perceived to have fewer resources to fight the ASB . Those in more affluent communities were perceived to have more readily accessible resources.

‘But in less affluent areas I think that some, not all the time, it’s not like a standard but I think sometimes they haven’t got an out. They can’t necessarily easily move, if they can’t necessarily get anywhere, they haven’t necessarily got the family support and I think that does make a big difference.’ Stakeholder, local authority, Leicester

Agencies and organisations discussed a paradox that exists in more deprived areas; while ASB tends to be more prevalent, fewer incidents are reported to the relevant agencies and organisations. There was a perception from qualitative participants that more affluent communities were less tolerant of ASB , whereas more deprived communities tended to accept a higher level of ASB . This also translated into reporting to the police or other organisations, with the degree of affluence or deprivation in a neighbourhood or community influencing whether the ASB was likely to be reported or not. Qualitative participants also observed a tendency for wealthier areas to report less severe incidents of ASB , compared with more deprived areas where much more severe ASB is tolerated. Therefore, when conducting future evaluation work, it should be considered that instances of ASB in more deprived areas may be underreported, which should be recognised when interpreting findings.

‘I think that in some parts of the city, we’ll get persistent complaints about parking, for example, and it will be a massive issue to them in their £1 million houses. Then in other parts of the city that are completely the opposite way, we’ll know that there are drug dealers operating out of a flat but nobody’s coming forward. So, people who are financially disadvantaged don’t come forward as often as those that aren’t.’ Stakeholder, local authority, Leicester

‘Posher estates tolerate less anti-social behaviour so you probably see crime will be far lower and things like that. Because if even something so small, like, if I park outside someone’s house, they might ring some sort of police or council and then my car gets a fine, so you instantly know not to do that again.’ Witnessed and experienced ASB, male, 24, Newcastle upon Tyne

5.6 Physical/mental health conditions

Those with a pre-existing physical or mental health condition were significantly more likely to experience a significant impact from ASB compared with overall (24% compared with 21% overall). Additionally, those who said that this condition causes them to have a reduced ability to conduct their daily lives were significantly more likely to have experienced a significant impact from ASB on their quality of life (26% of those who had a condition that reduced their ability compared to 21% overall). These existing vulnerabilities appeared to increase these individuals’ risk of experiencing more severe ASB impacts.

‘We have a lot of people that start as low risk but soon become high risk because of their vulnerabilities, because of their mental health because everything is impacted by that and such behaviour.’ Stakeholder, local authority, Leicester

Qualitative participants with mental health conditions said that ASB could act as a trigger for the escalation of their mental health conditions. This was further intensified when physical health conditions were also present. For example, physical health conditions that made participants less mobile reduced their ability to respond to ASB happening around their homes. This included reducing their ability to report ASB to relevant agencies while it is occurring, taking part in monitoring and investigation, and in some instances trying to stop incidents while they were occurring.

5.7 Pregnancy/children

Having children or being pregnant tended to make participants feel more vulnerable to ASB impacts, both individually and for their children. One participant who was pregnant described her experience with being intimidated/harassed while pregnant as having a negative impact on her privacy.

‘I was pregnant around the time as well, so I just felt like it was very intrusive. I felt, like I said, not just from the gentleman actually verbally assaulting me but just someone going through my garbage and just, I don’t know, I just felt it was a very intrusive situation to be in.’ Experienced ASB, female, 37, Westminster

6. The impact of the response to reporting ASB

This Section explores the role of reporting experiences on the impacts of ASB , outlining the negative impacts that can emerge when a reporting experience does not happen as expected. It also highlights how the negative impacts of ASB could be reduced by experiencing a positive reporting process

• Whether an individual reported an incident (and had an outcome) and whether they received support (and their satisfaction with it) influenced the degree of impacts felt. A poor experience or outcome from reporting or accessing support services increased negative impacts, whereas a positive experience or outcome helped to ease the impacts of the ASB .
• Victims highlighted increased fear of repercussions from the perpetrator, feeling annoyance and hopelessness, a loss of trust in reporting agencies, the additional burden of monitoring and continuation of their avoidance behaviours as having a negative impact.
• Agencies and victims interviewed also highlighted several ways in which the reporting process and support can help reduce the negative impacts of ASB . This includes timely responses and communication to make sure people feel listened to, options for anonymous reporting, support being delivered in different mediums, involving the community in the resolution process, and a more connected support system.

Among other factors, the impact of ASB influenced the likelihood of victims reporting an incident or accessing support. However, the experience and outcome of reporting and receiving support also played a role in the impact that ASB had on victims. In this context, ‘support’ includes communication and engagement from a formal support avenue, between reporting an incident to its resolution. This includes any reporting agency (for example, the local authority, police or housing provider). Emotional support and advice may also be provided to the individual by other teams within the reporting agency, or by external organisations. For example, the ASB or neighbourhood team within a local authority may provide communication and updates on an individual’s case but could also refer the individual to internal or external victim support, mental health or counselling services.

6.1 Role of the reporting experience on the impact of ASB

The severity of the ASB experienced was a common factor in reporting – those who experienced ASB types with the biggest impacts on quality of life more commonly reported it. However, qualitative interviews demonstrated that the experience of the reporting process itself also played a role in lessening or increasing the impact ASB had on those who experienced or witnessed it.

Qualitative interviews highlighted that a prominent negative impact relating to reporting ASB was an increased fear of repercussions from the perpetrator. Those who had reported ASB were worried about potential repercussions following reporting, should the perpetrators find out. Some reported intensified emotional impacts as a result of this, such as anxiety. Not being able to report ASB anonymously in many instances contributed to this fear and was a frequently mentioned barrier to reporting.

Additionally, if a report of ASB was not perceived to have been handled well, this could also increase the negative impacts of the ASB itself. These impacts are discussed in the following sub-sections.

6.1.1 Annoyance and hopelessness

Negative experiences of reporting such as a lack of, or slow, response, and a perceived lack of support offered, left some participants feeling annoyed and frustrated that nothing was being done about their situation. This was especially the case when repeated ASB had been reported on more than one occasion. These participants reflected on their experiences of reporting as being a waste of their own time. This had, in turn, discouraged further reporting. Where there was a negative outcome in their report, participants had similar feelings.

Participants also described frustration at being referred between agencies and that this left them feeling unsure about whom to turn to for support.

‘And when you get anti-social behaviour, you tend to think, “Right, I’m going to report it to the police”, you ring the police, the police then tell you, “It’s not our problem, you’ve got to contact the council.” You ring the council and they turn round and say, “Well it’s a police matter, nothing to do with us.” So we’re left in between, thinking, “Where do we turn to?”… it does leave us with a feeling of being dumped to one side.’ Experienced ASB, Leicester, focus group

6.1.2 Loss of trust in reporting agencies

A negative reporting experience also contributed to a lack or loss of trust in local agencies. Frustration and a lack of faith in the police and council in particular were cited by participants who were unhappy with the response to their report of ASB . While this was often directed at the reporting agency as a whole (for example, the police), some participants were more nuanced in their views. For example, it was acknowledged that ASB may not always be a police matter and one participant said they had lost faith in the police in handling neighbourhood matters, although not crime more generally.

‘… disappointment in the police for not carrying this through because I know there has been numerous reports on them… It’s been happening for years, and the police have never done anything.’ Witnessed ASB, female, 37, Cardiff

6.1.3 Additional burden of monitoring

The requirements of the person reporting ASB were said to be burdensome and were perceived by some to have a detrimental effect on the individual. For example, keeping diaries and using noise-monitoring equipment for a period of 3 months was mentioned by a number of participants as being challenging and time-consuming.

‘You kind of feel like it is consuming you. When you think, I’ve got a life outside of this. I’ve got other things I need to do. I haven’t got time just to, “What time is it, two o’clock or three o’clock in a morning.” to get up get a pen, get a paper and write everything down.’ Experienced ASB, female, 57, Newcastle upon Tyne

6.1.4 Continuation of avoidance behaviours

More than a third (36%) of survey participants who had experienced/witnessed ASB had avoided certain places as a result. In some cases, participants said that reporting ASB that had not, in their view, resulted in a successful outcome had meant they had to continue with these avoidance behaviours (for example, avoiding a particular park).

6.2 Reducing negative impacts through reporting and support processes

This sub-section explores what ‘good’ support looks like and considers how a positive experience of reporting or support could reduce the impacts experienced. It considers input from agencies and organisations interviewed for this research as well as participants from qualitative interviews who reported positive experiences of the reporting process. Participants were prompted to discuss methods of improving the reporting and support process.

6.2.1 Timely response and communication to make sure victims feel listened to

Participants who had reported ASB stated that they wanted to feel listened to and that effective communication about the case would offer some reassurance that it was being taken seriously and something would be done. Those who had positive experiences of reporting and accessing support described feeling listened to by the relevant agencies, which in some cases reduced emotional impacts such as feeling anxious.

‘I was heavily pregnant, and I had… that brute actually verbally attacking me and assaulting me. So, after that I was quite emotional… maybe after I reported it, maybe then somebody calls afterwards just to check in and make sure, “Actually, are you okay?”’ Experienced ASB, female, 37, Westminster

6.2.2 Option of anonymous reporting

Fear of repercussions was a key concern for people reporting ASB and had deterred some from reporting it. Some described wanting to report ASB but not wanting to give their personal details, and many said that allowing anonymous reporting would be a key improvement to the reporting process. Participants came up with some ideas around how this could be done, for example through an anonymous reporting app. Having the option to report in this way could reduce emotional impacts such as feeling fearful.

‘Just reporting it anonymously on the phone. For people to take it seriously whether you go to the council or whether you go to the police. An organisation that I can go to for help or report something… and just say to them, “Look this has happened to me.”’ Experienced ASB, female, 50, Leicester

6.2.3 Delivered through an appropriate medium for the individual

Linked to the above, many participants favoured the phone as the preferred medium for support to be delivered to make sure they had full anonymity from the perpetrator (or via Zoom, for some). There was a fear of identification by the perpetrator if support was offered in person at the person’s home, for example. However, this varied, and participants also spoke about the value of face-to-face support, which felt more personal. The importance of local support was also frequently mentioned, as participants thought they would benefit from someone who understands the local community and the specific issues individuals may be facing.

‘Give people a choice. Even with myself, as a counsellor, because I was doing some online counselling, I just noticed the difference the counselling experience itself impacts on actually their emotional wellbeing, just being present in a room and having that kind of emotional transference as well… seeing people’s behaviour patterns and eye contact and just experiencing this journey together I think is very, very important as well.’ Experienced ASB, female, 37, Westminster

6.2.4 Involving the community

As discussed, the impact of ASB on communities could be both positive and negative. In some cases, it brought the community closer together. The COVID-19 pandemic was described as having played a role in this, with apps such as ‘NextDoor’ gaining popularity and providing people with avenues to engage with their neighbours and communities in ways they had not always previously. There was also a common view that the community itself had a role to play in tackling ASB , and some participants talked about using apps and other sharing platforms to inform others about potential ASB risks. Many participants spoke positively about the value of peer and community support and wanted the opportunity for people who had experienced ASB locally to meet, for example through coffee mornings.

6.2.5 Mediation

This was also mentioned as a way for the community to help resolve ASB , which could be facilitated to build a better understanding of each other’s perspectives. Raising awareness of the impact of ASB on people within the community was also mentioned as a way to help perpetrators understand the impact of their own actions. Agencies and organisations described how some councils frequently used restorative justice in an ASB context, but this was not something that was consistently mentioned by agencies and organisations across all local case study areas.

6.2.6 Counselling

A lesser experienced form of support was counselling. Those who had experienced counselling reported positive experiences, citing organisations such as Victim Support. However, as outlined above, there was a sense from some that counselling was less helpful when it would not have any influence on how the case was handled. One participant suggested that, with consent, information shared through counselling sessions could be linked to the handling of the case of ASB . This would avoid victims having to share details directly with the police, in what was perceived to be a less comfortable environment.

6.2.7 Joined-up support

From a participant perspective, support was more effective where a joined-up approach was taken between agencies, for example, housing providers communicating with police, where necessary. This would avoid victims being signposted between services, saving time and emotional energy. From an agency’s and organisation’s perspective, a more holistic multi-agency approach was also perceived to be more effective, considering both the victim and the perpetrator. They highlighted how trying to tackle ASB without considering the reasons behind the incident itself would result in a limited approach.

‘Don’t think about investment in ASB in isolation, don’t think about investment in safer streets and violence against women and girls in isolation, don’t think about the response to homeless communities in isolation, because they’re all being thought about. Don’t think about drug treatment and mental health support in isolation because it very often is the same places with the same cohorts of individuals.’ Stakeholder, police, Cardiff

7. Conclusions

7.1 the range and extent of asb impacts.

While ASB is often considered a ‘low-level crime’, there was some evidence prior to this research that indicated that ASB had profound impacts on individuals who experienced or witnessed it. This study has further developed the evidence base of ASB impacts by quantifying impacts, exploring differences between types of ASB and comparing the experiences of different demographic groups. This has reinforced that the impacts of ASB on individuals’ quality of life are very real and widespread. Insights from the research demonstrated the range of impacts ASB can have on an individual’s personal life, including emotional and behavioural impacts. Impacts on personal networks and community were also found.

7.1.1 Key findings

Emotional impacts were widespread and varied by and within each ASB type, with 93% of participants experiencing at least one, such as anger or loss of confidence. Annoyance was the most common emotional impact experienced, at 56%.

Behavioural impacts were also common, with 66% changing their behaviour or experiencing behavioural changes in at least one way. Avoidance behaviours, such as avoiding certain places, were most common and were found across ASB types.

There were also impacts on personal networks, communities, and institutions, for example more than a quarter of survey participants (27%) stated that their experience of ASB caused a decline in their levels of trust in others/their community. While ASB had negative community impacts, there were ways in which working together to tackle ASB could offset these impacts and, in some cases, unite people. For example, sharing information via social media apps to overcome this common goal united people.

Impacts were perceived to be interlinked. For example, emotional impacts could lead to behavioural changes, whether actively or involuntary taken, which then had knock-on effects on individuals’ interactions with their personal networks and more widely, the community.

7.1.2 Implications for policy and evaluation

Concrete insights, such as the above, help to build a case for the value of tackling ASB in England and Wales. With nearly all survey participants who had experienced or witnessed ASB having been impacted by it in some way, there is a clear need for policies which help to minimise these impacts. Considerations for future policy design are outlined below.

Support offered to those who have suffered from the emotional impacts of ASB needs to be flexible, recognising the range of emotional impacts experienced. A one-size-fits-all approach to support is unlikely to adequately address the different types of emotional impacts and varying depths of impacts. For example, support for an individual experiencing feelings of anger is unlikely to be appropriate for someone suffering from panic attacks.

Interventions to offset the need for avoidance behaviours should be a priority. These behaviours were found regardless of ASB type.

Communities should have input into community-level support interventions. Communities are aware of the types of ASB that occur within their area and have often already proactively come up with their own strategies to offset ASB and its impacts.

The quantitative data produced from this research could be used to baseline the impact of future interventions on the prevalence of different impacts of ASB .

7.2 Factors influencing the likelihood of experiencing ASB impacts

7.2.1 key findings.

While 92% of participants experienced some type of negative impact on quality of life from an ASB incident, the severity of impact varied. This severity was influenced by a number of factors.

Certain types of ASB were shown to negatively impact participants more than others. For instance, those who experienced or witnessed sexual ASB [footnote 39] , nuisance neighbours, problems with out-of-control dogs, or loud music/noise were more likely to have reported significant impacts whereas those who experienced/witnessed vandalism or people using/evidence of drugs were more likely to report little impact.

There were more severe impacts felt where an incident was experienced rather than witnessed. The 3 most impactful types of ASB mentioned above were all more commonly experienced rather than witnessed.

More frequent incidents of ASB had a greater impact. They tended to be found in circumstances in which it was difficult to leave, including in the home. For example, incidents of nuisance neighbours tended to happen regularly.

The vulnerability or demographic characteristics of the individual influenced the extent of the impact. Men, younger people, those living in deprived areas and those living with a mental or physical health condition were all more impacted.

7.2.2 Implications for policy and evaluation

Insights from this research, particularly surrounding the breakdown of types of ASB , could aid the design and targeting of effective ASB interventions. For example, this could include:

• designing support tailored specifically for the more impactful types of ASB (for example, those who personally experience nuisance neighbours or being intimidated/harassed) and those likely to happen more frequently (including more ongoing provision for individuals experiencing these types of ASB )
• targeting resources towards the types of ASB that were found to be more likely to be experienced rather than witnessed [footnote 40]
• prioritising interventions around the most affected individuals (for example, those vulnerable due to pre-existing mental or physical health conditions)

7.3 Minimising and addressing ASB impacts

This study can also contribute to improving the effectiveness of support interventions by providing crucial information about the elements of support services that influenced the level of impact on victims and witnesses, as well as participants’ opinions on what could be done to improve this support to decrease negative impacts from ASB .

7.3.1 Key findings

Participants made a variety of suggestions for the improvement of support services, such as:

• ensuring a timely response and making individuals feel heard
• providing options for anonymity
• being delivered through alternative mediums that are suitable for a range of victims and people who have experienced ASB
• involving the community, for instance through having a community-level support group
• ensuring that there is a multi-agency approach to support offered

7.3.2 Implications for policy and evaluation

The insights outlined in this report provide critical knowledge for local agencies and organisations tasked with mitigating and responding to ASB . From this information about the prevalence of ASB , specific impacts experienced by type of ASB and the demographics of individuals more likely to experience impacts, there is an opportunity to use this data to develop national guidance for local agencies to follow based on these key factors. For instance, this could include guidance on the types of impacts that victims might experience and how to respond to them. Alternatively, guidance could explain who is more likely to experience more severe impacts, and under what circumstances, to allocate resources accordingly.

Data from this study could be used as a baseline for future studies (for example, to determine whether certain types of ASB are becoming more prevalent over time) and data from the quantitative survey could be used to support evaluations of the effectiveness of different interventions (for example, by testing the extent that participants felt that ASB was impacting their quality of life before and after receiving support).

Annex A: ASB types

The following types of ASB were asked about in the survey:

• youths/teenagers/groups hanging around
• drunken behaviour
• inconsiderate behaviour
• loud music/noise
• people using/evidence of drugs
• people being intimidated/harassed
• environmental ASB
• nuisance neighbours
• vehicle-related ASB
• aggressive begging
• problems with out-of-control dogs

Annex B: Sample demographic profiles

Quantitative sample.

Table A1: Gender

Table A2: Age

Table A3: IMD area

Table A4: Region

Table A5: Employment

Table A6: Income

Table A7: Ethnicity

Table A8: Social grade

Table A9: Accommodation type

Table A10: Household makeup

Table A11: Housing tenure

Table A12: Long-term physical or mental health conditions

Table A13: Reduced ability from long-term physical or mental health conditions (n=894)

Victim interview sample

Table A14: Victim interview sample

Victim focus group sample

Table A15: Victim focus group sample

Focus group dates

Table A16: Focus group dates

Agencies and organisations interview breakdown

Table A17: Agencies and organisations interview breakdown

In the survey, ‘personally experienced’ referred to an incident that happened specifically to an individual or was an act that was targeted directly at them, whereas ‘witnessed’ meant an incident that an individual saw, but one that was not targeted at them directly.  ↩

In the survey, ‘wider community or local area’ was described as the area within 15 minutes walking from where the person lived, whereas in the qualitative research this was left to the participant’s discretion/interpretation.  ↩

Anti-social behaviour: Living a nightmare: https://victimscommissioner.org.uk/document/anti-social-behaviour-living-a-nightmare/   ↩

Exploring the effects of long-term anti-social behaviour victimisation: https://journals.sagepub.com/doi/pdf/10.1177/0269758020961979   ↩

Defining and measuring anti-social behaviour: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/116655/dpr26.pdf   ↩

National standard for incident recording: https://www.gov.uk/government/publications/the-national-standard-for-incident-recording-nsir-counting-rules   ↩

Crime Survey for England and Wales: https://www.ons.gov.uk/peoplepopulationandcommunity/crimeandjustice/datasets/methodologynoteonthepossibleordereffectonresponsestoquestionsonantisocialbehaviourfromchangesinthecrimesurveyforenglandandwalesquestionnaireappendixtables   ↩

Victim/witness fieldwork was conducted with individuals from Westminster, whereas agencies and organisations’ interviews were conducted with those in London more broadly due to the availability of relevant individuals.  ↩

Including those who entered the survey and completed the screening questions but were ultimately screened out because they were not eligible to participate.  ↩

The IMD score is a measure of relative deprivation based on 37 separate indicators. IMD  classifies these areas into 5 areas based on relative disadvantage, with area 1 being the most deprived and area 5 being the least deprived. For more information, see https://understanding.herefordshire.gov.uk/inequalities/index-of-multiple-deprivation-imd/   ↩

Attributions of quotes from focus group participants do not include age information due to data recording practices.  ↩

‘Conduct that has caused, or is likely to cause, harassment, alarm or distress to any person; conduct capable of causing nuisance or annoyance to a person in relation to that person’s occupation of residential premises; or conduct capable of causing housing-related nuisance or annoyance to any person.’ https://www.legislation.gov.uk/ukpga/2014/12/contents/enacted   ↩

In the survey, sexual ASB was defined as ‘Sexual anti-social behaviour (for example prostitution or kerb-crawling or evidence of prostitution (such as cards in phone boxes, used condoms, people committing inappropriate or indecent sexual acts in public).’  ↩

3% indicated ‘don’t know/prefer not to say’.  ↩

See footnote 10.  ↩

Participant IMD classified as ‘Other’ where they did not consent to share a postcode.  ↩

Derived from the British National Readership Survey, social grade is a classification system based on the occupation of the Chief Income Earner of a household. Classifications are defined as: Social Grade ABC1: High managerial, administrative or professional, intermediate managerial, administrative or professional, supervisory, clerical and junior managerial, administrative or professional; Social Grade C2DE: Skilled manual workers, semi and unskilled manual workers, state pensioners, casual or lowest grade workers, unemployed with state benefits only. More information can be found at: https://www.ipsos.com/sites/default/files/publication/6800-03/MediaCT_thoughtpiece_Social_Grade_July09_V3_WEB.pdf   ↩

Limited differences across other demographic groups were also present, for example some differences by age were identified. However, these were inconsistent and so have not been explored further in this report.  ↩

Selected 2–10 on a scale where 1 = no effect and 10 = total effect.  ↩

See footnote 13.  ↩

Meaning a rating of 8–10 where 1 = no effect and 10 = total effect.  ↩

Percentages are marked with an asterisk where the base size is below 50. Given the sample size these figures are based on, these findings should be interpreted with caution.  ↩

Selected 8, 9 or 10 on a scale between 1 and 10 where 1 = no effect and 10 = total effect.  ↩

Nuisance neighbours and people being intimidated/harassed had the highest number of emotional impacts, with a mean of 3.6 impacts each.  ↩

Loss of trust in other people/my community and loss of trust in institutions are explored in Section 4.  ↩

Hate crime as defined by the Crown Prosecution Service is ‘Any criminal offence which is perceived by the victim or any other person, to be motivated by hostility or prejudice, based on a person’s disability or perceived disability; race or perceived race; or religion or perceived religion; or sexual orientation or perceived sexual orientation or transgender identity or perceived transgender identity.’  ↩

Responded ‘I am still doing this’ to the question ‘How long after experiencing/witnessing the anti-social behaviour did you do this for?’  ↩

This figure is based on those who selected one or more of the 3 avoidance behaviours, including avoiding certain places or situations (with 36% experiencing this behaviour change), going out of the house less often (24%) or changing their travel plans (17%) after experiencing or witnessing ASB .  ↩

Longevity of emotional impacts was not explored in this research.  ↩

Annoyance and anger have been combined as they are closely aligned.  ↩

https://www.britannica.com/topic/broken-windows-theory   ↩

21% of survey participants overall reported experiencing a significant impact from ASB .  ↩

29% of male survey participants had experienced/witnessed people being intimidated/harassed compared to 25% of female survey participants.  ↩

16% of male survey participants had experienced/witnessed problems with out-of-control dogs compared to 11% of female survey participants and 14% of survey participants overall.  ↩

Note: we have not included percentages of other ethnic groups due to lower base sizes when compared to white ethnicity. Base sizes: White n=2,210, Asian n=134, Black n=51, Other n=12.  ↩

Including those living in the 1-2 IMD areas.  ↩

Including those living in IMD area 5.  ↩

The findings from the qualitative research suggest that sexual ASB may be misinterpreted as sexual harassment, which could result in greater impacts. Findings should therefore be treated with caution.  ↩

Attribution to whether an incident of ASB was experienced or witnessed was done by participants, meaning it is subjective.  ↩

Stakeholder interviews were conducted with those in London more broadly due to availability of relevant individuals.  ↩

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Risk Factors for Antisocial Behavior in Low- and Middle-Income Countries: A Systematic Review of Longitudinal Studies

Joseph murray.

Postgraduate Program in Epidemiology, Federal University of Pelotas, Brazil

Yulia Shenderovich

Institute of Criminology, Cambridge University

Frances Gardner

Department of Social Policy and Intervention, Oxford University

Christopher Mikton

Department of Health and Social Sciences, University of the West of England

James H. Derzon

Center for Advanced Methods Development, Research Triangle Institute

Jianghong Liu

School of Nursing and Perelman School of Medicine, University of Pennsylvania

Manuel Eisner

Violent crime is a major cause of social instability, injury, and death in low- and middle-income countries. Longitudinal studies in high-income countries have provided important evidence on developmental precursors of violence and other antisocial behaviors. However, there may be unique influences or different risk factor effects in other social settings. Extensive searches in seven languages and screening of over 60,000 references identified 39 longitudinal studies of antisocial behavior in low- and middle-income countries. Many risk factors have roughly the same average effects as when studied in high-income countries. Stability of aggression over a 3-year period is almost identical across low- and middle-income countries and high-income countries. Dimensions of comorbid psychopathology such as low self-control, hyperactivity, and sensation seeking are associated with antisocial behavior in low- and middle-income countries, but some early physical health factors have consistently weak or null effects.

Although 80 percent of the world’s population live in low- and middle-income countries (LMICs), most behavioral research has been conducted in “WEIRD” populations—Western, Educated, Industrialized, and Democratic societies ( Henrich, Heine, and Norenzayan 2010 ). This raises fundamental questions about the generalizability of current scientific knowledge and its utility for practice and policy across all human societies. In this essay, we review evidence on risk factors for antisocial behavior in LMICs and consider whether results from high-income countries (HICs) apply similarly in LMICs.

Violence is a major cause of social instability, injury, mental health problems, and death in many LMICs ( Bowman et al. 2008 ; Matzopoulos et al. 2008 ). For example, in Latin America and the Caribbean, interpersonal violence was the leading cause of death among 15–49-year-olds in 2013 ( Institute for Health Metrics and Evaluation 2016 ). Violence is a complex, multifactorial behavior, often preceded by childhood conduct disorders, which also carry many adverse consequences through the life course. Prospective longitudinal studies provide the strongest evidence about predictors of violence, conduct disorders, and other antisocial behaviors, but major reviews of the literature have focused almost exclusively on HICs. Because risk processes for antisocial behavior may not be universal, identifying robust predictors of antisocial behavior in LMICs is a priority to develop effective interventions for most of the world.

Different types of antisocial behavior have different geographic patterns. Homicide, the most serious form of interpersonal violence, shows enormous variation across both time and space. In western Europe, homicide rates declined from about 25 homicides per 100,000 people per year in the Middle Ages to about 1.0 per year in the early twenty-first century ( Eisner 2014 ). Currently, the highest rates of homicide are found in LMICs in the Americas and in sub-Saharan Africa, with rates comparable to those in Europe many centuries ago. In 2013, there were 23.6 homicides per 100,000 people in Latin America and the Caribbean and 20.3 in southern sub-Saharan Africa ( Institute for Health Metrics and Evaluation 2016 ). Rates of nonfatal violence are considerably harder to compare across countries, but self-report surveys suggest levels of assault are nearly three times higher in LMICs than in HICs ( Wolf, Gray, and Fazel 2014 ). In contrast to these striking geographic variations in violence, rates of childhood conduct disorder (about 3.6 percent) and oppositional defiant disorder (2.1 percent) appear to be fairly constant around the globe ( Canino et al. 2010 ; Polanczyk et al. 2015 ). This geographic variability in violence and similarity in rates of childhood disruptive disorders are puzzling given the strong stability of antisocial behavior in individuals through time, at least within HICs ( Olweus 1979 ). Possibly, varying levels of stability in antisocial behavior across LMICs could help explain these patterns.

Developmental and life course theories of antisocial behavior highlight the influence of individual and environmental processes involved in self-control, moral reasoning, social bonding, and social learning from early life through adulthood ( Farrington 2005 b ; Eisner and Malti 2015 ). Prospective longitudinal studies provide the most important evidence on the natural history of antisocial behavior and the interplay of multiple risk and protective factors through the life course and across different ecological levels ( Farrington 2013 ). Evidence from major longitudinal studies has been synthesized in several prior narrative and meta-analytic reviews ( Lipsey and Derzon 1998 ; Rutter, Giller, and Hagell 1998 ; Hawkins et al. 2000 ; Derzon 2010 ; Murray and Farrington 2010 ; Farrington 2013 , 2015 b ; Tanner-Smith, Wilson, and Lipsey 2013 ; Eisner and Malti 2015 ). Key risk factors identified include individual factors such as impulsivity, low IQ, and low school achievement; parenting factors such as poor supervision, punitive or erratic discipline, cold attitude, and child physical abuse; other parent and family characteristics, such as parental conflict, disrupted families, antisocial parents, large family size, and low family income; antisocial peers, high delinquency rate schools, and high-crime neighborhoods. Results are not always consistent across studies, complex interactions still need to be clarified, and the identification of causes, as opposed to mere statistical associations, remains a major challenge for research, but increasing progress is being made ( Jaffee, Strait, and Odgers 2012 ).

Despite the advances made in longitudinal research on antisocial behavior, prior reviews of this evidence focus almost exclusively on studies in western Europe, North America, and Australasia. For example, David Farrington (2015 b ) recently reviewed 30 key longitudinal studies in criminology, and all but one were conducted in high-income countries, possibly because of the strong criteria used to select studies for inclusion in the review—studies with at least 300 participants, personal interviews, and follow-ups of at least 5 years. In other areas of behavioral science, WEIRD populations are considered “among the least representative populations one could find for generalizing about humans” ( Henrich, Heine, and Norenzayan 2010 , p. 61). Why prior reviews have not included more LMIC studies is not entirely clear. It is possible that relevant longitudinal studies are lacking in LMICs, that prior reviews did not aim to cover LMICs, or that standard reviewing methods (e.g., searching only in English) do not locate studies in LMICs. We imagine that most scholars assume that good longitudinal studies are lacking in LMICs.

It should be noted that some longitudinal surveys in HICs selected participants from socioeconomically disadvantaged populations, for example, the working-class sample living in inner London recruited in the classic Cambridge Study in Delinquent Development ( Piquero, Farrington, and Blumstein 2007 ; Farrington, Piquero, and Jennings 2013 ) and the inner-city black youths included in the Philadelphia cohort of the Collaborative Perinatal Project ( Denno 1990 ; Tibbetts and Piquero 1999 ). However, it would of course be a mistake to simply extrapolate results from these populations to people living in LMICs, with different levels of poverty and inequality and sociocultural conditions.

Given the focus of prior reviews on longitudinal studies in HICs, we aim here to synthesize the available evidence on risk factors for antisocial behavior in LMICs and consider whether findings are comparable across settings. We bring together findings from a surprisingly large number of longitudinal studies in LMICs, identified through extensive searches in seven languages. In the first section of the essay, we introduce theoretical perspectives on why risk factors for antisocial behavior could vary across the globe and define key terms used in the subsequent review of the empirical evidence. Section II describes the types of community-based, longitudinal studies that we searched for in LMICs, how we searched for them, and the approach we used to review their findings. Section III describes the 39 longitudinal studies we identified in LMICs and synthesizes their findings, organized in an ecological model of individual-level factors, early health factors, child rearing processes, maltreatment and other adversities, family characteristics, and wider social influences. Although these studies have produced an enormous collection of results, for most risk factors we examine, only a small handful of individual surveys in LMICs provide relevant evidence. We quantitatively pool the results wherever possible using meta-analysis and summarize all study findings in the text to provide a single, comprehensive resource that details existing findings on risk factors in LMICs. Section IV discusses broad theoretical and research implications.

Table 1 gives an overview of the results from our meta-analyses of LMIC studies, where similar constructs were available in prior reviews of studies from HICs. With few exceptions, average bivariate associations were very similar between LMICs and HICs. These similar findings across vastly different sociocultural contexts point toward global similarity in risk factors for antisocial behavior. However, there are two important caveats to this conclusion. First, because the associations represent bivariate correlations, one cannot draw conclusions about the similarity of causal processes. Second, these average associations mask considerable variability in results across different LMIC studies, which could represent context-specific influences of risk factors on antisocial behavior, as well as methodological variation between studies. Half of the meta-analyses of LMIC studies had at least moderate heterogeneity in the results.

N ote .—Associations are bivariate correlations. The strength of association is described as follows (see Sec. II ): negligible, d < 0.10; small, d = 0.10; medium, d = 0.25; large, d = 0.50. References for prior reviews in HICs: 1 , Olweus (1979) ; 2 , Derzon (2010) ; 3 , Lipsey and Derzon (1998) ; 4 , Tanner-Smith, Wilson, and Lipsey (2013) ; 5 , Aarnoudse-Moens et al. (2009) . For some risk factors in the current review, described later in the essay, no prior, comparable review was located for studies in HICs.

Although it is difficult to draw broad conclusions about overall replicability of risk factors based on the current LMIC evidence, and for some risk factors only a very small number of studies were available, the following key empirical findings emerged. First, past behavior was the strongest predictor of future antisocial behavior in LMICs, and associations were very similar to those found previously in HIC studies. Second, other relatively strong bivariate predictors of antisocial behavior in LMICs included hyperactivity and sensation seeking, low social competence, authoritarian parenting, and maternal smoking in pregnancy. Third, for these and other risk factors in LMICs, associations with antisocial behavior were generally similar in size, or slightly smaller than those in HICs, although some associations, such as having a large family and low maternal education, were considerably weaker in LMICs than in HICs. Fourth, there was little specificity in the type of antisocial behavior predicted by risk factors in LMICs, but associations tended to be stronger for child conduct problems and aggression, compared with youth crime or violence. This may be due to a longer time span between the risk factors and young adult outcomes of crime and violence. Fifth, there was good evidence that some of the early health factors studied, such as low birth weight, were not associated with antisocial behavior. Finally, there was substantial heterogeneity in the results for many risk factors investigated in LMICs; however, it is not currently possible to determine if this reflects variations in methodology between studies or substantive differences across social contexts.

We conclude that, although individual studies have provided important local evidence in a number of LMICs, and some broad patterns of findings are discernible, the bigger picture concerning replicability of findings across context is unclear, given the limited evidence available on each risk factor and methodological differences between existing studies in LMICs. It would therefore be premature to conclude whether the etiology of antisocial behavior reflects universal human phenomena or a mix of universal and context-contingent factors. We outline our hopes for a new generation of global coordinated research projects, using common methods and measures, to provide robust evidence on the degree of universality versus specificity of different risk processes involved in antisocial behavior across the life course.

I. Theories, Aims, and Definitions

In this section, we review theoretical perspectives on why risk factors might influence antisocial behavior differently across social contexts and specify our aims and definitions.

A. Why Might Risk Factors for Antisocial Behavior Not Be Universal?

It is possible that risk factors previously identified in HICs reflect universal patterns of human behavior and that similar empirical patterns will obtain consistently across all societies. Some existing studies have compared risk factors between different HICs and found very similar associations, for example, between Pittsburgh, Pennsylvania, and London, England ( Farrington and Loeber 1999 ; see also Farrington 2015 a ). However, given the great diversity in social contexts across LMICs, there are several reasons why risk and protective factors might not replicate so consistently elsewhere. First, even within HICs, numerous surveys suggest that the effects of individual-level and family-level risk factors can depend on community context; that is, there are interaction effects between risk factors across ecological levels. For example, in the Pittsburgh Youth Study, boys’ impulsivity level was positively associated with crime for males living in poor neighborhoods but posed reduced risk for those in better-off neighborhoods ( Lynam et al. 2000 ). Many studies show that parental supervision has stronger effects on child antisocial behavior in high-risk social settings than in less deprived contexts ( Schonberg and Shaw 2007 ). Therefore, looking across the globe to consider populations in radically different socioeconomic and cultural circumstances in LMICs, there may be systematic variability in risk factor associations according to geographic location.

Schonberg and Shaw (2007) discuss two theories why individual and family-level risk factors will probably have stronger effects on child behavior in more deprived social settings. First is the idea that risk factor effects increase when they co-occur: that cumulative risk exposure has multiplicative effects ( Appleyard et al. 2005 ). This “synergistic model” also predicts that risk factors are more likely to co-occur in deprived social settings. Therefore, a single risk factor in a deprived context is likely to have stronger effects on child antisocial behavior than in less deprived settings. A second and related theory also predicts stronger risk factor effects in contexts of adversity but emphasizes the interaction between “vulnerability factors” and “provoking agents” ( Schonberg and Shaw 2007 ). According to this perspective, individual vulnerability factors (such as genetic disposition) result in antisocial behavior only if provoking agents in the environment are also present. For example, adoption studies have shown that increased genetic risk for antisocial behavior, indicated by biological parents having a criminal record, predicts antisocial behavior only when adopting families also present some form of environmental risk ( Raine 2002 b ). Hence, individual-level risk factors should have larger effects in disadvantaged environments that trigger those dispositions.

A contrasting theoretical perspective predicts that individual-level risk factors will have weaker associations with antisocial behavior in high-risk environments because strong social forces override individual-level influences in these settings. Raine (2013) calls this the “social push” hypothesis. Accordingly, biological risk factors should have their strongest influence on antisocial behavior in relatively benign social environments and, by contrast, be overridden in contexts of high social adversity. Raine describes a range of findings on biological factors such as resting heart rate and skin-conductance reactivity, showing that effects are stronger in less disadvantaged social contexts.

Rutter (1999) points to other, more general, considerations about how social contexts can influence risk factor effects. He particularly emphasizes the issue of what a risk factor means socially, pointing to several ways this could influence its effects on behavior. For example, the marked changes in social views concerning childbearing out of wedlock through the twentieth century imply different consequences for mothers and children, with far greater effect in the 1930s, when unmarried mothers were viewed with serious social disapproval, than in later decades. The relative distribution of a risk factor across the population is another facet of social meaning that could alter a risk factor’s effects. Specifically, a risk factor’s influence might depend on a person’s relative social standing rather than an absolute effect. A clear example is the advantage that educational attainment buys in the job market: large population increases in educational attainment have altered the minimum qualification level required to obtain skilled jobs ( Rutter 1999 ). Thinking cross-sectionally, risk factor effects could also vary between countries because of different distributions of risk factors between populations. For example, varying levels of income inequality might mean that low family income has different associations with antisocial behavior across different countries. Rutter terms this a “comparative social context effect” because it reflects the importance of a person’s social standing in relation to others.

In summary, from four theoretical perspectives, different broad empirical predictions may be made about patterns of risk factor effects in LMICs. First, according to a universalist view, risk factor associations should be consistent both in and across LMICs compared with HICs. Second, individual- and family-level risk factors would be expected to have stronger effects in LMICs than in HICs, according to a “multiplicative effects” model, because of the higher likelihood of exposure to additional social disadvantage in LMICs. Third, according to the “social push” perspective, individual-level risk factors should have weaker effects in LMICs than in HICs because greater social disadvantage in LMICs overrides individual-level influences. According to both the “multiplicative effects” model and the “social push” model, variation in risk factor associations would also be expected across LMICs, given their many sociocultural differences. Fourth, if social meanings of risk factors influence their effects, one would also expect heterogeneity in effects, both across LMICs and between LMICs and HICs.

Longitudinal evidence from LMICs is important to test the universality of current developmental and life course theories, identify any context-specific influences on antisocial behavior, and deliver effective interventions in areas of the world most affected by violence. Longitudinal research in LMICs is also important because some risk factors do not occur commonly in HICs. For example, prospective evidence on the link between early childhood malnutrition and antisocial behavior was first described in the Mauritius Child Development Study ( Liu et al. 2004 ). Also, causal inference can be strengthened from research in LMICs if the patterning of underlying confounding factors is different from that in HICs ( Batty et al. 2007 ; Ebrahim et al. 2013 ). For example, a recent Brazilian study of breast feeding provided plausible evidence of causal effects on intelligence because breast feeding was not strongly socially patterned in that setting, although breast feeding is highly associated with maternal education and income in many HICs ( Victora et al. 2015 ). Considering the importance of synthesizing evidence on predictors of antisocial behavior in LMICs, we have four aims:

• To identify and characterize existing longitudinal studies of antisocial behavior in LMICs.
• To synthesize findings in LMICs on longitudinal predictors of child conduct problems and aggression and youth crime and violence.
• To compare average risk factor associations in LMICs with previous findings from HICs.
• To examine the consistency of results across LMICs to provide evidence about the possible universality or cross-country or cultural specificity of predictors.

C. Definitions

“Low- and middle-income countries” (LMICs) are defined as countries with a low- or middle-income status according to the World Bank; they are also sometimes referred to as developing countries. Because a country’s income status can change from year to year, we defined LMICs as countries classified as low- or middle-income during more than half of the years 1987–2012 for which World Bank classifications were available. By this definition, 164 countries were identified as LMICs. Although categorizing countries as low- and middle-income is internationally recognized, the terms hide great disparity within and across countries. For example, about 75 percent of the world’s poor live in middle-income countries such as China, India, and Brazil ( Sumner 2011 ). Despite enormous sociocultural heterogeneity across low- and middle-income countries, most have elevated rates of absolute poverty, income inequality, and violence, placing families, communities, and youths at greater risk ( Knerr, Gardner, and Cluver 2013 ).

“Conduct problems” refer to antisocial behaviors in childhood and adolescence that are symptomatic of oppositional defiant disorder and conduct disorders ( American Psychiatric Association 2013 ). We acknowledge that LMICs are spread across a wide range of cultures, and there is not a consensus about the universality of psychiatric disorders, given the lack of biological markers and gold standards for validation ( Canino and Alegria 2008 ). However, in our review, nearly all studies examined conduct problem symptoms, rather than diagnoses, using instruments such as Achenbach’s System of Empirically Based Assessment (e.g., the “externalizing” subscale of the Child Behavior Checklist; Achenbach and Rescorla 2000 ) or the Strengths and Difficulties Questionnaire (“conduct problems” subscale; Goodman 1997 ), which ask respondents about child behaviors such as temper tantrums, stealing, lying, and fighting. These instruments have shown good psychometric properties across a range of cultures and settings ( Achenbach, Rescorla, and Ivanova 2012 ; Rescorla et al. 2012 ).

“Aggression” refers to behaviors intended to cause physical or psychological harm to others. We examine risk factors for child and adolescent aggression separately from general conduct problems because of the large literature on aggression as a specific type of conduct problem, with different developmental patterns, subtypes, and potentially different prognoses and risk factors ( Eisner and Malti 2015 ). Measures such as the aggression subscale on the Child Behavior Checklist ( Achenbach and Rescorla 2000 ) are commonly used to assess the extent of children’s aggressive behaviors.

“Violence” is defined by the World Health Organization (2002, p. 5) as “the intentional use of physical force or power, threatened or actual … that either results in or has a high likelihood of resulting in injury, death, psychological harm, maldevelopment, or deprivation.” We review studies of interpersonal physical violence by youths (10–29 years old) committed both within families, or with intimate partners, and in the community. We exclude studies of suicidal behaviors or other forms of self-directed violence. Violence can be measured using self-reports or reports by other knowledgeable people (such as parents or teachers) or by collecting official records (e.g., police or court records). We also review findings on risk factors for youth crime that includes nonviolent offending, for two reasons. First, nonviolent offending is one manifestation of conduct disorder, and second, violent and nonviolent criminal behaviors are highly associated ( Farrington 1998 ).

“Antisocial behavior” refers to a wide variety of behaviors that violate societal norms or laws ( Rutter, Giller, and Hagell 1998 ), including the various behaviors we examine—child aggression and conduct problems and youth violence and crime. Given the strong correlations between these behaviors, some researchers consider them manifestations of the same underlying individual potential for antisocial conduct ( Farrington 1991 , 2005 a ).

We generally use the terms “childhood” to refer to ages under 10, “adolescence” to ages 10–17, and “young adulthood” to ages 18–29, with “youth” referring to ages 10–29, following the World Health Organization’s (2015) definition of youth violence. However, sometimes we had to use other distinctions made in the literature regarding specific studies or types of variables.

We review “longitudinal predictors,” which are variables associated with and preceding conduct problems or violence. Longitudinal predictors that increase the risk for adverse outcomes are called “risk factors.” Although most predictors we consider are risk factors, some variables lower the risk of an adverse outcome and are called “protective factors.” Direct protective factors predict a lower probability of antisocial behavior across the whole population, whereas buffering protective factors predict a low probability of antisocial behavior specifically among at-risk groups ( Lösel and Farrington 2012 ). A distinction might also be drawn between “explanatory” and “nonexplanatory” risk factors; explanatory ones clearly measure a construct different from the outcome behavior, and nonexplanatory ones could be measuring the same underlying construct as the outcome ( Farrington, Gaffney, and Ttofi 2017 ). For example, drug and alcohol abuse could be measuring the same underlying construct (such as a broad externalizing behavior syndrome; Patrick et al. 2015 ) as offending. Maybe peer delinquency is also measuring the same underlying construct as delinquency, because of co-offending.

Prospective longitudinal studies are the gold standard for investigating risk and protective factors because they can establish clear temporal order and avoid bias that can arise in retrospective studies ( Kraemer, Lowe, and Kupfer 2005 ). We consider only prospectively measured predictors of antisocial behavior in longitudinal studies. Hence, we do not include findings on correlates measured at the same time as antisocial behavior. Also, we do not review effects of prevention programs unless they yield insight into the effects of naturally occurring risk factors. We focus on modifiable risk factors that can change during the life course, and therefore might be targets for interventions, rather than static risk factors such as a person’s sex or race.

Critically, predictors are not necessarily causal. A risk factor might predict conduct problems or violence merely because it is associated with other causes (confounders), not because it itself influences the behavior. Therefore, although longitudinal predictors meet two criteria for causation (precedence and association), many do not meet a third criterion—that no confounding variable explains the association. Identifying which predictors are causes and which are merely markers of other causes is a major challenge for research, requiring use of experimental or quasiexperimental studies and genetically sensitive research designs to help rule out alternative explanations ( Rutter et al. 2001 ; Shadish, Cook, and Campbell 2002 ; Rutter 2003 ; Kraemer, Lowe, and Kupfer 2005 ; Murray, Farrington, and Eisner 2009 ; Jaffee, Strait, and Odgers 2012 ; Eisner and Malti 2015 ). Most findings we summarize do not permit strong causal inference, but we highlight studies that used stronger methods to improve causal inference, such as negative controls, experiments that target specific risk factors, cross-cohort comparisons, and twin studies ( Richmond et al. 2014 ). Analysis of within-individual change through time has also been recommended as a way to improve causal inference in longitudinal studies ( Farrington 1988 ; Murray, Farrington, and Eisner 2009 ).

II. Methods

Systematic reviews use thorough and explicit search methods, with preset eligibility criteria to locate all available evidence on a research topic, and ideally use quantitative analyses to synthesize the results from primary studies. In this section we detail the systematic review methods used to search for longitudinal studies in low- and middle-income countries, eligibility criteria, and our approach to synthesizing the results on risk factors for antisocial behavior.

A. Search Strategy

We conducted an extensive search for all available evidence on correlates and predictors of childhood conduct problems, aggression, and youth crime and violence in LMICs in multiple languages. Full details of the search and screening methods and the review protocol are described in a separate article ( Shenderovich et al. 2016 ). In summary, we first developed a broad and sensitive search strategy for multiple electronic databases. The search strategy combined terms for low- and middle-income countries, including names of all individual LMICs and relevant regions; children and youths; and relevant outcomes, including antisocial behavior, conduct problems and disorders, externalizing, aggression, bullying, crime, violence, gang membership, and so forth. We searched the following databases in August–September 2013 without restriction on study years or languages: PsycINFO, MEDLINE, EMBASE, CINAHL, EconLit, Criminal Justice Abstracts, Russian Academy of Sciences Bibliographies, Sociological Abstracts and Social Services Abstracts, Applied Social Sciences Index and Abstracts, International Bibliography of the Social Sciences, ERIC, Web of Science, National Criminal Justice Reference Service Abstracts Database, CENTRAL, JOLIS, World Bank, Open Grey, Global Health Library, and Google Scholar.

To complement the English language searches, we used translated search terms in six other languages to search Google Scholar and 12 regional databases: Index Medicus, King Saud University Repository, and YU-DSpace Repository in Arabic; CNKI, Wanfang Data, and Cqvip in Chinese; Index Medicus Afro, Revue de Médicine tropicale, Agence Universitaire de la Francophonie, and Refdoc in French; Elibrary.ru and Panteleimon in Russian; and LILACS and SciELO in Spanish and Portuguese. A further search for grey literature was conducted by entering the keywords into general internet search engines, including Google and Baidu, and contacting over 200 researchers in the field to locate unpublished studies. Jim Derzon (2010) also searched his large database of longitudinal studies to locate any other possibly eligible studies.

B. Eligibility Criteria and Screening

The review protocol was prepared with preset inclusion criteria. Inclusion criteria specified the population, outcome measures, and several methodological quality criteria for drawing conclusions about risk factors ( Murray, Farrington, and Eisner 2009 ; Jolliffe et al. 2012 ). Only prospective longitudinal studies were included in this essay, although cross-sectional and retrospective studies will be examined in other publications. To be eligible, studies must have met all the following criteria:

• The study was conducted in an LMIC.
• The study included at least 100 participants.
• The study reported at least one test of association between a potential predictor of childhood conduct problems or aggression, youth violence, or crime.
• Conduct problems and aggression were measured between birth and age 18, and youth crime and violence were measured between ages 10 and 29.
• Child conduct problems and aggression were measured using standardized instruments such as the Child Behavior Checklist or instruments with enough detail to determine that items concerning other behaviors, such as hyperactivity, were not included in the outcome.
• Measures of violence and crime were based on self-reports, criminal records, or other reports.
• The risk factor and the outcome were measured at the level of an individual. For example, studies of group-level correlates of neighborhood crime rates were not included. Ecological research was beyond our scope.
• Participants must have been recruited using random or stratified probability sampling or sampling of an entire population of children or youths in the community.
• If participants were recruited at schools or other institutions, such as maternity hospitals in birth cohort studies, participants must have been recruited from at least two such institutions to increase generalizability of the findings.
• Only prospective longitudinal studies were eligible.

We excluded cross-sectional and retrospective studies and excluded several longitudinal studies if they reported only correlates measured at the same time as the behavioral outcome ( Jackson 2001 ; Botcheva, Feldman, and Liederman 2002 ; Velásquez et al. 2002 ; Friday et al. 2003 , 2005 ; Taylor et al. 2004 ; Samms-Vaughan, Jackson, and Ashley 2005 ; Reyes et al. 2008 ; Zhou et al. 2012 ). Experimental studies that evaluated interventions that changed potential risk or protective factors for conduct problems, aggression, crime, or violence were included, as experimental studies can help identify causal effects of modifiable exposures.

All 44,318 titles and abstracts in English were screened for potentially relevant studies by Yulia Shenderovich, with Joseph Murray supervising decisions in cases of doubt. Non-English searches and screening of 17,290 titles and abstracts were conducted by six graduate students—four native speakers and two students fluent in the relevant languages. For all references referring to potentially eligible studies, 1,437 full texts were retrieved and screened. A team of 17 people translated all potentially eligible texts reported in languages other than English. All studies meeting the eligibility criteria, whether published or unpublished, conducted at any time up until the searches were completed were eligible. Two authors verified that all studies included met all eligibility criteria. Figure 1 shows a PRISMA flow diagram for the search and screening process.

—PRISMA flow diagram of review search and screening process. * Three studies were reclassified as eligible since Shenderovich et al. (2016) .

C. Synthesis of Findings

We followed prior reviews ( Hawkins et al. 1998 ; Rutter, Giller, and Hagell 1998 ; Hill 2002 ; Farrington and Welsh 2007 ; Murray and Farrington 2010 ; Tanner-Smith, Wilson, and Lipsey 2013 ) and grouped risk factors according to a bioecological model ( Bronfenbrenner and Morris 2007 ) in the following categories: individual factors; perinatal and early childhood health factors; child rearing factors; maltreatment and other adverse life events; family characteristics; peer factors; school factors, community factors, and cultural influences. Findings are reported in relation to the age at which children were exposed to each risk factor and age at outcome measurement, and separately for females and males, wherever original results were stratified by sex.

Meta-analyses were used to synthesize multiple findings from different studies for the same risk factor–outcome association. Evidence was also narratively reviewed to characterize the evidence included in the meta-analyses and to discuss additional findings that were ineligible for meta-analysis. Meta-analyses were conducted using random-effects models (using metan in Stata 12.1), given expected heterogeneity of results across different samples. Prior meta-analyses of predictors of antisocial behavior have generally synthesized only bivariate associations from primary studies ( Hawkins et al. 1998 ; Lipsey and Derzon 1998 ; Derzon 2010 ; Tanner-Smith, Wilson, and Lipsey 2013 ). Most of the meta-analyses we undertook also synthesize only bivariate associations. However, if multiple studies applied similar methods to calculate covariate-adjusted associations, we also meta-analyzed those results, separately, to consider the strength of risk factor associations independent of possible confounding variables. Studies that adjusted for potentially mediating mechanisms (variables on the causal pathway between the predictor and outcome) were not included in meta-analyses ( Victora et al. 1997 ). Adjusting for mediating variables will downwardly bias estimates of risk factor effects.

All studies meeting the eligibility criteria were included in the narrative review, but only studies with an effect size and standard error were included in meta-analyses. For this reason and because we judged some studies too different in their designs and analyses to warrant quantitative pooling of results, some meta-analyses contain fewer studies than the corresponding narrative reviews. Specifically, all findings were included in meta-analyses, unless: multiple studies were not available for the same risk factor–outcome association, mediating mechanisms were adjusted for in the analysis, it was not possible to calculate an effect size for a particular study, or multiple studies used such different designs and analyses that we judged meta-analysis was inappropriate.

Despite these restrictions, many studies had multiple results that were eligible for meta-analyses. To ensure that each meta-analysis was based on independent results, the following procedures were followed:

• Separate meta-analyses were conducted for each predictor.
• Separate meta-analyses were conducted for each outcome of child conduct problems and aggression and youth violence and crime.
• Separate meta-analyses were conducted for bivariate and covariate-adjusted results.
• Males and females were treated as separate samples where results were stratified by sex.
• Where there were still multiple results from a single study, the outcome assessed longest after the predictor was used.
• Where there were still multiple results from a single study, they were averaged, and the average effect size was used in meta-analysis.

Meta-analyses were used first to estimate average associations in LMIC studies. These findings were also compared with results from comparable reviews of longitudinal studies in HICs, to consider the robustness of findings between HICs and LMICs. However, average results in LMICs may obscure important heterogeneity in risk factor effects, for example, between different regions. For most risk factors, it was not possible to test whether results from LMICs varied systematically by region (or by other possible moderators, such as methodological characteristics of the studies), because meta-analyses included too few studies for this type of moderator analysis. However, for the variable that had the largest number of effect sizes (prior conduct problems and aggression), we grouped relevant results according to world region (World Health Organization [WHO] regions of Africa, Americas, Europe, and Western Pacific region) and tested whether these regions or other study characteristics moderated effect sizes in meta-analysis.

In the narrative review, we report effect sizes as they were presented in individual studies in their original form, for example, as odds ratios (OR) or risk ratios (RR) for dichotomous associations and correlations ( r ) or standardized regression coefficients for associations with continuous outcomes. Unless stated otherwise, results are based on bivariate tests of associations between predictors and outcomes. Meta-analytic results are reported using the standardized mean difference ( d ), representing the difference in the behavioral outcome (in standard deviation units) between individuals exposed to a risk factor and individuals not exposed. The same type of effect size ( d ) was used to report meta-analyses of associations adjusted for confounding variables. Sometimes, the terms small, medium, and large are used to describe the magnitude of an effect size, often following Jacob Cohen’s (1988) suggestions. However, existing conventions about what constitutes small, medium, and large, including those of Cohen, are not empirically grounded and ignore the context of the research ( Hill et al. 2008 ). To describe the size of risk factor associations, we used empirical benchmarks based on all 96 effect sizes coded for the meta-analyses. First, we rank-ordered the 96 (absolute) effect sizes, ranging from 0.0 to 5.5, and then divided them into quartiles. The quartiles were then used to define minimum values for small ( d = 0.10), medium ( d = 0.25), and large ( d = 0.50) associations. Equivalent cutoffs for ORs are approximately 1.2, 1.6, and 2.5, respectively. This internal approach—defining the magnitude of effect sizes relative to other findings on the same theme—is similar to that used by Lipsey and Wilson (1993) in their meta-analysis of psychosocial interventions. We also report the I 2 statistic for meta-analytic results, which shows the proportion of the total variance in effect sizes that is beyond chance. As a rough rule of thumb, I 2 = 0 percent suggests no heterogeneity, I 2 = 25 percent suggests low heterogeneity, I 2 = 50 percent suggests moderate heterogeneity, and I 2 = 75 percent suggests high heterogeneity ( Higgins et al. 2003 ).

III. Empirical Findings

This section synthesizes results from 39 longitudinal studies of child conduct problems, aggression, and youth violence and crime in 18 low- and middle-income countries. Section A describes the studies, and Sections B – J present their results grouped according to a bioecological categorization of risk factors. Section K compares meta-analytic results with meta-analytic results from previous reviews of studies of risk factors in high-income countries.

A. Description of the Studies

Of the 39 studies eligible, 12 were conducted in China, six in Brazil, five in South Africa (one of which also included a sample in Tanzania), two in the Czech Republic, two in Jamaica, and one in each of Barbados, Belarus, Chile, Colombia, Croatia, Guatemala, Mauritius, the Philippines, Poland, Puerto Rico, Russia, the Seychelles, and former Yugoslavia. Levels of serious violence in these countries range widely. Compared to the global average of six homicides per 100,000 people per year, homicide rates were lower in Chile, China, Croatia, the Czech Republic, Mauritius, and Poland in 2013; higher (up to 15 per 100,000) in Barbados, Belarus, the Philippines, and the Seychelles; and very high (over 15 per 100,000) in Brazil, Colombia, Guatemala, Jamaica, Russia, and South Africa ( Institute for Health Metrics and Evaluation 2016 ). Looking at development levels in terms of the Human Development Index, indicating longevity, education, and income levels, most included countries ( n = 15/18) had a high level of development in 2014 ( UN Development Programme 2015 ). Two (Poland and Czech Republic) were classified as very highly developed, 13 were highly developed, and three (Guatemala, Philippines, and South Africa) were considered as having a medium level of development. No country had a low level of human development. Two countries (Puerto Rico and former Yugoslavia) lacked data on homicide and human development.

Table 2 summarizes the characteristics of the 39 studies. The study numbers shown in table 2 are used throughout this essay to refer to individual study results (e.g., #1 refers to the Barbados Nutrition Study). Twenty-nine of the studies focused on childhood conduct problems or aggression, five focused on youth violence or crime, and another five examined both childhood conduct problems or aggression and youth violence or crime. Twelve studies were based on birth cohorts, one study sampled children using health care registers, 18 recruited children in preschools or schools, four were based on household samples, and four used a matched risk–control group design, in which children exposed to a risk factor were matched with a control group and both groups were prospectively followed until outcome assessment. Ten studies assessed participants only during childhood (up to age 9), 22 assessed participants during adolescence (between ages 10 and 19), and seven followed participants into young adulthood (20+). The studies used a mixture of participants’ self-reports, direct observations, parent reports, teacher reports, peer reports, medical exams, and official records to assess behavior and possible risk and protective factors. Three studies (#4, #30, #31) made direct comparisons of results with matched samples in high-income countries. Six studies involved evaluations of interventions, including zinc supplement interventions in Brazil and Guatemala (#6, #26), a diet supplement and home visits by health workers in Jamaica (#27), a nutritional and environmental enrichment program in Mauritius (#28), an HIV prevention program in South Africa and Tanzania (#35), and a breast-feeding promotion program in Belarus (#2).

In total, 96 effect sizes were extracted for use in meta-analyses. Table 3 shows that studies in Brazil and China contributed the majority of effect sizes to the meta-analyses. The most common results were for individual-level predictors and conduct problem outcomes. Most effect sizes were smaller than 0.50, and the vast majority (88 out of 95) represent bivariate associations.

B. Individual-Level Characteristics

Longitudinal studies in HICs have identified numerous individual characteristics that are associated with antisocial behavior, including biological factors such as low resting heart rate, and psychological factors including temperament, hyperactivity, low IQ, poor social skills, and positive attitudes toward delinquency ( Hinshaw 1992 ; Rutter, Giller, and Hagell 1998 ; Hill 2002 ; Farrington and Welsh 2007 ; Murray and Farrington 2010 ). Of course, not all risk factors consistently replicate across studies, but one of the strongest and most replicable predictors of future antisocial behavior is prior antisocial behavior ( Lipsey and Derzon 1998 ). We first review evidence for such continuity in antisocial behavior in LMICs before considering evidence on other individual biological and psychological factors. Table 4 shows the meta-analytic results for individual-level factors, and findings from individual studies are summarized below.

N ote .—# = study ID number shown in table 2 ; p a = p -value for d effect size; p b = p -value for a π 2 test for heterogeneity. Random-effects models.

1. Continuity in Antisocial Behavior through Time

In a classic review, Dan Olweus (1979) found that the continuity in an individual’s aggressive behavior through time was about as strong as continuity in intelligence. Across 16 samples in the United States, England, and Sweden, the (disattenuated) correlation coefficient for the continuity in aggression was 0.68, with an average time interval between measures of 5.8 years ( Olweus 1979 ). In our review of LMICs, nine studies assessed the continuity of aggression, and nine studies assessed the continuity of conduct problems, using the same informants on both occasions. 1 To compare the extent of continuity in aggression and conduct problems in these studies with previous findings from HICs, we used the same procedure as Olweus and calculated disattenuated correlation coefficients. 2 We combined results for both sexes, as there were few studies with separate results for males and females. The average time interval between assessments was 3.0 years (range 1.0–8.0 years) for aggression and 2.8 years (range 0.8–8.0 years) for conduct problems.

Pooling results from nine LMIC studies in meta-analysis, the average disattenuated correlation coefficient for continuity in aggression was 0.75 (95% confidence interval [CI] = 0.40 to 0.91, p < 0.001). To compare this with results from Olweus’s review, we estimated the correlation coefficient in Olweus’s review for the same time interval (3 years). 3 Results were almost identical: the disattenuated correlation was 0.73 for studies with a 3-year interval in Olweus’s review. Considering the continuity in conduct problems in LMICs, pooling results from nine studies, the average disattenuated correlation coefficient was 0.49 (95% CI = 0.36 to 0.61, p < 0.001).

There was significant ( p < 0.001) heterogeneity in the results for both continuity in aggression and conduct problems in LMICs. Figure 2 shows the extent of continuity in aggression and conduct problems according to the time interval between measures, with no clear pattern in the results. In meta-regression, we also tested whether the extent of continuity was related to children’s age at first assessment, the time interval between measures, the Human Development Index score of the country of study, the country homicide rate, and the WHO region of the study. No variable was significantly related to continuity in aggression or continuity in conduct problems (all p > 0.05). To compare with other meta-analytic results in this review, the results for continuity in aggression and conduct problems were converted into a d -type effect size and are shown in table 4 . 4

Continuity in aggression and conduct problems through time in LMICs, according to the time interval between measures.

Three studies in LMICs found a small amount of continuity evident between childhood conduct problems and later violence or crime. Among 11-year-olds in Pelotas, Brazil, conduct problems predicted self-reported violence at age 18 (RR = 1.4 for males and 1.9 for females; #4: Murray, Menezes, et al. 2015 ). The corresponding increased risk for nonviolent crime was 1.7 for males and 2.7 for females. This continuity was quite similar to that found in a matched study in Britain ( Murray, Menezes, et al. 2015 ). In Colombia, boys’ behavior problems at school at ages 12–17 predicted self-reported violence 2 years later ( r = 0.22; #22: Brook et al. 2001 ). Continuity in violent behavior itself from ages 12–17 to 2 years later was slightly stronger ( r = 0.37). However, there was no association between conduct problems measured at age 11 and crime at age 23 ( d = −0.08 in follow-back analyses) in a Mauritius study (#28: Gao et al. 2013 ). Pooling results for the association between conduct problems and violence for males in two of these studies (#4, #22), the effect size was medium ( d = 0.34, table 4 ) with significant heterogeneity between the two. Pooling results for the association between conduct problems and crime for males in two studies (#4, #28), the effect size was small ( d = 0.12, table 4 ) with significant heterogeneity.

In summary, across nine longitudinal studies in LMICs, the average continuity in aggressive behavior over 3 years was very similar to that found previously in HICs. However, there was less continuity in conduct problems than aggression in LMICs, and the association between conduct problems in childhood and crime and violence in young adulthood was weak. There was marked heterogeneity in the extent of continuity in antisocial behavior in LMIC studies, but this was not explained by differences in participant age, length of follow-up period, or other study characteristics.

2. Biological Factors

Biological factors that have been related to the development of antisocial behavior in HIC settings include genetic influences, characteristics of brain structure and functioning, features of the autonomic nervous system, and hormonal influences (see, e.g., Rutter, Giller, and Hagell 1998 ; Raine 2013 ; DeLisi and Vaughn 2015 ). An interesting question is whether biological factors have similar effects across LMIC settings, or whether biological influences are attenuated in contexts in which social adversity is greater, as suggested by the social push hypothesis ( Raine 2013 ). Only one longitudinal study in an LMIC examined a genetic influence on antisocial behavior: in a test of the interaction between the genetic polymorphism encoding the monoamine oxidase A (MAOA) enzyme and child maltreatment, originally reported by Caspi et al. (2002) for males in New Zealand. In Pelotas, Brazil, there was no evidence of a main effect of the same MAOA genetic variant on boys’ conduct problems at age 15 or of an interaction between the MAOA variant and maltreatment in predicting conduct problems (#4: Kieling et al. 2013 ).

The Mauritius Child Health Project (#28) provides unique evidence on the association between several biological variables and antisocial behavior. Children who were taller ( d = 0.30), weighed more ( d = 0.25), and had greater body “bulk” ( d = 0.25) at age 3 were more likely to be aggressive at age 11, but they were not more likely to show nonaggressive conduct problems ( Raine et al. 1998 ). Presumably, these associations reflect physical ability to dominate in a fight, which would explain why there was no association with nonaggressive behaviors. Biological measures of electrodermal activity (e.g., skin concordance during an auditory paradigm) were also used as indicators of child fear conditioning and emotionality and tested in relation to antisocial behavior. Electrodermal measures of emotionality at age 3 were associated with teacher ratings of child aggression at age 9 for males, but not for females ( Clark 1982 ). Electrodermal measures of fear conditioning at age 3 also predicted officially recorded crime up to age 23 ( Gao et al. 2010 a ). Furthermore, children with persistently low fear conditioning between ages 3 and 8 had more aggressive ( d = 0.57) and nonaggressive conduct problems ( d = 0.52) at age 8 ( Gao et al. 2010 b ). In relation to autonomic functioning, low resting heart rate when children were age 3 predicted aggressive behavior (RR = 2.1) at age 11, but not nonaggressive conduct problems, after adjustment for other biological and psychological covariates ( Raine et al. 1997 ). In the only test of brain functioning and antisocial behavior in an LMIC study, individuals in the Mauritius study with criminal records at age 23 were compared with controls on measures of P3 amplitude at age 11, a particular brain response during a cognitive task that reflects attentional processing capacity. Criminal offenders had lower P3 amplitude compared with controls ( d = 0.32), and this association persisted even after adjusting for antisocial behavior and hyperactivity at age 11 and alcoholism at age 23 ( Gao et al. 2013 ).

In summary, only two longitudinal studies provide evidence on biological risk factors for antisocial behavior in LMICs. The lack of a gene-environment interaction in the Brazilian study could reflect a predominance of social factors causing conduct problems in that context, measurement differences across studies, or a more generic replication problem in gene-by-environment research ( Duncan and Keller 2011 ; but see Byrd and Manuck [2014] for positive meta-analytic results on the maltreatment-by-MAOA finding). In Mauritius, a small LMIC country with relatively low levels of serious violence ( UN Office on Drugs and Crime 2013 ), numerous childhood biological indicators (larger body size, low resting heart rate, low skin conductance, autonomic fear conditioning, and P3 amplitude) were associated with later conduct problems, particularly aggression, and some measures also predicted increased risk of crime in early adulthood. These investigations in Mauritius are unique within the LMIC studies reviewed here, and many are novel worldwide.

3. Early Child Temperament

Although research in HICs has highlighted the importance of children’s early temperament for the development of antisocial behavior ( White et al. 1990 ; Caspi et al. 1995 ), results on this topic from four studies in Brazil, China, and Mauritius were mixed. In Pelotas, Brazil, no aspect of temperament or psychosocial functioning (withdrawn, somatic complaints, anxious/depressed, social problems, thought problems) at age 4 predicted conduct problems at age 12, adjusting for baseline conduct problems and family socioeconomic status (#4: Anselmi et al. 2008 ). It is possible that these null findings arose because of “overcontrol,” that is, the adjustment of baseline conduct problems, which might themselves have been affected by early temperament. In a study in Beijing and Shanghai, children’s affective behaviors with their mothers were assessed at age 2, but these were not associated with aggression at age 4 (#15: Wang et al. 2006 ). However, in a second study in Beijing, both child internalizing problems ( r = 0.28) and social competence ( r = −0.35) at age 2 predicted conduct problems 1 year later (#12: Zhang 2013 ). In Mauritius, having a sensation-seeking temperament at age 3 predicted aggressive, but not nonaggressive, conduct problems at age 11, adjusting for covariates including height, weight, and body size (#28: Raine et al. 1998 ), but fearlessness at age 3 was not predictive. As previously discussed, early biological measures that tap into constructs of emotionality and poor fear conditioning were also associated with aggression at age 8 in the Mauritius study (#28) and with crime up to age 23.

In summary, two studies in China and Mauritius found associations between several early temperament characteristics (stimulation seeking, poor social competence, emotionality, and poor fear conditioning) and later antisocial behavior, but further research is needed to clarify the effects, given that two other studies reported null findings.

4. Hyperactivity and Attention Deficit

Hyperactivity is one of the most robust risk factors for conduct problems and crime found across longitudinal studies in HICs, with numerous related concepts also predicting antisocial behavior, including attention deficit, restlessness, clumsiness, low self-control, impulsiveness, and risk taking ( Rutter, Giller, and Hagell 1998 ; Pratt et al. 2002 ; Jolliffe and Farrington 2008 ; Murray and Farrington 2010 ). Results from two studies in Chile and China were consistent with this literature. In Chile, hyperactivity at age 6 predicted conduct problems (OR = 2.2) at age 11 (#9: de la Barra, Toledo, and Rodríguez 2005 ), and among 6–9-year-olds in Beijing, higher effortful control (the reverse of impulsiveness) predicted less aggression and fewer conduct problems at ages 10–13 ( r = −0.26 for both outcomes, averaging across parent, teacher, and child reports; #10: Zhou, Main, and Wang 2010 ). Pooling results from these two studies (#9, #10), there was an overall moderate bivariate association between hyperactivity and conduct problems ( d = 0.51, table 4 ). However, in Pelotas, Brazil, hyperactivity at age 4 did not significantly predict conduct problems at age 12, independently of baseline conduct problems and socioeconomic status (#4: Anselmi et al. 2008 ). Again, it is possible that the total effects of hyperactivity were underestimated because baseline conduct problems were adjusted for in the analysis (no bivariate results were available to include in meta-analysis).

Considering hyperactivity measured after early childhood, three LMIC studies assessed associations with violence and crime in LMICs. Meta-analyzing results from two studies (#4, #28), the average bivariate association was almost zero ( d = 0.04, table 4 ), but there was considerable heterogeneity. Specifically, in Mauritius, there was no significant association between hyperactivity at age 11 and crime at age 23 (#28: Gao et al. 2013 ). However, in Pelotas, Brazil, hyperactivity at age 11 predicted violence at age 18 (RR = 1.8 females, 1.3 males), although results for nonviolent crime were weaker and nonsignificant (RR = 1.3 females, 1.2 males), adjusting for child conduct problems and perinatal and family factors (#4: Murray, Menezes, et al. 2015 ). Comparing associations with a matched British study, the effects of hyperactivity on violent and nonviolent crime in Pelotas were similar between sites ( Murray, Menezes, et al. 2015 ). In a third study that examined trajectories of delinquency (and could not be included in the meta-analysis), sensation-seeking among 5–13-year-olds in Puerto Rico predicted delinquent behavior over a 2-year period for both girls and boys, adjusting for various other individual, family, and social factors. Compared with Puerto Rican children living in New York, associations were similar between the two sites, even though the shape of the trajectories differed (#31: Maldonado-Molina et al. 2009 ; Jennings et al. 2010 ).

In summary, studies in LMICs generally show positive associations between hyperactivity, conduct problems, and violence but weak associations with youth crime.

5. Internalizing Problems

Internalizing problems are characterized by symptoms of anxiety and depression and are related to other concepts such as sensitivity, shyness, and poor self-concept. In six studies in LMICs, there were only null or weak associations between measures of internalizing problems and antisocial behavior. The studies are summarized below but were too heterogeneous in their designs and analyses to pool in meta-analyses. Three studies of internalizing problems and antisocial behavior were conducted in China, all showing weak or null associations. In the first, in Beijing, there was no significant association between child depressive symptoms and aggressive behavior over four waves of assessment between ages 9 and 12 (#11: Chen et al. 2012 ). This was a rather special study because repeated waves of data were used to account for continuity in behavior when estimating the associations. In a second study, in Shanghai, shyness at mean age 11 was only weakly associated with lower aggression 2 years later ( r = −0.10), and there was no significant association between low self-worth and aggression (#21: Chen, He, and Li 2004 ). In another Shanghai study, neither shyness/sensitivity nor poor self-perception at ages 7 and 10 was significantly associated with conduct problems 4 years later (#20: Chen et al. 1999 ).

Additional weak or null associations concerning internalizing problems were found in Chile and Colombia. In Santiago, Chile, neither “social contact” nor “emotional maturity” among 6-year-olds significantly predicted conduct problems at age 11 (#9: de la Barra, Toledo, and Rodríguez 2003 , 2005 ). Greater “sensitivity” among 12–17-year-old Colombian males was only weakly associated ( r = −0.06) with lower levels of violence 2 years later (#22: Brook, Brook, and Whiteman 2007 ). However, in Puerto Rico, children’s self-esteem at ages 5–13 predicted trajectories of delinquency over the following 2 years (#31: Maldonado-Molina et al. 2009 ). Higher self-esteem was observed among children whose delinquency remained persistently low compared with children who had initially high then declining rates of delinquency. Interestingly, a rather different pattern emerged among Puerto Rican children living in New York, where self-esteem was highest among children who had persistently elevated levels of delinquency over the 3-year study period ( Maldonado-Molina et al. 2009 ).

To summarize, existing evidence in LMICs generally suggests weak or no associations between internalizing problems or related concepts and conduct problems.

6. Intelligence and Educational Performance

Low intelligence and poor educational attainment are well-replicated predictors of antisocial behavior in HICs ( Hinshaw 1992 ; Rutter, Giller, and Hagell 1998 ; Farrington and Welsh 2007 ; Murray and Farrington 2010 ). Three studies in LMICs also found that low intelligence predicted various forms of antisocial behavior, but associations were robust after adjustment for confounding factors in only two studies. Meta-analyses were not conducted because of the different outcomes assessed across the studies. In Mauritius, low spatial intelligence, but not verbal intelligence, at age 3 predicted persistent antisocial behavior between ages 8 and 17, adjusting for social adversity, hyperactivity, and reading ability (#28: Raine et al. 2002 ). Also, in the Seychelles, children with lower intelligence scores at age 11 had more conduct problems at 17, adjusting for children’s mercury exposure, maternal IQ, and socioeconomic position (#33: Davidson et al. 2011 ). Among Polish children aged 7 and 9, lower intelligence did not predict aggression over a 2-year period, adjusting for baseline aggression, violent television viewing, and sociodemographic factors (#30: Frączek 1986 ).

Regarding school performance, two Chinese studies found only weak effects on antisocial behavior, and their pooled bivariate association was zero ( d = 0.00, table 4 ). In Beijing, lower school grades at ages 6–9 had a weak association with conduct problems ( r = 0.16) but were also associated with less aggression ( r = −0.13) at ages 10–13, averaging across parent, teacher, and child reports (#10: Zhou, Main, and Wang 2010 ). In Shanghai, children with lower participation and competence in school activities at mean age 11 had slightly higher aggression scores ( r = 0.13) 2 years later (#21: Chen, He, and Li 2004 ).

Two studies in the Philippines (#29) and South Africa (#34) also showed null or weak associations between lower educational achievement and violence, and their pooled bivariate association was almost zero ( d = 0.04, table 4 ), with significant heterogeneity between their results. The first study, in the Philippines, found that completing fewer school years by age 18 was not significantly associated with perpetrating intimate partner violence 3 years later, either in bivariate analysis or in adjusting for family of origin characteristics and other individual and household factors (#29: Fehringer and Hindin 2009 ). Among South African males, those with low educational attainment at ages 18–26 were at increased risk (OR = 1.4) for self-reported perpetration of family or intimate partner violence 3 years later (#34: Thaler 2011 ). However, in this study, there was no association with violence against strangers, adjusting for childhood background factors and youth unemployment ( Seekings and Thaler 2011 ).

In summary, there are few studies concerning intelligence and school performance and the development of antisocial behavior in LMICs. Existing studies in China, Mauritius, Poland, South Africa, and the Philippines show weak and inconsistent associations.

7. Drug and Alcohol Use

Drug and alcohol use might contribute to antisocial behavior in several ways, including through physiological changes that increase disinhibited behavior, disruption of family and social bonds, involvement in theft to purchase drugs, and increasing contact with organized violent groups involved in drug trafficking ( Goldstein 1985 ; Rutter, Giller, and Hagell 1998 ; Atkinson et al. 2009 ). Substance use problems could also be an indicator of a broad externalizing behavior syndrome, underpinned by a common construct of behavioral disinhibition ( Patrick et al. 2015 ) and as such represent a marker rather than an explanatory cause of other antisocial behaviors. Although drug use is generally less common in LMICs than in HICs, it is associated with greater risk of mortality in LMICs than in HICs ( Medina-Mora and Gibbs 2013 ).

Only three longitudinal studies have investigated drug or alcohol use as possible risk factors for antisocial behavior in LMICs: one found no association with conduct problems, and two showed associations with violence and delinquency. Two studies (#22, #34) that could be meta-analyzed showed a large-sized average bivariate association between drug use and violence ( d = 0.69, table 4 ). In the first study, conducted in Colombia, marijuana use by 12–17-year-old males was associated with four times the odds of participation in delinquency 2 years later (#22: Brook et al. 2003 ), and lifetime drug use was associated ( r = 0.36) with increased levels of violence ( Brook, Brook, and Whiteman 2007 ). In the second study, South African males aged 14–22 who reported drug taking or drinking multiple times over a 4-year period were at increased risk for perpetrating family or intimate partner violence 7 years later (OR = 2.6 for drugs; OR = 1.5 for drinking; #34: Thaler 2011 ). Heavy drinking across multiple waves was also associated with increased risk (OR = 1.7) of violence against strangers, adjusting for drinking and drug taking in the participant’s childhood home and neighborhood poverty in childhood (#34: Seekings and Thaler 2011 ). However, in another South African study (not in the meta-analysis because only adjusted results were available), a combined measure of alcohol and drug use at ages 10–17 was only weakly associated with conduct problems 1 year later ( β = 0.04), adjusting for baseline measures of conduct problems, poverty, sociodemographics, and violence exposure (#37: Waller, Gardner, and Cluver 2014 ). The adjustment for baseline conduct problems in this study might have caused an underestimation of the total effect of drug and alcohol use on conduct problems.

In summary, two studies in LMICs show associations between drug use and later antisocial behavior, but it is not clear which mechanisms are involved or whether these represent causal effects. Future research should test possible competing mechanisms and incorporate tests of whether drug use predicts antisocial behavior only because they both form a broader syndrome of externalizing behavior.

8. Other, Less Studied, Individual Factors

Numerous other individual factors have been found to relate to the development of antisocial behavior in HICs but have not been extensively investigated in LMICs. Here, we summarize findings from the few studies in LMICs that examined antisocial behavior in relation to social competence, locus of control, attitudes toward deviance, and religiosity. One would expect that attitudes favorable to antisocial behavior would strongly predict antisocial behavior itself. Indeed, in Puerto Rico, 5–13-year-old children with positive attitudes to delinquency were most likely to have a high but declining rate of delinquency, adjusting for several other individual, family, and social factors (#31: Maldonado-Molina et al. 2009 ; Jennings et al. 2010 ). Similar effects were observed in a matched sample of Puerto Rican youths in New York ( Maldonado-Molina et al. 2009 ; Jennings et al. 2010 ). However, in Colombia, a tolerant attitude toward “deviance” at ages 12–17 predicted ( r = 0.17) violent behavior 2 years later only weakly (#22: Brook, Brook, and Whiteman 2007 ).

Two studies in Shanghai (#20, #21) showed no association between children’s sociability and later conduct problems ( Chen et al. 1999 , 2000 ). The pooled bivariate association in these studies was almost zero ( d = −0.03, table 4 ). However, prosocial behavior at age 11 predicted fewer conduct problems 2 years later ( r = −0.22) in one of the studies (#21: Chen et al. 2000 ), and social competence at ages 6–9 also predicted fewer conduct problems 4 years later in another study in Beijing (average r = −0.20; #10: Tao, Zhou, and Wang 2010 ; Chen et al. 2011 ). The pooled bivariate association between social competence/prosocial behavior and conduct problems in these two studies (#10, #21) was medium and negative ( d = −0.43, table 4 ).

The psychological trait of having an “external locus of control” was investigated as a possible predictor of delinquency in San Juan, Puerto Rico (#31). External locus of control means perceiving your life as mainly influenced by uncontrollable, external forces. Children aged 5–13 with a higher external locus of control were more likely to show high but declining trajectories of delinquency over a 2-year period (#31: Maldonado-Molina et al. 2009 ), in contrast to a matched sample in the Bronx, New York, where external locus of control did not associate with any particular delinquency trajectory.

Religiosity has been theorized to be protective against antisocial behavior ( Baier and Wright 2001 ). However, a study in the Philippines found no association between frequent church attendance at age 18 and risk of perpetration of intimate partner violence 3 years later, in either bivariate or multivariate analyses (both RR = 1.0), adjusting for family of origin characteristics including intergenerational violence and other individual and household factors (#29: Fehringer and Hindin 2009 ).

In summary, a small number of LMIC studies suggest antisocial behavior might have a small association with low levels of social competence, having an external locus of control, and having attitudes favorable to delinquency. The limited evidence available in LMICs suggests no association between antisocial behavior and sociability or religiosity.

C. Prenatal and Early Health Influences

It is estimated that over 200 million children in LMICs do not reach their developmental potential by age 5 because of nutritional deficiencies, exposure to toxins, violence, poverty, and other health and social problems early in life ( Grantham-McGregor et al. 2007 ; Walker, Wachs, et al. 2007 ). Some longitudinal research in HICs suggests that early health risks affect children’s neurological development and thereby increase vulnerability to environmental stresses causing antisocial behavior ( Moffitt 1993 ; Raine 2002 a ; Brennan, Grekin, and Mednick 2003 ; Liu 2011 ). This line of research has led to the development of prevention programs from pregnancy onward to enhance children’s development and reduce risk of adverse outcomes, including antisocial behavior ( Tremblay and Japel 2003 ). Eleven longitudinal studies in LMICs examined pregnancy and perinatal factors as possible influences on child conduct problems and youth violence, in Brazil, the Czech Republic, Mauritius, South Africa, and former Yugoslavia. Meta-analytic results are shown in table 5 , with results from individual studies summarized below.

N ote .—# = study ID number shown in table 2 ; p a = p -value for d effect size; p b = p -value for a χ 2 test for heterogeneity. Random-effects models.

1. Prenatal and Birth Factors

Unplanned pregnancy was examined as a possible risk factor for children’s antisocial behavior in Pelotas, Brazil (#4: Murray, Maughan, et al. 2015 ). However, it was only weakly associated with offspring conduct problems at age 11 (females RR = 1.3; males RR = 1.2) and violence at age 18 (females RR = 1.5; males RR = 1.2). The very different, and less common, event of an unwanted pregnancy was the focus of a long-term prospective investigation in the Czech Republic. Children of mothers who, unsuccessfully, applied for an abortion were compared with matched control children in the same school classes and assessed in adulthood. Children from unwanted pregnancies were more likely than control children (OR = 2.2) to have a criminal record by ages 22–24 (#24: Dytrych, Matějček, and Schüller 1988 ), but there was almost no difference (OR = 1.2) in the probability of having a criminal record at age 30 ( Kubička et al. 1995 ), suggesting an attenuation of long-term risk associated with unwanted pregnancies.

Maternal smoking in pregnancy was examined as a predictor of child conduct problems in four studies in Brazil, the Czech Republic, and former Yugoslavia. Meta-analysis of these studies revealed a medium-sized average bivariate association ( d = 0.36, across #4, #25, #39) and reduced covariate-adjusted association ( d = 0.26, across #4, #5, #39; table 5 ). In Pelotas, Brazil, maternal smoking in pregnancy was associated with children’s conduct problems at age 4 (OR = 1.4), adjusting for paternal smoking, parental education, family income, and social class (#4: Brion et al. 2010 ). That children’s conduct problems were associated with maternal but not paternal smoking increased the plausibility of biological effects of tobacco exposure in utero ( Brion et al. 2010 ). In contrast to many HICs, maternal smoking in pregnancy was not strongly socially patterned in Pelotas, Brazil, helping to rule out explanations based on family income or social class. Associations with conduct problems persisted in follow-ups of the same cohort at ages 11 and 15 (#4: Anselmi et al. 2012 ; Murray, Maughan, et al. 2015 ). In another study in Pelotas, Brazil, maternal smoking in pregnancy was associated with higher levels of children’s conduct problems at age 4 ( d = 0.25), adjusting for a range of sociodemographic factors, maternal psychopathology, and childbirth characteristics (#5: Matijasevich et al. 2014 ). Also, in former Yugoslavia, maternal smoking in pregnancy predicted conduct problems at ages 4–5, adjusting for age, sex, ethnicity, lead exposure, birth weight, maternal education, and parental warmth toward the child (#39: Wasserman et al. 2001 ). Moreover, maternal smoking in pregnancy predicted conduct problems at age 8 (e.g., OR = 1.7 for “provokes fights”) in the Czech Republic, although associations weakened by age 13 (#25: Kukla, Hruba, and Tyrlik 2008 ).

Only two studies in LMICs investigated whether maternal smoking in pregnancy predicted youth violence, both in Pelotas, Brazil. Their pooled bivariate results yielded a small and nonsignificant association ( d = 0.13, table 5 ). In a cohort of children born in 1982, there was no association between maternal smoking in pregnancy and conviction for violence up to age 25, either in bivariate analyses or in adjusting for sociodemographic factors (adjusted RR = 1.1 for males, 0.8 for females; #3: Caicedo et al. 2010 ). However, in a later cohort, born in 1993, maternal smoking in pregnancy predicted self-reported violence at age 18 for females (RR = 1.7), but not for males (RR = 1.1; #4: Murray, Maughan, et al. 2015 ).

Maternal alcohol use in pregnancy, urinary infection in pregnancy, and intrauterine growth restriction were also examined as predictors of conduct problems and violence in the 1993 cohort in Pelotas, Brazil (#4: Murray, Maughan, et al. 2015 ). Conduct problems at age 11 were moderately associated with maternal alcohol use in pregnancy (males only, RR = 1.5) and urinary infection in pregnancy (females only, RR = 1.3), but not intrauterine growth restriction for either sex. The only variable associated with violence at age 18 was maternal alcohol use in pregnancy (males only, RR = 1.5). These findings were compared with those from a matched study in Britain; several risk factor associations were weaker in Pelotas than in the British study, especially for males ( Murray, Maughan, et al. 2015 ).

Mercury exposure in utero was investigated as another toxin that might affect children’s neurodevelopment and later antisocial behavior in a study in the Seychelles (#33). However, there was no association between mercury exposure and children’s aggressive or conduct problem behaviors at ages 5 and 17 ( Myers et al. 2000 ; Davidson et al. 2011 ).

Complications at birth (such as breech birth, use of forceps during delivery, caesarean delivery, or difficulty with breathing) were weakly associated with conduct problems at age 11 in Mauritius, and this relationship was partly mediated by low IQ (#28: Liu et al. 2009 ). However, in Pelotas, Brazil, birth complications did not predict violent crime up to age 25, adjusting for sociodemographic factors and maternal smoking in pregnancy (RR = 1.1 for males and 1.2 for females; #3: Caicedo et al. 2010 ).

Six studies, in Brazil, South Africa, the Seychelles, and former Yugoslavia, convincingly show that there is no association between low birth weight and children’s conduct problems. Individually, each reported no association (#5, #6, #8, #33, #36, #39; Myers et al. 2000 ; Wasserman et al. 2001 ; Emond et al. 2006 ; Sabet et al. 2009 ; Rodriguez et al. 2011 ; Matijasevich et al. 2014 ). Pooling effect sizes for low birth weight (<2,500 grams) reported in three studies (#6, #8, #36), the average association with conduct problems was almost zero ( d = 0.01, table 5 ). Covariate-adjusted results were also nonsignificant in five studies ( Myers et al. 2000 ; Wasserman et al. 2001 ; Sabet et al. 2009 ; Rodriguez et al. 2011 ; Matijasevich et al. 2014 ) and almost zero ( d = 0.02, table 5 ) in meta-analysis of two studies for which effect sizes could be computed (#5, #36). Birth weight was also unrelated to violent crime in the 1982 Pelotas study, both before and after adjusting for sociodemographic factors (adjusted RR = 1.3 for males; #3: Caicedo et al. 2010 ). Similarly, premature birth did not predict child conduct problems in all three Brazilian studies that tested the association (#4, #5, #8: Rodriguez et al. 2011 ; Matijasevich et al. 2014 ; Murray, Maughan, et al. 2015 ). The pooled bivariate association in these three studies was almost zero ( d = 0.04, table 5 ), and one covariate-adjusted result was nonsignificant (#8: Rodriguez et al. 2011 ).

In summary, the perinatal factor most consistently associated with child conduct problems in LMIC studies is maternal smoking in pregnancy. Although the evidence is limited, it points toward a possible biological effect of this risk factor, given that maternal smoking but not paternal smoking was predictive in one study, and some results showed associations even after adjustment for covariates. However, similar results have previously been reported in HICs (for a review and meta-analysis, see Wakschlag et al. [2002] ; Pratt, McGloin, and Fearn [2006] ), only to be questioned by null findings in studies with stronger research designs, including twin studies and sibling comparisons ( Maughan et al. 2004 ; D’Onofrio et al. 2008 ; Jaffee, Strait, and Odgers 2012 ). Hence, it is difficult to know whether the associations observed in studies in LMICs really reflect causal effects. Several studies consistently showed that low birth weight and preterm birth were not associated with children’s conduct problems, which is consistent with a prior meta-analysis of very low birth weight and prematurity in HICs ( Aarnoudse-Moens et al. 2009 ). Limited evidence on associations between unplanned pregnancy, unwanted pregnancy, alcohol use in pregnancy, intrauterine growth restriction, and birth complications also suggested zero or only weak associations with conduct problems and violence. These various null and weak findings in LMIC studies are important to consider, given prominent theories predicting adverse influences of early health risks on antisocial behavior via effects on neurological functioning ( Raine 2002 a , 2013 ; Eryigit Madzwamuse et al. 2015 ). However, these studies tended to examine health risks in isolation. Studies in HICs show that prenatal and perinatal health risks are influential when considered in interaction with subsequent adverse social environments ( Piquero and Tibbetts 1999 ; Tibbetts and Piquero 1999 ; Raine 2002 b ), as predicted by some developmental theories ( Moffitt 1993 ). Future research should test for such interactions in LMIC studies.

2. Early Life Health Influences

Malnutrition in the first years of life and early exposure to toxins, such as lead, have been hypothesized to increase risk for antisocial behavior via effects on neurological processes related to behavior control ( Raine 2002 a ; Liu 2011 ). Seven studies examined health factors including malnutrition and exposure to toxins in early childhood as possible risk factors for later antisocial behavior in Barbados, Brazil, China, Guatemala, Jamaica, Mauritius, and former Yugoslavia. Three studies had mixed findings on the effects of malnutrition (see studies #1, #27, #28). Their pooled bivariate association between early malnutrition and later conduct problems was medium ( d = 0.35, table 5 ), with high heterogeneity in the results. Pooling covariate-adjusted results available in two studies (#1, #27) produced a similar association ( d = 0.35, table 5 ) without heterogeneity. Their individual findings were as follows. In Barbados (#1), children with malnutrition in their first year of life were at increased risk for self-reported conduct problems at ages 11–17 ( β = 0.19), adjusting for living conditions in the home ( Galler et al. 2012 ), but malnutrition did not independently predict parent-rated aggression or teacher-rated conduct problems at 9–17 ( Galler and Ramsey 1989 ; Galler et al. 2011 ). In Jamaica (#27), children with stunting at ages 9–24 months were at increased risk for parent-reported conduct problems at ages 11–12 and oppositional behavior at age 17, but not teacher-reported conduct problems at ages 11–12 or self-reported antisocial behavior at age 17 ( Chang et al. 2002 ; Walker, Chang, et al. 2007 ). In the same study, there was no significant difference in oppositional-antisocial behavior by stunting status, adjusting for both housing conditions and witnessing violence (#27: Walker, Chang, et al. 2007 ). In Mauritius, malnutrition at age 3 predicted aggression at 8 and conduct disorder at 17, but there was no association with aggression or delinquency at age 11 or 17 (#28: Liu et al. 2004 ).

It has been suggested that breast feeding may reduce risk for antisocial behavior because of its positive effects on mother-child bonding and nutrients in breast milk that contribute to neuronal development ( Anderson, Johnstone, and Remley 1999 ; Fergusson and Woodward 1999 ; Caicedo et al. 2010 ). Little evidence is available on this topic in high-income countries. However, a strong test of the hypothesis was conducted in Belarus, in a large cluster-randomized trial evaluating effects of breast feeding promotion by pediatric health workers in selected hospitals. Breast feeding duration was substantially increased in the experimental group, and this was found to improve infant health up to age 1 (#2: Kramer et al. 2001 ). However, at age 6, the experimental and control groups had identical levels of conduct problems, as rated by both parents ( d = 0.0) and teachers ( d = 0.0), indicating no protective effect of breast feeding on child conduct problems (#2: Kramer et al. 2008 ). Null results for breast feeding were also reported in relation to violence in Pelotas, Brazil, where longer breast feeding duration did not predict differential risk for violent conviction up to age 25 (#3: Caicedo et al. 2010 ). The relative lack of socioeconomic patterning in rates of breast feeding in the Pelotas context helped rule out confounding in this study.

Lead ingestion has been hypothesized to influence child development and antisocial behavior via its effects on cognition and brain functioning. Many ecological studies suggest an association between environmental lead levels and criminal behavior ( Nevin 2007 ; Mielke and Zahran 2012 ). Neurological research shows effects of lead exposure on brain development ( Wright et al. 2008 ), and a longitudinal study in the United States found an association between pre- and postnatal lead exposure and adult crime ( Cecil et al. 2008 ). However, longitudinal data from LMICs have not supported the lead–antisocial behavior hypothesis. In former Yugoslavia, five out of six measures of blood lead levels taken up to age 2.5 were not associated with child aggression at age 3 (#39: Wasserman et al. 1998 ; Factor-Litvak et al. 1999 ). In the same study, children’s average lead exposure during early childhood was not associated with aggression at ages 4–5 in bivariate analyses, although it was associated ( B = 0.32) with the delinquency subscale of the Child Behavior Checklist after adjusting for sociodemographics, early health factors, and maternal warmth and responsiveness ( Wasserman et al. 2001 ). In a Chinese study, children’s blood lead levels at age 3 did not significantly predict aggressive or oppositional defiant behavior at age 5, adjusting for sociodemographic factors and child IQ (#18: Liu et al. 2014 ).

In Guatemala, the effects of a zinc supplementation intervention on the mental health of school children aged 6–11 were investigated in a randomized control trial (#26: DiGirolamo et al. 2010 ). Although the intervention successfully increased zinc levels ( d = 0.29), among treated children there was no evidence that increases in zinc changed child aggressive behavior or conduct problems.

In summary, although there is some evidence for a small association between malnutrition and child conduct problems, existing evidence in LMICs does not suggest a strong influence of early childhood health factors on the development of conduct problems or violence. Individual studies of zinc and lead exposure indicated no effect on antisocial behavior. Two LMIC studies on breast feeding, including one randomized control trial, are particularly unusual in the literature and provide strong evidence that breast feeding is not a direct protective factor for antisocial behavior.

D. Child Rearing Processes

Child rearing processes play a fundamental role in several major theories of the development of antisocial behavior ( Moffitt 1993 ; Patterson 1995 ; Farrington 2005 b ). However, the effects of any given parenting practice may depend partly on cultural norms and the meanings given to those behaviors ( Lansford et al. 2005 ). For example, it has been suggested that tougher parenting styles may predict better adjustment for children in high-risk communities but worse adjustment for children in low-risk environments ( Cummings, Davies, and Campbell 2000 ). There is considerable variability across LMICs in the extent of use of harsh discipline, including physical punishment, and its cultural acceptability ( Lansford and Deater-Deckard 2012 ; UN Children’s Fund 2014 ); hence it may be expected that parenting practices would have heterogeneous effects on child behavior across different cultural contexts.

1. Harsh, Coercive, and Rejecting Parenting

Parental harsh and inconsistent discipline is considered an important risk factor contributing to escalating difficulties in parent-child interactions and the onset and persistence of behavior problems ( Rothbaum and Weisz 1994 ; Patterson 1995 ; Smith and Stern 1997 ; McCord 1998 ; Farrington 2002 ; Gershoff 2002 ). For example, a meta-analysis of 88 studies showed that corporal punishment was associated with increased child aggression ( d = 0.36) and adult crime and antisocial behavior ( d = 0.42; Gershoff 2002 ). Moreover, although familial confounding and child effects (child behavior causing harsh parenting) are relevant, quasi-experimental studies and randomized experiments are consistent with the view that harsh parenting is a causal risk factor for antisocial behavior ( Jaffee, Strait, and Odgers 2012 ).

Longitudinal evidence on associations between harsh parenting and child antisocial behavior in LMICs comes from China, Russia, Brazil, Poland, Puerto Rico, South Africa, and Colombia. Findings from individual studies are summarized below, and meta-analytic results are shown in table 6 . It is important to note that associations between parenting and child adjustment tend to be highest when assessments of both variables are based on parental reports ( Collishaw et al. 2009 ). Nearly all studies in LMICs used parental reports to assess parenting practices; therefore, we pay particular attention to whether or not child behavior was also assessed by parents or by other informants.

“Authoritarian parenting” refers to a general style of parenting involving coercion, harsh punishment, and withdrawal of affection and has been linked to the development of antisocial behavior in various studies in HICs ( Baumrind 1966 ; Farrington 2002 ; Hoeve et al. 2009 ). In LMICs, two studies, in China (#10) and Russia (#32), reported weak associations between maternal authoritarian parenting and child conduct problems. In the Chinese study, authoritarian parenting when children were 6–9 years old weakly predicted ( r = 0.14) child conduct problems reported by parents, teachers, and children themselves 3 years later, adjusting for other parental characteristics and child conduct problems at baseline ( Zhou et al. 2008 ; see also Tao, Zhou, and Wang 2010 ; #10: Chen et al. 2011 ). In the Russian study, maternal authoritarian parenting in the preschool years predicted self-rated adolescent physical aggression for girls ( β = 0.34) and relational aggression for boys ( β = 0.35), adjusting for other parenting factors and preschool child aggression (#32: Nelson et al. 2014 ). However, in the same study, maternal authoritarian parenting did not significantly predict relational aggression for girls or physical aggression for boys; and paternal authoritarian parenting was not associated with any child outcome. The pooled bivariate association between maternal authoritarian parenting and child behavior problems in these studies was medium-sized and significant ( d = 0.38, table 6 ).

Other studies of authoritarian parenting were not meta-analyzed because they examined only specific subdomains of authoritarian parenting, but nearly all reported positive associations with child behavior problems. Three such studies were conducted in Beijing. The first (#14) found that parental rejecting behaviors of 2-year-olds predicted parent-rated conduct problems ( β = 0.25) when children were aged 4, adjusting for baseline child conduct problems ( Zhu et al. 2011 ). A second study of 2-year-olds in Beijing (#15) found that parental power assertion and harsh parenting when children were aged 2 predicted observer-rated child aggression at age 4 ( β = 0.16), adjusting for other parenting factors and child non-compliance at baseline ( Chen et al. 2002 ). In a third Beijing study (#10), punitive parental reactions to children’s negative emotions, when they were aged 6–9, also weakly correlated with children’s conduct problems 3 years later ( β = 0.07), adjusting for baseline child behavior and family socioeconomic position ( Tao, Zhou, and Wang 2010 ).

Studies in Brazil and Poland also showed positive associations between specific aspects of authoritarian parenting and antisocial behavior. In São Gonçalo, Brazil, parental verbal aggression when children were aged 7 predicted increased parent-rated conduct problems over the next 3 years ( d = 0.30), adjusting for baseline sociodemographic factors and various types of home and community violence (#7: de Assis et al. 2013 ). In Poland (#30), parenting characterized as rejecting of children at ages 7 and 9 was associated with child aggression over the next 3 years in both parent and self-reports ( β = 0.32 for boys and 0.30 for girls), adjusting for other parenting variables, sociodemographics, and violent television viewing ( Frączek 1986 ). Parental “punishment” (presumably referring to harsh punishment) also predicted girls’ ( β = 0.20) peer-rated aggressive behavior, but there was no significant association for boys (#30: Frączek 1986 ). More equivocal results were reported from a Russian study (#32) that examined parental “psychological control” of preschool children as a possible predictor of adolescent self-reported aggression. For boys, there was no significant association, adjusting for other parenting factors and early child aggression ( Nelson et al. 2014 ). For girls, paternal psychological control predicted more relational and physical aggression ( β = 0.40 and 0.36, respectively), but maternal psychological control predicted less physical aggression ( β = −0.26) and was not associated with relational aggression.

Hou et al. (2013) conducted a rare genetically sensitive study of the effects of hostile parenting on children in Beijing, China (#13). Differences in parents’ treatment of monozygotic twins were examined in relation to subsequent twin differences in conduct problems, assessed by parent and self-reports. Twins exposed to more parental hostility than their twin sibling at ages 10–18 did not show more conduct problems 2 years later. By contrast, initial twin differences in conduct problems did predict later parental hostility. This suggested that, rather than parental hostility causing increases in conduct problems, the reverse was true: child conduct problems elicited higher levels of parental hostility in adolescence.

Two studies that examined indicators of harsh parenting in relation to delinquent or violent behavior in LMICs had different findings. In Colombia, strict parental discipline reported by adolescents at ages 12–17 was not associated with self-reported violent behavior 2 years later (#22: Brook, Brook, and Whiteman 2007 ). In Puerto Rico, parental coercive discipline reported by children aged 5–13 was highest among those with a high rate of delinquency that quite rapidly declined over the next 2 years (#31: Maldonado-Molina et al. 2009 ).

As would be expected, parent-child conflict was associated with antisocial behavior in the two studies that examined this issue in LMICs. Among 2-year-old Chinese children, mother-child conflict predicted mother-reported child conduct problems ( r = 0.37) 9 months later (#12: Zhang 2013 ). In Colombia, adolescent-reported conflict with parents at ages 12–17 was weakly associated with self-reported violent behavior ( r = 0.14) 2 years later (#22: Brook, Brook, and Whiteman 2007 ). Given that the studies analyzed different outcomes, they were not meta-analyzed.

In summary, studies of authoritarian parenting styles and specific aspects of harsh parenting generally show associations with child antisocial behavior in LMICs, although not all findings were positive. Notably, all studies relied on questionnaires to assess parents’ attitudes and behaviors, and all but two relied on parental reports. More sensitive observational measures may reveal different patterns. A particular problem with interpreting associations found in these studies is that harsh parenting practices can arise in response to child misbehavior (possible reverse causation), and genetic influences might produce spurious associations between parental and child behaviors ( Jaffee, Strait, and Odgers 2012 ), as suggested by one genetically sensitive study conducted in China ( Hou et al. 2013 ). Causal inference should be strengthened in future research in LMICs by conducting more observational studies that examine within-individual change in both parenting and child behavior through time, employing genetically sensitive research designs, and also by conducting randomized trials of parenting programs designed to reduce child behavior problems, and testing whether intervention effects are mediated by reductions in harsh parenting practices ( Rutter et al. 2001 ). Such studies have been conducted in HICs ( Forehand et al. 2014 ), but not to our knowledge as part of randomized trials in LMICs ( Knerr, Gardner, and Cluver 2013 ).

2. Authoritative and Warm Parenting

In contrast to harsh and rejecting parenting behaviors, an “authoritative” parenting style, combining warmth and limit setting guided by explanations, is theorized to reduce child problem behavior ( Larzelere, Morris, and Harrist 2013 ). However, findings on this issue were mixed in three studies in LMICs, producing a medium-sized, nonsignificant association in meta-analysis. Individual studies included in the meta-analysis were conducted in Russia and China. Among Russian preschool children, authoritative parenting predicted lower levels of self-reported physical aggression for boys ( β = −0.29 mothers; β = −0.39 fathers), but not for girls, adjusting for other parenting factors (#32: Nelson et al. 2014 ). Considering relational aggression as an outcome in the same study, only paternal authoritative parenting was predictive, and only for boys ( β = −0.39; #32: Nelson et al. 2014 ). Among 6–9-year-old children in Beijing, authoritative parenting predicted slightly fewer ( r = −0.12) child conduct problems 3 years later, assessed by parents, teachers, and children themselves, adjusting for other parental characteristics and child conduct problems at baseline ( Zhou et al. 2008 ; see also Tao, Zhou, and Wang 2010 ; #10: Chen et al. 2011 ). In another Beijing study, maternal “inductive parenting” (a concept similar to authoritative parenting), when children were aged 2, predicted less observer-rated aggression for girls ( r = −0.45), but not for boys; paternal inductive parenting was not associated with child aggression (#15: Chen et al. 2002 ). In a meta-analysis of these three studies (#10, #15, #32), the bivariate association between maternal authoritative parenting and child conduct problems and aggression was medium but nonsignificant ( d = −0.26, table 6 ), with significant heterogeneity. Meta-analysis of the two studies (#15, #32) that examined the bivariate association between paternal authoritative parenting and child aggression was of similar magnitude ( d = −0.25, table 6 ).

We conducted a separate meta-analysis of bivariate results from four Chinese studies that examined related subdimensions of authoritative parenting: parental warmth, closeness, acceptance, and responsiveness. Among 2-year-olds in Beijing, paternal warmth ( r = −0.21), but not maternal warmth, predicted less observer-rated child aggression at age 4 (#15: Chen et al. 2002 ). In another sample of 2-year-old children in Beijing, mother-child closeness predicted fewer ( r = −0.28) conduct problems reported by mothers at ages 3–4 (#12: Zhang 2013 ). A third Beijing study found no significant association between parental supportiveness in response to child negative emotions among 6–9-year-olds and child conduct problems 3 years later (#10: Tao, Zhou, and Wang 2010 ). However, in a Shanghai study, maternal acceptance (warmth, enjoyment, and less rejection) toward 7- and 10-year-old children predicted less ( β = −0.14) child aggressive and disruptive behavior 4 years later, as reported by peers (#20: Chen et al. 1999 ). Pooling results across these studies (#12, #10, #15, #20) produced a small bivariate association between maternal “warmth” and child behavior problems ( d = −0.12) that was not significant ( table 6 ).

Three other studies in Poland, former Yugoslavia, and Puerto Rico examined specific aspects of authoritative parenting in multivariate models and had mixed results. Among 7- and 9-year-old Polish children, parental “nurturance” predicted lower peer-rated aggressive behavior ( β = −0.19) for girls over a 3-year period, adjusting for sociodemographics, other parenting variables, and child violent television viewing, but there was no significant association for boys (#30: Frączek 1986 ). In former Yugoslavia, observer ratings of parental warmth and responsiveness with 3-year-old children predicted reduced maternal-reported conduct problems, but not aggression, when children were aged 4–5, adjusting for perinatal and demographic factors (#39: Wasserman et al. 2001 ). In Puerto Rico, levels of family and social support toward children aged 9, on average, did not significantly predict self-reported delinquency over the next 2 years, as was also found in a matched sample in New York (#31: Maldonado-Molina et al. 2009 ).

In the genetically sensitive twin study in Beijing (#13), Hou et al. (2013) examined differences in levels of parental warmth between monozygotic twins as a predictor of twin differences in conduct problems, assessed using both parent and self-reports. The results were null: twin differences in maternal and paternal warmth at ages 10–18 did not associate with levels of conduct problems 2 years later.

Authoritative parenting might be contrasted with overly permissive parenting in which children are not given clear limits about behavior. In Voronezh in Russia, “overly permissive” parenting during children’s preschool years was examined as a possible predictor of adolescent self-rated relational or physical aggression, adjusting for other parenting factors and child aggression in preschool (#32: Nelson et al. 2014 ). For boys, there was no significant association. For girls, high permissiveness by fathers predicted more physical aggression ( β = 0.45); however, high permissiveness by mothers predicted less physical aggression ( β = −0.23), and there were no significant associations with relational aggression. Among Colombian males, those who reported fewer parental rules at ages 12–17 had marginally higher levels of self-reported violence 2 years later ( r = 0.08; #22: Brook, Brook, and Whiteman 2007 ).

In summary, although several studies in LMICs found that authoritative parenting was associated with less child antisocial behavior, results were not consistent, and few studies adjusted for other child and family factors when estimating these effects. As with research on harsh parenting, future studies about the effects of authoritative parenting should use observational measures and strengthen causal inference by analyzing within-individual change, using genetically sensitive designs, and integrating findings from observational studies with those from randomized trials of parenting programs.

E. Maltreatment and Other Adverse Life Events

Stressful life experiences including maltreatment predict a range of adverse health and behavioral outcomes. The effects of multiple stressful events have been highlighted as of particular importance for children’s development ( Anda et al. 2005 ). Stress can affect neurocognitive and endocrine systems, children’s relationships, and learning processes that are implicated in the development of antisocial behavior ( Susman 2006 ). Recent estimates suggest that more than half of children (ages 2–17) worldwide experienced violence during a 1-year period ( Hillis et al. 2016 ). Across 25 LMICs, it was estimated that between 20 and 50 percent of 13–15-year-old children were physically attacked in the previous 12 months ( UN Children’s Fund 2014 ). In this section, we review evidence from LMICs on the effects of maltreatment and other adverse life events on antisocial behavior. The studies summarized below were considered too heterogeneous in their designs and analyses to pool in meta-analyses.

Surprisingly, the three longitudinal studies in LMICs that examined effects of maltreatment on antisocial behavior all found weak or null associations. In São Gonçalo, Brazil, severe parental physical violence against children, reported by parents when children were aged 7, was not significantly associated with child conduct problems over the following 3 years, adjusting for baseline sociodemographic factors and other home and community violence (#7: de Assis et al. 2013 ). In South Africa, physical, emotional, and sexual maltreatment reported by adolescents aged 10–17 was only weakly associated ( β = 0.04) with conduct problems 1 year later, adjusting for baseline levels of child behavior, poverty, and other forms of home and community violence (#37: Waller, Gardner, and Cluver 2014 ). In another South African study, male youths aged 14–22 who reported having been physically abused as a child were not at increased risk of perpetrating family or intimate partner violence 7 years later (#34: Thaler 2011 ).

These same three studies in Brazil and South Africa, and a fourth in the Philippines, also reported weak or null effects of other forms of family violence on antisocial behavior. In São Gonçalo, Brazil, physical violence between grandparents when children were aged 7 was weakly associated ( d = 0.32) with conduct problems over the next 3 years, adjusting for baseline sociodemographic factors and other types of home and community violence (#7: de Assis et al. 2013 ); physical violence between parents was not significantly predictive. In South Africa, exposure to family physical and emotional violence at ages 10–17 was not associated ( β = 0.01) with conduct problems 1 year later, adjusting for baseline poverty level, child behavior, maltreatment, and community violence (#37: Waller, Gardner, and Cluver 2014 ). Also in South Africa, intimate partner violence suffered by mothers until children were age 5 was weakly associated with child aggression ( r = 0.13), but not with oppositional behavior at age 5 (#36: Barbarin, Richter, and DeWet 2001 ). In Cebu, the Philippines, recall of interparental violence at age 18 was not associated with perpetrating intimate partner violence 3 years later, in either bivariate or multivariate analyses, adjusting for other family of origin characteristics and current individual and household factors (#29: Fehringer and Hindin 2009 ).

War-related trauma increases children’s risk for mental health problems such as post-traumatic stress disorder ( Thabet and Vostanis 1999 ). A study conducted in Croatia (#23) was the only longitudinal study in an LMIC to compare child antisocial behavior according to differences in exposure to war. The study included 208 children in Zagreb assessed at age 5 in 1991, before the war in Yugoslavia started, who were then followed up at age 6, during the war (#23: Rabotegsaric, Zuzul, and Kerestes 1994 ). Comparing the same children before and during the war, no change in aggression was observed. Also, there was no difference in levels of aggression between children during the war and a control group of the same age prior to the war. However, the extent of exposure to wartime traumatic events was not assessed in this study, which is an important moderator of the effects of war on other mental health outcomes such as post-traumatic stress disorder ( Pine, Costello, and Masten 2005 ).

Four studies in LMICs examined other forms of stressful life events, such as death of a family member, permanent house moves, and experiences of discrimination, in relation to child antisocial behavior. In Pelotas, Brazil, a composite measure of stressful life events up to age 11 predicted conduct problems at age 15 ( d = 0.39, comparing children who experienced multiple stressful events versus no events; #4: Anselmi et al. 2012 ). In Colombia, experiences of discrimination at ages 12–17 were not associated ( r = 0.01) with violent behavior 2 years later (#22: Brook, Brook, and Whiteman 2007 ). In Puerto Rico, stressful life events at mean age 9 were most common among children who then showed high but rapidly declining delinquency rates, followed by children who showed low but stable rates of delinquency over a 2-year period (#31: Maldonado-Molina et al. 2009 ). In a matched sample of Puerto Rican children in New York, stressful life events were most common among children with a high and increasing rate of offending.

Some of these findings on effects of stressful life events in LMICs are at odds with comparable findings in HICs. Perhaps the most striking difference concerns the effects of child maltreatment. A meta-analysis of the effects of experiencing violence on antisocial behavior in HICs revealed an overall association of d = 0.55 but found a reduced effect ( d = 0.31) among prospective studies, many of which involved child maltreatment ( Wilson, Stover, and Berkowitz 2009 ). Quite similar associations were found for violence experienced in the home ( d = 0.34) and in the community ( d = 0.24). In their review of studies with genetically sensitive research designs, Jaffee et al. (2012) concluded that maltreatment does have causal effects on children’s antisocial behavior, with genetic factors explaining only a very small amount of the association. The null and weak findings on the effects of witnessing violence between other family members were largely in keeping with findings of Wilson et al. (2009, p. 773) , who concluded that “the overall relationship between witnessing violence and juvenile delinquency was negligible ( d = .15).”

In summary, associations between child conduct problems and experiences of violence in the home, including maltreatment, were weak or inconsistent in LMIC studies, and associations with other stressful life events were also generally weak. However, the true consequences of these experiences on young people’s behavior may be obscured in these studies because many adjusted for possible mediating mechanisms, including child behavior measured at the same time as the exposure variable, which could downwardly bias the results. Further research is required on the influence of stressful life events on children in LMICs, particularly experiences of violence, with careful treatment of confounders and mediators used in analyses. Other severe traumas experienced by many children in LMICs, such as female genital mutilation, being orphaned by AIDS, traumas associated with child labor, and wartime traumas, are very important areas for future research ( Benjet et al. 2009 ).

F. Family Characteristics

Family influences play a central role in developmental theories of antisocial behavior ( Farrington 1994 ) and represent a key focus for preventive intervention ( Farrington and Welsh 2003 ). The earlier section on child rearing processes highlighted the importance of parenting practices such as discipline methods, supervision, and affection. In this section, we consider associations between antisocial behavior outcomes and parental mental health and behavior, family socioeconomic factors, and family demographics. Jim Derzon’s (2010) meta-analysis of longitudinal studies in HICs confirmed the following significant correlations between family factors and crime: family stress, r = 0.214; parent antisocial behavior, r = 0.150; broken home, r = 0.095; separated from parents, r = 0.083; low family socioeconomic status, r = 0.129; large family size, r = 0.110; young parent(s), r = 0.079; and urban housing, r = 0.133.

1. Parental Mental Health and Behavior

Parental care of children may be compromised if parents themselves experience stress and mental health problems ( Cummings, Davies, and Campbell 2000 ; Keenan and Shaw 2003 ). This is potentially a major issue in LMICs where rates of maternal mental disorders are estimated to be significantly higher than in HICs ( Affonso et al. 2000 ; Walker, Wachs, et al. 2007 ). Higher rates of mental disorders among poor populations in LMICs are driven by experiences of anxiety associated with economic insecurity, hopelessness regarding future opportunities, rapid social changes, and risks of violence and physical ill health ( Patel and Kleinman 2003 ). However, only two studies prospectively examined maternal mental health as a possible risk factor for children’s conduct problems in LMICs. Both were in Pelotas, Brazil, and both were consistent with the literature in HICs in showing higher rates of child behavior problems among children whose mothers had mental health problems. In the first study, children whose mothers screened positive for mental health problems when children were aged 11 had raised levels of conduct problems at age 15 ( d = 0.54; #4: Anselmi et al. 2012 ). In a second study, maternal psychiatric problems when children were 3 months old predicted conduct problems, rule breaking, and aggressive behaviors at age 4, adjusting for a range of sociodemographic factors and children’s characteristics at birth (#5: Matijasevich et al. 2014 ).

Chen et al. (2011) proposed that Eastern and Western cultures have different values about emotion expression, and as such, parental expression of emotion might have different effects on children in China compared with Western countries, where most previous research on this topic had been conducted. In a study in Beijing, they examined associations between three types of parental emotion expression in the family (negative dominant expression, positive expression, and negative submissive expression) when children were 6–9 years old and tested for associations with children’s conduct problems 3 years later (#10: Chen et al. 2011 ). Adjusting for family socioeconomic status, parenting styles, and child conduct problems at baseline, only parental expression of negative dominant emotion predicted ( β = 0.25) later child conduct problems.

The intergenerational transmission of antisocial behavior is a major theme in the international literature, with both genetic and environmental mechanisms implicated in the transmission ( Rhee and Waldman 2002 ; Thornberry et al. 2003 ; Farrington, Coid, and Murray 2009 ; Murray, Farrington, and Sekol 2012 ). No longitudinal study in an LMIC tested the link between parental crime and child antisocial behavior. However, among 12–17-year-olds in Colombia, illicit drug use by parents and siblings was weakly associated with youth violence 2 years later ( r = 0.07 for mothers, r = 0.18 for fathers, r = 0.16 for siblings; #22: Brook, Brook, and Whiteman 2007 ). Problematic parental drug use can undermine household stability and child care ( Barnard and McKeganey 2004 ), which could affect antisocial behavior. In South Africa, 14–22-year-olds who reported that drugs or alcohol were used in their childhood home were more likely (OR = 1.7) to self-report violence against strangers 7 years later, adjusting for education, unemployment, childhood poverty, and family structure (#34: Seekings and Thaler 2011 ). In the Philippines, parental alcohol use (not necessarily problematic use) when children were aged 10 was not significantly associated with perpetration of partner violence at age 21 (#29: Fehringer and Hindin 2009 ).

In summary, the evidence on the influence of parental mental health and behavior on child and youth antisocial behavior is extremely sparse in LMICs. The few existing studies, in Brazil, Colombia, South Africa, and the Philippines, show positive associations between parental mental health problems and child conduct problems, and parental illicit drug use and youth violence, although no study used a genetically informative design to disentangle potential environmental effects from genetic influences. A single study in China suggests a particular role of parental negative dominant expressivity as a potential predictor of child conduct problems.

2. Family Poverty, Parental Education, and Employment

Poverty and low socioeconomic status can influence child development through proximal influences in the home, such as undernutrition or overcrowding, and through more distal mechanisms such as reduced educational opportunities ( Wachs 1999 ; Walker et al. 2011 ). Quasi-experimental studies in HICs suggest causal effects of family poverty on antisocial behavior ( Jaffee, Strait, and Odgers 2012 ). Therefore, children from impoverished backgrounds in LMICs may be at increased risk for conduct problems or violence. Meta-analytic results on this topic are shown in table 7 , with findings from individual studies summarized below.

Six studies in LMICs examined associations between poverty and child conduct problems. The three studies (#4, #5, #37) that were included in a meta-analysis were conducted in Brazil and South Africa. The pooled bivariate association between poverty and conduct problems was small ( d = 0.12, table 7 ), with high heterogeneity in the results. In Pelotas, Brazil, low family income at birth was associated with child conduct problems at age 11 for boys (RR = 1.3) and girls (RR = 1.5; #4: Murray, Maughan, et al. 2015 ). Also, children whose families remained poor or became poor between birth and age 11 had more conduct problems at age 15 ( β = 0.61, comparing persistently low versus persistently high family income groups), adjusting for other sociodemographic factors (#4: Anselmi et al. 2012 ). These effects were partly explained by stressful life events and maternal mental health problems associated with poverty ( Anselmi et al. 2012 ). In a second study in Pelotas, lower family wealth at birth was also associated with oppositional behavior and conduct disorder at age 6 (RR = 5.0, comparing bottom and top income quintiles); however, this association was mainly a function of the highest income group having a particularly low risk of disorder compared to all other groups (#5: Petresco et al. 2014 ). In South Africa, family poverty at ages 10–17 was not associated with conduct problems 1 year later (#37: Waller, Gardner, and Cluver 2014 ). Three other studies that lacked sufficient information for inclusion in the meta-analysis were conducted in Brazil and Poland and had similarly weak or null results. In São Luís, Brazil, children in low-income families at birth were not at increased risk of conduct problems at ages 7–9, compared to children in medium-income families, although there was some increased risk comparing children in middle-income families to those in high-income families (RR = 1.3; #8: Rodriguez et al. 2011 ). In São Gonçalo, Brazil, 7-year-old children in poor families did not have significantly increased rates of conduct problems over the next 3 years, adjusting for other sociodemographic factors and experiences of violence (#7: de Assis et al. 2013 ). Among Polish children aged 7 and 9, parental income was not significantly associated with children’s aggressive behavior over the next 3 years, adjusting for baseline aggression, IQ, and sociodemographic factors (#30: Frączek 1986 ).

Considering family poverty as a predictor of violence, results from two of the Pelotas cohorts in Brazil were pooled in a meta-analysis. In the first study, children whose family income was below the minimum wage at birth in 1982 had a higher risk for conviction for violence up to age 25 (males OR = 2.3, females OR = 1.4), compared to all other children (#3: Caicedo et al. 2010 ). However, in the later 1993 Pelotas Birth Cohort Study, low family income at birth was not significantly associated with self-reported violence at age 18 for males (RR = 1.2) or females (RR = 1.4; #4: Murray, Maughan, et al. 2015 ); also effect sizes were smaller in this Brazilian study than in a matched British birth cohort ( Murray, Maughan, et al. 2015 ). Combining results from these two cohorts, the association between family poverty and violence was weak ( d = 0.18, table 7 ).

In three other studies in Puerto Rico, the Philippines, and South Africa, associations between family poverty and general delinquency and intimate partner violence were all null. In Puerto Rico, family welfare receipt among 5–13-year-old children did not predict trajectories of delinquency over the next 2 years, as was also found in a matched sample in New York (#31: Maldonado-Molina et al. 2009 ). Among 10-year-olds in the Philippines, neither household income nor wealth predicted perpetration of partner violence at age 21 (#29: Fehringer and Hindin 2009 ). In South Africa, males aged 14–22 who reported having been poor as a child were not at significantly higher risk of self-reported perpetration of family or intimate partner violence 7 years later (#34: Thaler 2011 ).

Low parental education was investigated as a predictor of antisocial behavior in eight studies in Brazil, China, the Philippines, Poland, and former Yugoslavia. Pooling bivariate results that were available in three of the studies in Brazil and China (#4, #8, #12), the association between low maternal education at birth and child conduct problems was weak ( d = 0.15, table 7 ) and nonsignificant, with moderate heterogeneity in the results. Five other studies (#5, #7, #8, #29, #37) also reported nonsignificant covariate-adjusted associations between parental education and child conduct problems and aggression ( Frączek 1986 ; Wasserman et al. 2001 ; Rodriguez et al. 2011 ; de Assis et al. 2013 ; Matijasevich et al. 2014 ). These could not be meta-analyzed given differences in the multivariate analyses used.

Related concepts of family socioeconomic status and parental IQ were investigated in two studies. In Beijing (#10), a combined measure of low parental education and low family income when children were aged 6–9 was positively associated with child conduct problems 4 years later ( β = 0.16), adjusting for parenting styles and child behavior at baseline (see also Tao, Zhou, and Wang 2010 ; Chen et al. 2011 ). In a study in the Seychelles (#33), family socioeconomic position at age 9 was unassociated with conduct problems at age 17, but maternal IQ at age 10 was negatively predictive, adjusting for the child’s own IQ and mercury exposure ( Davidson et al. 2011 ).

Two studies that examined the association between low parental education and youth violence had weak and null findings. In Pelotas, Brazil, low maternal education at birth was associated with self-reported violence at age 18 for females (RR = 1.4) but not for males (RR = 1.1; #4: Murray, Maughan, et al. 2015 ). These results were similar to those found in a matched British study ( Murray, Maughan, et al. 2015 ). In the Philippines, maternal education, indicated by the number of years of schooling, was not associated with perpetration of partner violence at age 21, either before or after adjusting for other parental sociodemographics and domestic violence in the childhood home (RR = 0.96 for both estimates; #29: Fehringer and Hindin 2009 ).

Parental employment status was not associated with child conduct problems or aggression in three studies in Brazil and Poland. In Pelotas, Brazil, children born to parents who had a “proletariat” occupation were not more likely than children of “bourgeois” parents to show conduct problems at age 4 (#4: Brion et al. 2010 ). Also, in São Gonçalo, Brazil, having unemployed parents at age 7 did not significantly predict child conduct problems over the following 3 years, adjusting for other family sociodemographics and experiences of violence (#7: de Assis et al. 2013 ). In Poland, paternal occupational status when children were aged 7 and 9 was not significantly associated with child aggressive behavior over the next 3 years, adjusting for baseline aggression, IQ, violent television viewing, and other sociodemographics (#30: Frączek 1986 ).

Thaler (2011) found significant associations between South African men’s own poverty and unemployment at ages 17–25 and perpetration of family or intimate partner violence 4 years later (#34); odds ratios were 2.0 for being very poor and 1.8 for unemployment.

In summary, existing LMICs studies reveal only weak associations between childhood poverty, parental education, and employment with future antisocial behavior. Some LMIC studies included mediating mechanisms in adjusted analyses, meaning that the overall effects of socioeconomic factors might have been underestimated in those studies. However, bivariate associations also tended to be weak or null, suggesting that these family background factors are not important influences on the development of conduct problems or violence in these studies. These findings on poverty in the family of origin and its impact on antisocial behavior are not markedly different from those reported in HICs. In a meta-analysis of predictors for youth crime and violence, based on 41 prospective studies in HICs, Tanner-Smith et al. (2013) found that correlations between socioeconomic status and later crime and violence were weak ( r < 0.20) or nonsignificant, regardless of the age at which the predictor was measured (childhood, early adolescence, or later adolescence) and of the age at which the outcome was measured (early adolescence, late adolescence, or early adulthood). An examination of studies using designs that allow stronger causal inferences concluded that poverty and family income do have a causal role in antisocial behavior ( Jaffee, Strait, and Odgers 2012 ), but it did not provide a pooled effect size estimate that could be compared to our findings. The only LMIC study that investigated the influence of poverty and unemployment in young adulthood (as opposed to poverty and unemployment in the family of origin) found a positive association with family and partner violence in South Africa.

3. Parental Age, Marital Status, and Family Size

Sociodemographic factors that have been associated with antisocial behavior in HICs include being born to a teenage parent, living in a single-parent household, and having a large family ( Hawkins et al. 1998 ; Jaffee, Strait, and Odgers 2001 ; Derzon 2010 ; Murray and Farrington 2010 ). There is also some evidence for causal effects of young motherhood and divorce on children’s antisocial behavior ( Jaffee, Strait, and Odgers 2012 ). Results from two Brazilian studies (#4, #8) on the association between low maternal age at birth (<20 years) and child conduct problems were combined in a meta-analysis. In Pelotas (#4), having a young mother at birth was associated with child conduct problems at both age 11 (RR = 1.3 for males, 1.5 for females; Murray, Maughan, et al. 2015 ) and age 15 ( d = 0.30; Anselmi et al. 2012 ). However, in São Luís, lower maternal age at birth was not associated with child conduct problems (#8: Rodriguez et al. 2011 ). The meta-analysis of these two studies (#4, #8) produced a weak and nonsignificant association between low maternal age at birth and child conduct problems ( d = 0.20, table 7 ), with significant heterogeneity in the results. Additional evidence on this topic comes from a later study in Pelotas, which did find an association between lower maternal age and child conduct problems at age 4, adjusting for other sociodemographic factors, maternal psychiatric disorder, and childbirth characteristics (#5: Matijasevich et al. 2014 ). However, in São Gonçalo, Brazil, lower parental age was not associated with child conduct problems over the next 3 years, adjusting for other sociodemographic factors and experiences of violence (#7: de Assis et al. 2013 ). Moreover, in the Seychelles, maternal age was not associated with child conduct problems at age 5 ( Myers et al. 2000 ).

Considering risk for violence, in the 1982 cohort in Pelotas, Brazil, having a young mother at birth (<20 years) predicted conviction for violence up to age 25 for females, adjusting for other sociodemographic factors and maternal smoking in pregnancy (bivariate RR = 3.8, adjusted RR = 2.9); however, there was no significant association for males (#3: Caicedo et al. 2010 ). In the later 1993 Pelotas cohort, having a young mother at birth (<20 years) was not associated with self-reported violence at age 18 for males or females (#4: Murray, Maughan, et al. 2015 ). Pooling the bivariate results from these two studies, having a young mother at birth (<20 years) was weakly associated with youth violence ( d = 0.21, table 7 ). In the Philippines, maternal age was not associated with perpetration of intimate partner violence at age 21, either in bivariate analyses or in multivariate analyses adjusting for other family factors in childhood (#29: Fehringer and Hindin 2009 ).

Three Brazilian studies (#4, #5, #8) examined the association between parental marital status and child conduct problems; their pooled bivariate association was almost zero ( d = 0.01, table 7 ). In the 1993 Pelotas cohort, having a single mother at birth was associated with child conduct problems both at age 11 (RR = 1.2 for males; RR = 1.4 for females; #4: Murray, Maughan, et al. 2015 ) and at age 15 ( d = 0.19; #4: Anselmi et al. 2012 ). In the later 2004 Pelotas cohort, having a single mother at birth was also associated with child conduct problems at age 4, adjusting for other sociodemographic factors, maternal psychiatric disorder, and childbirth characteristics (#5: Matijasevich et al. 2014 ). However, in São Luís, Brazil, having a single mother at birth was not significantly associated with child conduct problems (#8: Rodriguez et al. 2011 ). Considering violence as an outcome, there was no association with having a single mother at birth in the two older (1982 and 1993) Pelotas cohorts (#3: Caicedo et al. 2010 ; #4: Murray, Maughan, et al. 2015 ).

Three studies examined whether large family size was associated with child conduct problems. Two of the studies in Pelotas, Brazil, reported weak and null associations. In the 1993 cohort, having three or more siblings at birth was weakly associated with conduct problems at age 11 (RR = 1.2 for both males and females; #4: Murray, Maughan, et al. 2015 ). In the 2004 cohort, maternal parity at birth was not associated with child conduct problems at age 4, adjusting for other sociodemographic factors, maternal psychiatric disorder, and childbirth characteristics (#5: Matijasevich et al. 2014 ). In China, the single-child policy represents a unique setting to investigate family size and child behavior. A study in Nanjing compared 3–6-year-olds with and without siblings on 116 different behaviors assessed four times over a 10-year period. For boys, only four conduct behaviors were significantly more frequent when siblings were present (#19: Tseng et al. 2000 ). For girls with siblings, only temper tantrums were more frequent than for girls without siblings. The very large number of tests conducted in this study (116 each for boys and girls) suggests that these may well be chance findings.

Youth violence was investigated in relation to family size in the two Pelotas studies of children born in 1982 and 1993. In the 1982 cohort, violent conviction up to age 25 was assessed in relation to how many younger and older siblings children had had at age 4. For males, having any younger siblings predicted increased risk of violence (RR = 1.9), adjusting for family sociodemographics, mother smoking in pregnancy, and childbirth characteristics, but there was no significant association with having older siblings and no significant association for females (#3: Caicedo et al. 2010 ). In the 1993 cohort, there was no significant association between having three or more older siblings at birth and risk of self-reported violence at age 18 (#4: Murray, Maughan, et al. 2015 ). Combining these two studies in meta-analysis, the association between having multiple older siblings (two or more in the 1982 cohort, three or more in the 1993 cohort) and youth violence was almost zero ( d = 0.06, table 7 ).

In summary, existing evidence suggests only weak associations between some family sociodemographic factors in the development of conduct problems and violence in LMICs. Notably, nearly all studies to date have been conducted in Brazil. The associations between having a young mother at birth and conduct problems and violence were small. The association between having a single mother at birth and conduct problems was small, and there was no association with violence. There was a negligible association between having a large family and conduct problems, and no association with violence.

4. Other, Less Studied, Family Factors

In the Philippines, parental joint decision making and maternal church attendance measured when children were aged 10 were not associated with perpetration of partner violence at age 21, adjusting for sociodemographic factors, intergenerational violence, and other youth characteristics (#29: Fehringer and Hindin 2009 ).

In former Yugoslavia, living in an apartment (compared to in a house or on a farm) in the perinatal period was not significantly associated with child aggression at age 3, adjusting for sociodemographic factors and an assessment of the child’s home learning environment (#39: Wasserman et al. 1998 ).

G. Peer Characteristics

Adolescence is a period of heightened social sensitivity when peers exert strong influence on risk-taking behaviors ( Blakemore and Mills 2014 ). Two types of peer influence have been studied extensively in relation to antisocial behavior: reinforcement or modeling of antisocial behavior by antisocial peers and possible protective effects of having a supportive friendship network ( Jaffee, Strait, and Odgers 2012 ; Eisner and Malti 2015 ). It is important to emphasize that spurious associations between peer characteristics and child antisocial behavior can arise in two main ways. First, antisocial children may seek companionship with peers showing similar antisocial tendencies; second, children’s own aggressive behaviors may cause particular peer responses, such as social rejection ( Jaffee, Strait, and Odgers 2012 ). Hence, the issue of social causation versus social selection is particularly difficult to disentangle concerning peer effects. Studies of peer influences on antisocial behavior in LMICs were considered too heterogeneous in their designs and analyses to pool results in meta-analyses, but individual study results are summarized below.

Four studies in China, Colombia, Puerto Rico, and South Africa examined the influence of antisocial peers on antisocial behavior. A genetically sensitive study in Beijing is particularly interesting because it tested whether twin differences in antisocial peers at ages 10–18 predicted twin differences in conduct problems 2 years later (#13: Hou et al. 2013 ). The results did not support the social causation hypothesis: initial differences between twins in peer antisocial behavior did not predict later differences in conduct problems, adjusting for baseline parental warmth/hostility and child conduct problems. In Colombia (#22), 12–17-year-olds whose peers were involved in delinquency and drug use were at increased risk for violent behavior 2 years later ( r = 0.22 and 0.27, respectively; Brook, Brook, and Whiteman 2007 ). However, associations were nonsignificant when adjusted for individual characteristics and violent behavior measured at baseline. Among 5–13-year-olds in Puerto Rico, differences in peer delinquency levels predicted children’s own delinquency over the following 3 years (#31: Maldonado-Molina et al. 2009 ). Specifically, peer delinquency was highest among children whose own delinquency showed an initially high but declining trajectory. Interestingly, in a matched sample in New York, peer delinquency was also highest among children who had declining delinquency rates rather than those who had high and increasing rates of delinquency ( Maldonado-Molina et al. 2009 ). In South Africa, 14–22-year-olds who had many friends using drugs were at increased risk for perpetration of family and intimate partner violence 7 years later (OR = 1.5), but having many friends drinking alcohol was not associated with this outcome (#34: Thaler 2011 ).

Peer popularity and peer rejection were investigated in three studies in China and Puerto Rico, and each found a significant association with antisocial behavior. In Beijing, there were bidirectional relationships, with aggressive behaviors increasing risk for subsequent social rejection, and social rejection also contributing to later aggression, over a 4-year period from age 9 (#11: Chen et al. 2012 ). In Shanghai, greater popularity at mean age 11 was associated with less aggression 2 years later ( r = −0.24; #21: Chen, He, and Li 2004 ). In Puerto Rico, peer relations at 5–13 differed only slightly according to children’s trajectories of delinquency over the next 2 years, with positive peer relations being highest among nonoffenders (#31: Maldonado-Molina et al. 2009 ). There was no significant association in a matched sample in New York ( Maldonado-Molina et al. 2009 ).

Three studies in LMICs suggest a weak association between both bullying and peer victimization and antisocial behavior. In São Gonçalo, Brazil, violent victimization at school among 7-year-olds was very weakly associated with conduct problems in the next 3 years ( d = 0.15), adjusting for baseline sociodemographic factors and other types of home and community violence (#7: de Assis et al. 2013 ). In Jinan, China, victimization by peers and child aggression were assessed annually for 4 years among children aged 9 and 11 years at baseline. Physical victimization by peers was weakly associated with physical aggression ( β = 0.05), and relational victimization by peers was weakly associated with relational aggression ( β = 0.05), but only in the last years of the study, not before transitioning from primary to middle school (#17: Chen 2012 ). In South Africa, experiencing any bullying at ages 10–17 was only weakly associated with conduct problems 1 year later ( d = 0.16), but experiencing four or more types of bullying was strongly associated ( d = 0.58) and remained significant adjusting for child demographics, family poverty, and residence location (#37: Boyes et al. 2014 ).

In summary, nine studies in LMICs suggest that antisocial behavior is positively associated with both peer victimization and having antisocial peers, and it is inversely associated with both peer popularity and positive peer relations. The relatively weak association found between peer victimization and antisocial behavior is broadly consistent with a 2012 meta-analysis that found that bullying victimization predicted violence with an odds ratio of 1.43 (equivalent to a small effect size of d = 0.19; Ttofi, Farrington, and Lösel 2012 ). Regarding the influence of antisocial peers, limited evidence from LMICs suggests that reverse causation is important, with one genetically sensitive study finding no effect of peer antisocial behavior on later conduct problems and another study showing bidirectional effects between aggression and social rejection.

H. School Environment

In HICs, it is well established that there are large differences in rates of antisocial behavior between different schools ( Rutter, Giller, and Hagell 1998 ). Children with antisocial behaviors disproportionately attend high–delinquency rate schools that have high levels of distrust between teachers and students, low commitment to the school by students, and unclear and inconsistently enforced rules ( Graham 1988 ). However, what is less clear is to what extent such differences reflect school influences related to their organization, climate, and practices or different intakes of children into schools ( Rutter et al. 1979 ; Rutter, Giller, and Hagell 1998 ). Only one study in an LMIC examined the influence of school environment on youth antisocial behavior. In Puerto Rico (#31), the school environment was assessed at ages 5–13 by asking children about factors such as the number of substitute teachers they had had in the previous year. School environments were much more negative among children with high initial delinquency rates, which then declined over a 2-year period, and among children with moderate and stable delinquency rates, compared to children with a nonoffending trajectory (respectively, d = 1.1 and 0.6; #31: Maldonado-Molina et al. 2009 ). Negative school environment also distinguished children’s delinquency trajectories after adjusting for a range of individual, family, peer, and social factors. And negative school environment was also found to be important for delinquency trajectories in a matched sample in New York: children with a high and increasing rate of delinquency had the most negative school environments ( Maldonado-Molina et al. 2009 ).

In summary, a single LMIC longitudinal study conducted in Puerto Rico found large effects of school environment on children’s delinquent development. However, much more research is needed on this important topic, particularly using experimental and quasi-experimental designs to test causal mechanisms ( Rutter, Giller, and Hagell 1998 ).

I. Community Influences

A long history of research in HICs has established that offenders tend disproportionately to live in inner-city areas characterized by physical deterioration, neighborhood disorganization, and high residential mobility ( Shaw and McKay 1969 ). However, it is difficult to determine to what extent the areas themselves influence antisocial behavior and to what extent people with antisocial behavior tend to live in deprived areas, for example, because of family poverty or public housing allocation policies.

Few LMIC studies examined associations between neighborhood characteristics and antisocial behavior, and they were too heterogeneous to pool in a meta-analysis. Considering the influence of neighborhood crime rates, Brook et al. (2007) investigated whether drug availability, neighborhood risk, and danger on the street predicted youth violent behavior 2 years later among 12–17-year-old Colombians (#22). Only community drug availability was significantly associated with perpetrating violence ( r = 0.11). In South Africa, community violence and political violence near children’s homes were assessed from children’s birth to age 5. Community violence was associated with child aggression ( r = 0.13), but not oppositional behavior at age 5 (#36: Barbarin et al. 2001 ); political violence was not associated with aggressive or oppositional behavior.

The only study to examine neighborhood poverty was a South African survey of 14–22-year-old males. Youths who had grown up in poor neighborhoods were at increased risk (OR = 1.7) for perpetrating family or intimate partner violence 7 years later (#34: Thaler 2011 ). However, in separate analysis of the same study, there was no association between childhood neighborhood poverty and perpetrating violence against strangers (#34: Seekings and Thaler 2011 ).

Violent victimization in the community was inconsistently associated with conduct problems in three studies in LMICs. In São Gonçalo, Brazil, violent victimization in the community at age 7 was not significantly associated with conduct problems over the next 3 years, adjusting for baseline sociodemographic factors and other types of home and school violence (#7: de Assis et al. 2013 ). In South Africa, witnessing or being a victim of serious violence in the community at ages 10–17 was only weakly associated ( β = 0.07) with conduct problems 1 year later, adjusting for baseline child behavior, poverty, and violence in the home (#37: Waller, Gardner, and Cluver 2014 ). Also in South Africa, violent victimization of a family member between children’s birth and age 5 was weakly associated with oppositional behaviors ( r = 0.07), but not aggression at age 5 (#36: Barbarin et al. 2001 ).

Two studies in LMICs found positive associations between violent victimization and perpetration of violence or delinquency. In Colombia, violent victimization at ages 12–17 was associated ( r = 0.31) with violent behavior 2 years later (#22: Brook, Brook, and Whiteman 2007 ). In Puerto Rico, exposure to violence at mean age 9 was highest among children who had high but rapidly declining delinquency rates over the next 2 years, followed by children who had low but stable rates of delinquency (#31: Maldonado-Molina et al. 2009 ). In a matched sample of Puerto Rican children living in New York, exposure to violence was highest among children with a high and increasing rate of offending—a delinquency trajectory that did not exist in the sample living in Puerto Rico ( Maldonado-Molina et al. 2009 ).

In summary, limited evidence suggests small associations between antisocial behavior and community poverty, drug availability, and violence in Colombia and South Africa. Individual studies report associations between violent victimization and later violence, but evidence was inconsistent regarding the association between victimization and conduct problems.

J. Cultural and Media Influences

The influence of media violence on children and youths is an important theme in the international literature ( Rutter, Giller, and Hagell 1998 ; Huesmann et al. 2003 ; Bushman and Huesmann 2006 ). Its effects on children were studied in Poland as part of a large international project on this topic ( Huesmann and Eron 1986 ). At baseline, Polish children aged 7–9 were interviewed about their favorite television programs, which were then coded by research staff for violent content. Preference for violent television programs was associated with child aggression over a 3-year period ( r = 0.14 for both boys and girls), independently of baseline levels of aggression (#30: Frączek 1986 ; Groebel 1988 ) and also independently of child IQ, parenting factors, and parental social class. Associations between violent television viewing and aggression in matched samples in HICs were for boys and girls, respectively, r = 0.15 and 0.14 in the United States; r = 0.08 and 0.00 in Australia; r = 0.21 and 0.65 in Finland; and r = 0.29 and 0.52 in Israel, adjusting for baseline aggression ( Groebel 1988 ). Hence, associations varied considerably between countries, and the small correlations in Poland were most similar to those in the United States. In Colombia, 12–17-year-old males who reported a preference for violent television also reported more violent behavior ( r = 0.14) 2 years later (#22: Brook, Brook, and Whiteman 2007 ). Of course, this association could reflect proviolent attitudes causing a preference for both violent television and violent behavior.

Cultural beliefs about masculinity and sexual entitlement may facilitate perpetration of intimate partner violence ( Santana et al. 2006 ; Jewkes et al. 2011 ). Believing in male sexual entitlement was investigated as a possible risk factor for perpetrating intimate partner violence in a study in three towns in South Africa and Tanzania (#35: Wubs et al. 2013 ). Adjusting for baseline violence at ages 10–18, adolescents who believed in male sexual entitlement were more likely to perpetrate intimate partner violence 6 months later in all three study sites (OR = 1.3 in Cape Town; OR = 1.6 in Mankweng; OR = 1.8 in Dar es Salaam), although the association persisted to a 1-year follow-up only in Cape Town (OR = 1.3).

A unique investigation of the effects of “acculturation” and “cultural stress” was conducted in San Juan, Puerto Rico, and in a matched sample of Puerto Rican families in New York. When children were aged 5–13, children and parents were assessed for levels of “acculturation” (meaning how much they used English and were integrated into US cultural norms) and “cultural stress” (meaning how much distress they experienced from pressure to adapt to US cultural norms). Children’s conduct problems were predicted only by parental acculturation and cultural stress ( r = 0.15 and 0.13, respectively), and only in the San Juan sample, not in the matched New York sample (#31: Duarte et al. 2008 ). However, children’s delinquency rates did vary according to their own levels of acculturation in San Juan: children who showed initially high and then declining levels of delinquency over 2 years had higher levels of acculturation than children in the nonoffending group and children in the stable but moderate delinquency group (#31: Maldonado-Molina et al. 2009 ; Jennings et al. 2010 ); this difference was not observed in the matched New York sample.

In summary, there are few longitudinal studies on the influence of cultural and media influences on antisocial behavior in LMICs. Small associations were observed between television violence and antisocial behavior. A single study in South Africa found short-term associations between beliefs about male sexual entitlement and intimate partner violence. One study found a weak association between the degree of family integration into US culture and the development of antisocial behavior among Puerto Rican children.

K. Relative Strength of Predictors and Comparison of Results with Those of High-Income Countries

In this section, we consider the relative size of risk factor associations estimated in the meta-analyses of studies in LMICs and how those results compare with findings from existing similar meta-analyses of longitudinal studies in HICs. To compare like with like, we examine bivariate associations from the current review while recognizing that these are less informative regarding causal inference. We used findings from prior meta-analyses that examined a wide range of risk factors in HICs ( Lipsey and Derzon 1998 ; Derzon 2010 ; Tanner-Smith, Wilson, and Lipsey 2013 ), as well as searching for additional meta-analyses of individual risk factors in bibliographic databases and David Farrington’s recent systematic review of reviews ( Farrington, Gaffney, and Ttofti 2017 ). Additional meta-analyses of bivariate associations based on longitudinal studies from HICs were located only for aggression ( Olweus 1979 ) and very low birth weight/prematurity ( Aarnoudse-Moens et al. 2009 ). Note that in the latter review, the cutoff for very low birth weight (<1,500 grams) was lower than that for low birth weight (<2,500 grams) in our review.

Figures 3 and ​ and4 4 show the pooled bivariate associations between risk factors and child conduct problems and youth violence in LMICs, ordered by size. Consistent with evidence from HICs ( Lipsey and Derzon 1998 ; Tanner-Smith, Wilson, and Lipsey 2013 ), the strongest associations in LMICs relate to prior measures of antisocial behavior: prior conduct problems predicting later conduct problems and drug use and conduct problems predicting violence. The next-strongest predictors of conduct problems in LMICs were hyperactivity, low social competence, maternal authoritarian parenting, maternal smoking in pregnancy, and malnutrition, with associations ranging from d = 0.35 to 0.51. For violence, the next-strongest risk factors, after prior antisocial behavior, were having a young mother at birth, family poverty during childhood, and maternal smoking in pregnancy, but the strength of these associations was small ( d = 0.15 to 0.21). Associations for comparable constructs assessed in HICs (also shown in figs. 3 and ​ and4) 4 ) were generally similar or slightly stronger compared with those from LMICs. In fact, the only significant and large differences were for low maternal education and having a poor family, associated more strongly with conduct problems in HICs (both p < 0.001), and having many siblings, which was also more strongly associated with violence in HICs ( p < 0.001).

Longitudinal predictors of child conduct problems: average bivariate associations ( d and 95 percent confidence interval). * Results refer to aggression or conduct problems with aggression.

Longitudinal predictors of youth violence: average bivariate associations ( d and 95 percent confidence interval). * Results for LMICs refer to intimate partner violence.

IV. Discussion

We identified 39 longitudinal studies of child and youth antisocial behavior in low- and middle-income countries. This is a remarkable number of studies, given that prior reviews have been based almost exclusively on surveys in WEIRD populations in HICs. Studies in LMICs variously examined the roles of individual factors, child rearing processes, adverse childhood experiences, family characteristics, and peer, school, community, and cultural factors in the development of antisocial behavior, although for a number of risk factors, evidence in LMICs was sparse. Below, we discuss key theoretical issues related to the findings, focusing on the following general themes: global replicability of risk factors, the stability of antisocial behavior through time, paradoxical cross-country rates of conduct disorder and serious violence, early childhood as a possible sensitive period, the role of parenting factors, and some striking null findings that emerged in the review.

A. Global Risk Factors for Antisocial Behavior?

This review of risk factors for antisocial behavior in LMIC countries was motivated, in part, by a fundamental question of criminology: Do theories of offending and antisocial behavior have universal validity across all human societies? Or are there differences between societies, not only in the prevalence of causal mechanisms but also in their effects?

Many developmental and life course theories in criminology were developed in the 1990s. They responded to an increasing set of regularities, based on a growing number of longitudinal studies in HICs, that required explanation. Prominent theories developed in this period include, for example, Terrie Moffitt’s (1993) dual taxonomy of offending behavior, Thornberry and Krohn’s ( Thornberry et al. 1994 ; Thornberry and Krohn 2005 ) interactional theory of antisocial behavior, Sampson and Laub’s (1993) age-graded informal control theory, and Farrington’s (2003) integrated cognitive antisocial potential theory; others are described by Farrington (2005 b ) .

Few if any of these life course and developmental theories in criminology specify the range of societies and contexts that they apply to. An exception is Moffitt’s dual taxonomy in that the adolescence-limited group is believed to reflect underlying tensions associated with the transition from childhood to adulthood that are specific to modern societies. In contrast, most theories implicitly assume that the causal mechanisms involved in the stability and change of antisocial behavior apply to all societies, at all times, in all places.

The present review has brought together a previously unknown wealth of regularities and evidence on risk factors in LMICs. In the broadest sense, findings on the patterning of risk factors are consistent with what has been found in HICs. Measures of underlying psychological propensity show the highest associations with antisocial behavior over time, proximal risk factors tend to be more consistently associated, and distal risk factors generally have weak associations with behavioral outcomes. This first set of findings points to generalizability of results across the globe.

While important, these regularities provide limited insight into whether the life course theories developed in criminology have universal validity, let alone which theory is more suited to explain the empirical regularities. The reason is that, although average risk factor associations were generally similar between LMICs and HICs, heterogeneity was common between individual studies in LMICs. We emphasize that this could be primarily an artifact of different methodologies applied across surveys; however, it is also possible that it reflects true differences in risk factor effects between geographic locations and cultural groups in LMICs.

This systematic review consists of 39 studies from five continents: 13 studies were conducted in Asia, eight in South America, seven in Africa, seven in Europe, and four in North America, which entail diverse economic conditions, societies, and cultures. As discussed by Schonberg and Shaw (2007) , variations in socioeconomic surroundings may alter the effects of individual- and family-level risk factors because of multiplicative effects of risk factors when they accumulate. Also, societies differ along other, broader, cultural dimensions that could also alter proximal mechanisms in the development of antisocial behavior. Major cultural dimensions identified in cross-national studies include individualism-collectivism, uncertainty avoidance, masculinity-femininity, power distance, long- and short-term orientation, and indulgence-restraint ( Hofstede and Hofstede 2001 ); traditionalist values versus secular-rational values, survival values versus self-expression values ( Inglehart, Basanez, and Moreno 1998 ); and tight versus loose cultures ( Gelfand et al. 2011 ). As well as influencing the prevalence rates of risk factors, such as particular parenting practices ( Lansford et al. 2005 ; Bornstein 2012 ), these sociocultural dimensions could interact with proximal processes to produce different risk factor effects ( Lansford 2010 ).

Cultural factors relating to discipline, moral development, and tolerance of deviance may be particularly relevant in influencing individual- and family-level risk factors for antisocial behavior. For example, Rutter (1999) argued that the link between a risk factor and an outcome may depend on whether either variable denotes an “illegitimate” behavior within a cultural context. We examined various constructs whose normative connotations vary across settings. These include, for example, parental corporal punishment, school bullying, gender-based violence against women, parental separation, breast feeding, and premarital sex. Unfortunately, however, the small number of studies in LMICs for each specific variable, and the lack of information about normative expectations in each study context, make it impossible to say whether normative context or other macro-level variables do moderate associations between putative risk factors and outcomes. For the same reason, it is not possible to conclude whether current evidence better supports the hypothesis of “multiplicative effects” of risk factors (stronger effects in contexts of social disadvantage) or the “social push” hypothesis (weaker effects of biological risk factors in disadvantaged environments).

We highlight three main methodological influences that could also give rise to the heterogeneity observed in results across LMICs: assessment instruments, sources of information, and variables adjusted for in analyses. First, when studies use different instruments to assess the same variable, results could differ because of different validity or reliability levels of each instrument. Even when the same instrument is used across studies, variance in item functioning may mean that results differ because of a lack of adequate cross-cultural adaptation of instruments. Second, variations in the informants used to collect data, on both risk factors and outcomes, could cause variations in the findings. For example, parental reports and child self-reports of maltreatment exposure are likely to have very different validity, and both were used in different studies. Third, heterogeneity in effects may also result from different confounding variables adjusted for in each study. Even when considering only bivariate associations, different “confounding structures” across social settings—the degree of social patterning of risk factors—could give rise to different associations.

Therefore, while the amount of evidence on risk factors for antisocial behavior in LMICs is far greater than we had expected before embarking on this work and includes some intriguing individual results, the broad findings, comparing both across and between LMICs and HICs, do not resolve the fundamental issue of the universal validity of causal mechanisms for antisocial behavior. As we discuss below, this should motivate new studies across LMICs, particularly new cross-cultural collaborative research projects, using similar methodologies to test for context effects on risk factor associations.

B. Stability of Aggression in LMICs

In LMIC studies, the average continuity in aggressive behavior when measured with the same informant over a 3-year period was high (adjusted r = 0.75) and almost identical to the extent of continuity found in studies in HICs ( Olweus 1979 ). However, there was also considerable variation in LMIC results that was not explained by differences in child age, the time lag between assessments of aggression, or several country-level characteristics, such as homicide rates or development levels. More recent evidence from HICs also demonstrates considerable heterogeneity in the stability of various types of antisocial behavior ( Derzon 2001 ). This heterogeneity might relate to methodological issues, such as different instruments used, or it might be explained by the causal mechanisms underlying the stability of aggression. Olweus (1979) suggested that stability of aggression is caused by relatively constant individual characteristics or motivational systems. Current theories suggest that these tendencies are due to time-invariant genetic influences, neurocognitive impairments incurred in the first years of life, and stable personality characteristics, such as psychopathy or callous-unemotional traits ( van Goozen et al. 2007 ; Frick and White 2008 ). It is hard to see how such time-constant factors could explain variation in the stability of aggression between contexts. However, “state-dependent” theories might offer more explanation. State-dependent theories propose that stability in aggression is primarily caused by continuity in the social environment. Continuity in social bonds, social learning processes, strains, and negative life events are cited as important causes ( Eisner and Malti 2015 ). Importantly, changes in those same processes could also cause changes in the degree of stability in aggression. Therefore, according to theories of state dependency, different degrees of continuity in social conditions between LMICs could account for different levels of stability in aggression. Future research should test the different possible social mechanisms involved.

C. The Prevalence Paradox: International Rates of Conduct Problems and Serious Violence

Several studies in LMICs demonstrated some continuity in conduct problems through time and an association between conduct problems and later violence. This general continuity in antisocial behavior produces an apparent paradox, considering the fairly constant rates of conduct disorder found around the globe ( Canino et al. 2010 ) in contrast to the enormous cross-country variability in levels of serious violence, with rates of homicide ranging from about one per 100,000 persons in the United Kingdom to about 90 in Honduras ( UN Office on Drugs and Crime 2013 ). How can these contrasting geographic patterns for conduct disorder and violence occur alongside continuity in antisocial behavior, including from conduct problems to violence? Why might countries with higher levels of violence not also have higher levels of child conduct disorder? One possible explanation concerns the aforementioned heterogeneity in levels of stability in antisocial behavior. For example, there might be stronger continuity of antisocial behavior in countries that have higher rates of violence. However, we found no evidence to support this hypothesis: the stability of aggression did not vary systematically with national homicide rates.

A second possible explanation for the puzzling differences in geographic patterns of conduct disorder and violence, alongside individual-level stability in antisocial behavior, concerns the specific subtypes of antisocial behavior being considered. Behavioral stability was strongest for aggression, but it was weaker for conduct problems and weaker still for continuity between childhood conduct problems and youth crime or violence (see also Derzon [2001] and Burt [2012] for similar findings in HICs). Hence, we believe that the quite constant rates of conduct disorders observed across geographic regions are compatible with varying levels of violence, simply because continuity from conduct problems to violence is not strong: childhood conduct problems are far from deterministic of future violence. It should also be considered that although rates of conduct disorder appear similar across cultures ( Canino et al. 2010 ), rates of child behavior problems, as measured by the Child Behavior Checklist, show modest cross-national variability ( Rescorla et al. 2012 ). Therefore, it is also possible that rates of serious violence do covary with levels of child behavior problems measured as symptom scores, but we are not aware of studies that have tested this hypothesis.

D. Early Childhood as a Sensitive Period of Development

The first 1,000 days of life are considered a critical window of opportunity to set children on a path of healthy development by ensuring adequate nutrition, cognitive stimulation, and safe and caring environments ( Engle et al. 2007 ). Early health problems have been hypothesized to influence child behavior via effects on the developing brain, with possible risk factors including prenatal and postnatal malnutrition, tobacco and alcohol use in pregnancy, birth complications, brain injury, and exposure to toxins ( Liu 2011 ). However, in the current review, birth cohort studies in LMICs showed mostly weak or zero effects of several early health factors on antisocial behavior. For instance, one of the most consistent findings was the absence of an association between low birth weight and antisocial behavior—replicated across six studies and producing a pooled effect size of zero. Weak or null findings were also found for premature birth, birth complications, lead and mercury exposure, breast feeding, and zinc consumption. Results for the association between malnutrition and antisocial behavior were mixed, and although several studies reported positive associations between maternal smoking in pregnancy and antisocial behavior, the causal status of these findings is unclear, given the lack of genetically sensitive research designs in LMIC studies. More robust studies of maternal smoking in pregnancy have revealed null or weak effects on antisocial behavior in HICs ( Jaffee, Strait, and Odgers 2012 ). Hence, the general conclusion must be that the evidence to date generally shows weak or no influence of early life health factors in the development of antisocial behavior in LMICs.

Weak effects of early health factors have also been reported in several longitudinal studies in HICs. For example, low birth weight was not an independent predictor of conduct problems or crime in a British birth cohort ( Murray et al. 2010 ). However, the consistent null results in LMIC studies are striking, especially given that many LMICs have relatively poor neonatal health care provision ( Lawn, Cousens, and Zupan 2005 ). The null and weak findings in LMICs may have implications for developmental theories that hypothesize particularly strong effects of early health factors in the context of high social risk, for example, Moffitt’s (1993) theory of life course persistent antisocial behavior. However, to test such developmental theories adequately, future LMIC studies need to use repeated measures to distinguish trajectories of antisocial behavior according to age of onset and persistence through the life course. Also needed are studies of possible interactions between early health variables and social risk factors within LMIC settings, which are proposed as key processes in causing early onset and persistent antisocial behavior ( Moffitt 1993 ).

E. Parenting Influences

Weak and null findings on early health factors do not imply that early childhood is not a sensitive period, as other types of early influences might be more important for the development of antisocial behavior. In particular, several LMIC studies found associations between parenting practices measured in preschool years and subsequent conduct problems. Authoritarian parenting practices, such as coercive discipline, were positively associated with child antisocial behavior, whereas authoritative parenting practices, combining warmth and clear limit setting, predicted fewer behavior problems. However, these results were not all consistent, effect sizes were generally modest, and studies lacked more sophisticated designs for ruling out reciprocal causation and for disentangling the effects of parental behavior from other confounding variables.

Overall, the findings are at least moderately consistent with the notion that parenting practices are predictive of conduct problems and violence in LMICs, just as they are in HICs. It should be noted that effect sizes are modest in HICs, around r = 0.2 ( Hoeve et al. 2009 ), as well as in our review. In particular, our findings are important in showing that in countries such as China, where authoritarian parenting values are thought to be more normative than in the West ( Chao 1994 ), such parenting styles nevertheless are still associated with higher levels of conduct problems, just as they are in “Western” countries, including in the studies we examined in Poland and Russia. Similarly, positive, “authoritative” styles of parenting tended to be associated with lower levels of child conduct problems, just as they are in HICs, albeit with more inconsistent findings across LMIC studies.

Although there is a lack of clear-cut evidence for the causal role of parenting in the LMIC studies, confidence in the causal role of parenting as an intervention strategy comes from extensive evidence from randomized trials, both in the field and in lab conditions in HICs ( Piquero et al. 2009 , 2016 ; Leijten et al. 2015 ). Although the majority of parenting field trials are in HICs, an increasing number have been conducted in LMICs ( Mejia, Calam, and Sanders 2012 ; Knerr, Gardner, and Cluver 2013 ; Leijten et al. 2016 ), and most of these trials show improvements in positive parenting and in child problem behavior, in a range of age groups from toddlerhood through teenage years. Furthermore, findings from systematic reviews of interventions are broadly consistent with our risk factor findings, suggesting that cultural variation in parenting need not necessarily be a barrier to transporting such programs across countries, cultures, and service contexts. Thus, effect sizes were equivalent for parenting interventions developed within a particular country, compared to those imported from abroad ( Leijten et al. 2016 ). A second review suggested that effectiveness of parenting interventions when transported from one country to another was not dependent on the degree of similarity between countries in cultural values or child and family policy regimes ( Gardner, Montgomery, and Knerr 2015 ).

F. Striking Null Findings in LMICs

Early health factors had only weak associations with antisocial behavior in LMICs. Perhaps more surprisingly, several other potential risk factors also failed to have positive associations with antisocial behavior. For example, poor educational performance, maltreatment, large family size, low maternal education, and family poverty had notably weak or null associations. However, it would be wrong to assume that evidence in HICs provides a completely different, consistent set of positive results. With respect to some risk factors, null results in LMIC studies may reflect inconsistent evidence in the global literature. For example, the failed replication of an MAOA-abuse interaction in predicting conduct problems in a Brazilian study ( Kieling et al. 2013 ) may reflect generally inconsistent results rather than anything specific about the Brazilian context ( Duncan and Keller 2011 ).

However, some of our null findings were surprising, particularly those concerning the lack of effects of maltreatment on conduct problems or violence; albeit only three studies examined this topic, and so only tentative conclusions are warranted. There are several possible explanations for the differences between generally positive findings in HICs and the null findings from LMICs with regard to the association between child maltreatment and later antisocial behavior. First, there may be true differences. One possible explanation might be that harsh physical punishment and child maltreatment are more widespread and considered more normative in LMICs. This might lead more children to believe that harsh punishment is used as part of a planned strategy that is in their best interests, which might reduce some of its adverse effects ( Lansford 2010 ; Vittrup and Holden 2010 ). Second, it is possible that the larger effects found in HICs (see, e.g., Wilson, Stover, and Berkowitz [2009] for the most comparable results in HICs) are due to the longer time periods between measures of exposure and outcome in studies in HICs and possible “sleeper effects”—whereby effects that are weak or undetectable at first strengthen and become measurable later. The time lags in the eight prospective studies in HICs included in the review by Wilson et al. (2009) range between 3 and 24 years, with many in the region of 10 years. The equivalent time lags in the three studies in our review were 3 years ( de Assis et al. 2013 ), 1 year ( Waller, Gardner, and Cluver 2014 ), and 7 years ( Thaler 2011 )—a mean of 3.7. There is some evidence for “sleeper effects” in relation to corporal punishment and harsh parenting ( Tanner-Smith, Wilson, and Lipsey 2013 ; Coley, Kull, and Carrano 2014 ), child sexual abuse ( Putnam 2003 ; Smith, Ireland, and Thornberry 2005 ; Trickett, Noll, and Putnam 2011 ), and exposure to intimate partner violence ( Vu et al. 2016 ). Third, it is also possible that differences are due to methodological factors, such as differences in types of child maltreatment considered as predictors (physical, sexual, psychological, neglect) or sources of reports (self-report, parental reports, administrative records).

G. Strengths and Limitations

We are not aware of any prior review that has synthesized, narratively or meta-analytically, evidence on longitudinal predictors of antisocial behavior across LMICs. This review, we believe, has several important strengths, including the enormous search efforts that went into locating studies in LMICs in multiple languages, the large number of eligible studies retrieved, meta-analytic synthesis of many risk factors, and comparisons made with findings from HICs. However, there are also important reasons to treat our findings with caution.

Importantly, almost none of the primary studies used methods that allow for strong causal inference. Apart from a few studies that used randomized trials to target specific risk factors or a single study that used twins to eliminate genetic confounding, nearly all studies relied on regression-based models to adjust for a limited number of possible confounding factors. An increasing range of advanced study designs and analytic methods can help improve causal inference about risk factors ( Jaffee, Strait, and Odgers 2012 ), but these have been rarely used in studies in LMICs. In the context of regression-based studies, it was often unclear whether the covariates that were included in multivariate models really represented confounding factors that should be controlled for when estimating causal effects, or whether they actually measured mediating mechanisms on the causal pathway between the risk factor and behavioral outcome. Adjusting for mediating mechanisms can bias estimates of risk factor total effects downward ( Schisterman, Cole, and Platt 2009 ), and considerable care is needed in selecting variables for inclusion in multivariate models in future research. A related point is that researchers sometimes included earlier measures of the outcome variable in multivariate models. By doing this, the coefficient for the risk factor will represent its association with change in the outcome through time, which may not be the objective of the study. These considerations raise doubts about how to interpret some individual study findings. However, our meta-analyses excluded such studies when calculating pooled effect sizes. Most prior meta-analyses of risk factors in HICs ( Hawkins et al. 1998 ; Lipsey and Derzon 1998 ; Derzon 2010 ; Tanner-Smith, Wilson, and Lipsey 2013 ) have synthesized only bivariate associations, and our meta-analyses also mostly synthesized only bivariate associations, although we were able to pool some covariate-adjusted effect sizes.

As in HICs, the longitudinal studies in LMICs used many different sampling methods, follow-up periods, informants, and measures. Hence, heterogeneity in results seems as likely to reflect methodological variations as possible true differences in effects of predictors across different LMIC contexts. Unfortunately, relatively few primary studies were available for each risk factor considered; hence, it was rarely possible to investigate the population characteristics or study features that might explain any observed heterogeneity.

Although we included studies from 14 different LMICs, the vast majority came from Brazil and China, two powerful countries in their respective regions, but with vastly different cultures and sociopolitical structures. Such large, medium-income countries also dominate in other areas of research in LMICs; for example, a systematic review on predictors of physical activity in LMICs found most evidence in Brazil and China ( Sallis et al. 2016 ). Notably, apart from studies in three countries (China, the Philippines, and South Africa), there was no other evidence available from Asia or Africa. Also, although violence is a critical issue affecting many LMICs, of the 39 studies reviewed here, only seven provided data on predictors of violence. Therefore, the evidence base is particularly weak for drawing conclusions about predictors of violence, despite the major impact that it has on many LMICs.

A further limitation in the evidence we reviewed concerns the high likelihood of reporting and publication bias in observational studies, which may explain some of the heterogeneity and failure to replicate across studies, in both HICs and LMICs. Outcome reporting bias has been well documented in randomized control trials ( Smyth et al. 2011 ), and it is likely to be a greater source of bias in observational studies, where prespecified protocols are rarer than for trials, analytic strategies are more varied, and data may be available for many investigators to mine. Where weak associations were found in individual studies, these might be accounted for by methodological limitations, in terms of low-quality measures or high rates of attrition, for example. However, some weak and null findings were replicated across multiple studies with different methodologies, increasing confidence that those variables really were not associated with antisocial behavior.

H. Implications for Research

Some key issues confronting LMIC populations have not received adequate research attention in relation to the development of antisocial behavior. Experiences of civil conflict and migration are major issues that require study in LMICs. Other severe traumas commonly experienced in LMICs, such as female genital mutilation, being orphaned by AIDS, and stresses associated with child labor, are important areas for future research. Research with a resilience framework would be particularly valuable to consider ways in which individuals may cope with such traumas in LMIC contexts. Another research priority is to develop understanding of how macro-level influences that are known to covary with violence, such as illegitimate state institutions and national levels of income-inequality ( Nivette 2011 ; Nivette and Eisner 2013 ), interact with individual development to cause antisocial behavior in LMICs. New studies should increase construct and internal validity by using multiple informants, well-validated and culturally adapted measures, and appropriate designs to increase understanding of causal mechanisms, such as sibling and twin studies, natural experiments, and analytic approaches such as propensity scores, analysis of within-individual change, and instrumental variables.

As new studies are conducted and additional results become available from more diverse settings across LMICs, it will become possible to assess the robustness of the current findings and identify causes of heterogeneity between study results. Understanding of the processes involved in the development of conduct problems, aggression, and delinquency across different cultures could be substantially enhanced from comparative longitudinal studies. These would be studies that are based on comparable sampling strategies, measurement tools, and analytic approaches in two or more populations with different cultural, economic, or social characteristics. Such studies would allow research to rule out many of the possible methodological reasons for heterogeneity between studies and provide a much better basis for understanding the extent to which there is cross-cultural variation in mechanisms leading to antisocial behavior. David Farrington (2001) laid out a program for comparative cross-national longitudinal surveys in Europe, which would investigate to what extent criminal careers, risk factors, and intervention effects are the same across participating countries. He recommends correlating the strength of risk factor associations across sites (see, e.g., Farrington et al. 2015 ). Even more ambitiously, a similar research program could be advanced across LMICs. An existing consortium of birth cohort studies in Brazil, Guatemala, India, the Philippines, and South Africa coordinates research on health, nutrition, and human capital in those settings ( Richter et al. 2012 ). New projects could compare influences on the development of antisocial behavior and violence across LMICs.

A series of measures could help to improve comparability of developmental risk factor research across LMICs and human societies more generally. First, it seems important that studies conducted in different cultures use comparable and cross-culturally validated instruments to measure core constructs such as parenting, self-control, or aggression. Organizations such as the UNICEF Office of Research or the World Health Organization can help to promote good practice through recommendations. Second, developmental studies should be encouraged to publish research protocols similar to protocols for experimental studies. This would help to improve understanding of which putative risk factors were measured in a study and to what extent published results are based on fishing expeditions or on hypothesis-driven deductive reasoning.

Future syntheses of research on antisocial behavior should take a global view. Given the striking restriction of previous reviews to literature from HICs, we aimed to synthesize the existing evidence in LMICs. However, future reviews could encompass all world regions, increasing both the statistical power for quantitative syntheses of results and the potential to examine methodological and substantive factors that explain heterogeneity in findings around the globe.

V. Conclusion

A large body of longitudinal research on antisocial behavior from LMICs has been excluded from most reviews on this topic. The most robust findings that emerge from these studies are that conduct problems tend to persist; dimensions of comorbid psychopathology such as low self-control, hyperactivity, and sensation seeking are also associated with antisocial behavior; many risk factors appear to have roughly the same average effects as when studied in HICs; and some early health factors have weak or null effects. The time is ripe for a new generation of collaborative research, with carefully coordinated methods, to identify global and context-specific mechanisms involved in the development of antisocial behaviors.

Acknowledgments

We thank Tomas Allen and Isla Kuhn for vital help in developing the search strategy and Antonia Concha Errazuriz, Bruno Dalponte, Dong Yiqun, Franziska Mager, Lana Ghuneim, Lana Yoo, Lídia Maria de Oliveira Morais, Maria Paula Godoy, Simón Escoffier Martínez, Sze Long Mui, Yan Zhang, Zehang Chen, Li Jiawei, Ma Li, Li Tianqing, Wei Junfan, and Zheng Anqing for searches, screening, and translation in languages other than English. We are especially grateful to Adrian Raine, Christiane Duarte, Jie Chen and Jianxin Zhang, Mark Boyes, Phillip Davidson, and Edwin Wijngaarden, who provided additional data from and information about their studies. This work was funded by grants to Joseph Murray from the Wellcome Trust (089963/Z/09/Z) and the Bernard van Leer Foundation (222-2014-010).

1 Studies included were Frączek (1986) , Botha and Mels (1990) , Chen, Rubin, and Li (1997) , Raine, Venables, and Mednick (1997) , Zhang et al. (2003) , Chen, He, and Li (2004) , de la Barra, Toledo, and Rodríguez (2005) , Anselmi et al. (2008) , Duarte et al. (2008) , Zhou, Main, and Wang (2010) , Zhu, Yan, and Li (2011) , Chen et al. (2012) , Hou et al. (2013) , and Zhang (2013) .

2 Attenuation refers to the systematic reduction in continuity coefficients caused by measurement error. Disattenuated correlation coefficients are estimated using the following equation: r d = r x y / ( r x x × r y y ) , where r d is the disattenuated correlation coefficient, r xy is the observed correlation between x and y , and r xx and r yy are the reliability coefficients for x and y . Following Olweus (1979) , if incomplete data were available on reliability coefficients, values were estimated from similar studies, using higher values wherever appropriate, because using low-reliability coefficients can artificially inflate estimates of the disattenuated correlation.

3 This was calculated from the regression model estimated by Olweus: y = 0.78 − (0.18 × x ), where y is the disattenuated correlation coefficient and x is the interval between measures in years (in this case 3.0).

4 These meta-analyses were conducted on the basis of uncorrected correlation coefficients, rather than disattenuated ones, to increase comparability with other results in the review. For other risk factors, reliability information was not available to calculate disattenuated associations.

Contributor Information

Joseph Murray, Postgraduate Program in Epidemiology, Federal University of Pelotas, Brazil.

Yulia Shenderovich, Institute of Criminology, Cambridge University.

Frances Gardner, Department of Social Policy and Intervention, Oxford University.

Christopher Mikton, Department of Health and Social Sciences, University of the West of England.

James H. Derzon, Center for Advanced Methods Development, Research Triangle Institute.

Jianghong Liu, School of Nursing and Perelman School of Medicine, University of Pennsylvania.

Manuel Eisner, Institute of Criminology, Cambridge University.

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There is a general increase in anti-social behaviours and lack of respect for others. What are the causes and solutions?

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Some people believe that children nowadays have too much freedom. Other believe that children are sometimes protected too much by their parents. Which of these viewpoints do you agree with?

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Understanding Anti-social Behavior

Jane Doe Criminology 178 Professor John Doe 3 April 2018

Anti-social Behavior

The Crime and Disorder Act defines anti-social behavior as “…acting in a manner that caused or was likely to cause harassment, alarm or distress to one or more persons not of the same household as [the defendant]” (Code of Practice for Youth Conditional Cautions). According to Andrews et al., “people understand anti-social behavior differently based on a series of factors including time, context, location, community tolerance and quality of life expectations” (34). As a result what may be regarded as an anti-social behavior to one person may be seen as an unacceptable behavior to another person. The understanding of anti-social behavior is “based on the individual perceptions and may include a wide range of behaviors” (Harradine et al). Anti-social behavior causes damage to many fragile communities and if unchecked it may lead to decline of neighborhoods with people moving from their homes to other places which they regard safe.

Anti-social behavior damages the quality of life of the most vulnerable people through the infliction of fear and victimization. It also leads to individuals, families, communities, schools, local authorities, businesses and the governments to incur costs not always planned for (Rubin at al.). Hence there is a need of devising different methods of tackling anti-social behavior.

In my area, Leeds, the levels of youth crime are high with very high rates of youths in police custody every other given day. Most youths especially in the ages between 10 years and 24 years of age engage in anti-social behavior which most people are always offended by and do not take lightly (Time for a Fresh Start).

Some of these anti-social behaviors in my area include: rowdy and nuisance behavior by the youth, playing of loud music both during the day and late night hours, vandalism, graffiti and fly posting, taking over of public spaces by gangs, drug dealing and drug abuse, anti-social drinking, misuse of fireworks, dumping of rubbish and all manners of waste among many other behaviors.

Most residents in the Leeds neighborhood have the feelings of being insecure and have even contemplated shifting to other places where they can feel secure and have a peace of mind if the situation is not rectified. In fact some of the residents in my area have left the neighborhood as a result of “taking it no more.” The quality of life has deteriorated and the old people together with women being most vulnerable to these anti-social behavior.

1. The Factors of Anti-social Behaviour

These youth crime incidents in my neighborhood can be attributed to various factors which include family conflicts, mental illness, availability of drugs and alcohol, unemployment and others (Time for a Fresh Start).

Family conflicts. The ever rising conflicts among families especially those involving parents and children have led to most of these children to engage in these crimes. As a result of these conflicts the youths tend to involve in anti-social behavior as a way of getting out of their frustrations and getting out of that situation.

Mental illness. According to Committee of Public Accounts, antisocial behavior can be a symptom of mental illness. This is evidenced by the increase of poor mental health in children and the youth over the years particularly among the socially disadvantaged (Tackling Anti–Social Behaviour). In my neighborhood it is estimated that 30% of the anti-social behavior involve someone with a mental health problem either as a perpetrator or the victim.

Availability of drugs and alcohol. Most of the young people in my neighborhood involve in drug abuse and alcoholism.

Cannabis has been found to be the most popular among the youths and its hallucinogenic effects which sometimes lead to paranoia have always led to anti-social behavior. Excessive drinking has also led to some anti-social behavior including rowdiness and loud music.

Poor parental discipline and supervision. Most parents with their busy daily schedules, have not taken the responsibility of ensuring the instilling of discipline and to their children and the supervision of their behaviors. This is more evident in Leeds where most parents have allowed their children to have the freedom of doing their own things without their involvement. The cases of poor quality parenting are seen as a precursor of early onset conduct behaviors.

Community disorganization and neglect. The community around have always known the problems facing the youth and the issues behind these anti-social behaviors but have continually turned a blind eye. This has made the cases of youth crimes to be more rampant in this area.

Unemployment. Some of the youth in this area have nothing to do and hence because of idleness they engage in behaviors which many regard as anti-social. The playing of loud music and burglary are some of the anti-social behaviors as a result of unemployment, low income or homelessness.

The lack of commitment in schools by the youth or the subjection to bullying by some of these youth has also led to youth crimes in my neighborhood. Also cases of low achievement in school coupled with school disorganization have also led to these anti-social behaviors.

The exposure to violence at tender ages has also led to the increased number of youth crimes in my area. Some of these youths have been exposed to criminal gangs that have taught them how to carry out these violent acts. They hence grow up being criminals.

2. Role of the Community in Supporting Youths and Preventing Youth Crime

Anti-social behaviors are highly localized because of the nature of anti-social behaviors. Some of the anti-social behaviors like for example graffiti may be a problem in one community whereas in another it is not hence the need to identify these problems from a community perspective. Different communities’ experience different anti-social behaviors. There is the need of involving communities in identifying which problems are the most important and need speedy resolutions. The community should also be consulted in coming up with long lasting solutions to the crime problem and programs aimed at supporting youths and preventing them from crime.

There is the need of the government and local authorities to develop partnerships with communities which would be aimed at developing safety strategies, carrying out of audits of anti-social behavior so as to know which problems to tackle, setting baselines for improvement, setting of clear targets, adjusting the implementations employed and the monitoring and evaluation of their work. The Anti-social behavior toolkit by the Government of United Kingdom is an example of a program by which communities can be involved in partnerships aimed at reducing crime and disorder. The toolkit offers practical examples by which the communities can be involved in identifying the local problems associated with anti-social behavior, determination of the local actions to be implemented, Implementation of the proposed local actions and assessment of the local action employed to reduce crimes and disorder.

Though the Crime and Disorder partnerships with communities, anti-social behaviors may be prevented through the putting in place of measures to create a physical and social environment where anti-social behaviors and violent acts are less likely to happen.

Community safety partnerships should be encouraged to set local standards and find local solutions to these problems in their communities.

The standards to be set using these partnerships should be aimed at reducing the number of anti-social behavior incidences and reducing their perceptions. Community safety partnerships can also be included in the recording the incidences of anti-social behavior cases and actions taken on perpetrators, provision of information to residents about anti- social behaviors and the actions taken, facilitation of discussions between community members about their feelings about these behaviors and provision of a right to the residents of complaining if the authorities are not putting efficient measures to tackle a given problem in the community (Rubin et al.).

Communities can also play a key role in the support of the youth who are either victims or witnesses of these anti-social behaviors. This support can be done through counseling and therapy to ensure that they are not affected by either what they saw or experienced. Some of the victims may find it hard to cope with what they experienced and hence this may change their perceptions towards someone or something which may have negative implications and hence the community can come in handy in ensuring resolutions to these differences.

These community partnerships can also work with the authorities in ensuring that cases of drug abuse and alcoholism are reported. The youth can also be advised on better choices in life and engaged in constructive activities like community work. The partnership between communities and authorities if implemented well may play an integral role in ensuring the improvement of the quality of life in a community and the reduction in the cases of anti-social behaviors.

3. The Different Forms of Anti-Social Behavior

Homophobia. According to The report of the Independent Commission on Youth Crime and Antisocial Behavior, 34% of men and 25% of women have experienced violence because of their sexuality (Time for a Fresh Start).

This includes gay men, lesbians and bisexuals. This violence has been in the form of verbal attacks, assault by weapons, blackmail, vandalism, hate mail, graffiti and other forms of homophobic attacks.

Racism. The Independent Commission on Youth Crime and Antisocial Behavior links anti-social behavior to racism (Time for a Fresh Start). In the year 1988 the Crime and Disorder act was amended to include maximum penalties where the circumstances of an offence were racially aggravated. These included vandalism, wounding, harassment and common assault (Code of Practice for Youth Conditional Cautions).

Drug and Alcohol Misuse. The misuse of drugs and excessive alcohol consumption is a significant contributor in anti-social behavior. Alcohol is a contributor in a number of crimes like for example about 44% of all victims claim that the assailant was drunk (Time for a Fresh Start). Alcohol or drug related anti-social behavior may take the form of violence, stabbing, verbal abuse, vandalism, playing of loud music among many others.

According to Harradine et al., “anti-social behavior destroys the quality of life to those at the receiving end”(victims) (Harradine et al.). Most of the victims usually experience mental problems six months after the event, just showing that the effects of victimization can continue long afterwards. A victim would continue suffering in as long as the anti-social behavior continues and this may lead to long-term damages. The people usually worst affected by anti-social behaviors include the poorest individuals in the community, ethnic minorities and homosexuals, young people and other vulnerable persons including the old, disabled and women.

The wider communities suffer a lot as a result of anti-social related behavior and this mainly involves incurring high financial costs. Many families, landlords and the community as a whole incur costs related to the prevention and response to anti-social behaviors. The financial costs are usually high as it is estimated anti-social behavior causes the taxpayer 3.4 billion pounds per year (Rubin et al.).

Works Cited

Andrews, Donald A., and James Bonta. The Psychology of Criminal Conduct. 5th ed., Lexis Nexis/Anderson Pub., 2010.

Harradine, Sally, Jenny Kodz, Francesca Lemetti, and Bethan Jones. Defining and Measuring Anti-Social Behavior . 2004, assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/116655/dpr26.pdf. Accessed 21 Nov. 2017.

House of Commons of the United Kingdom, Committee of Public Accounts. Tackling Anti–Social Behaviour . 24 July 2007, publications.parliament.uk/pa/cm200607/cmselect/cmpubacc/246/246.pdf. Accessed 17 Nov. 2017.

Rubin, Jennifer, Lila Rabinovich, Michael Hallsworth, and Edward Nason. Interventions to Reduce Anti-Social Behavior and Crime: A Review of Effectiveness and Costs. RAND Corporation, 2006. www.rand.org/content/dam/rand/pubs/technical_reports/2006/RAND_TR448.pdf. Accessed 15 Nov. 2017.

The Police Foundation, The Independent Commission on Youth Crime and Antisocial Behavior. Time for a Fresh Start: The report of the Independent Commission on Youth Crime and Antisocial Behavior . 2008, www.police-foundation.org.uk/uploads/catalogerfiles/independent-commission-on-youth-crime-and-antisocial-behaviour/fresh_start.pdf. Accessed 21 Nov. 2017.

UK Ministry of Justice. Code of Practice for Youth Conditional Cautions: Crime & Disorder Act 1998 (as amended by the Criminal Justice & Immigration Act 2008 and the Legal Aid, Sentencing and Punishment of Offenders Act 2012). Mar. 2013, assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/243443/9780108512179.pdf. Accessed 17 Nov. 2017.

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ESSAY ON GENERAL INCREASE IN ANTI-SOCIAL BEHAVIOUR AND LACK OF RESPECT FOR OTHERS, WHAT ARE THE CAUSE AND SOLUTION.

IELTS essay ESSAY ON GENERAL INCREASE IN ANTI-SOCIAL BEHAVIOUR AND LACK OF RESPECT FOR OTHERS, WHAT ARE THE CAUSE AND SOLUTION.

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