research proposal bullying

Preventing Bullying Through Science, Policy, and Practice (2016)

Chapter: 1 introduction, 1 introduction.

Bullying, long tolerated by many as a rite of passage into adulthood, is now recognized as a major and preventable public health problem, one that can have long-lasting consequences ( McDougall and Vaillancourt, 2015 ; Wolke and Lereya, 2015 ). Those consequences—for those who are bullied, for the perpetrators of bullying, and for witnesses who are present during a bullying event—include poor school performance, anxiety, depression, and future delinquent and aggressive behavior. Federal, state, and local governments have responded by adopting laws and implementing programs to prevent bullying and deal with its consequences. However, many of these responses have been undertaken with little attention to what is known about bullying and its effects. Even the definition of bullying varies among both researchers and lawmakers, though it generally includes physical and verbal behavior, behavior leading to social isolation, and behavior that uses digital communications technology (cyberbullying). This report adopts the term “bullying behavior,” which is frequently used in the research field, to cover all of these behaviors.

Bullying behavior is evident as early as preschool, although it peaks during the middle school years ( Currie et al., 2012 ; Vaillancourt et al., 2010 ). It can occur in diverse social settings, including classrooms, school gyms and cafeterias, on school buses, and online. Bullying behavior affects not only the children and youth who are bullied, who bully, and who are both bullied and bully others but also bystanders to bullying incidents. Given the myriad situations in which bullying can occur and the many people who may be involved, identifying effective prevention programs and policies is challenging, and it is unlikely that any one approach will be ap-

propriate in all situations. Commonly used bullying prevention approaches include policies regarding acceptable behavior in schools and behavioral interventions to promote positive cultural norms.

STUDY CHARGE

Recognizing that bullying behavior is a major public health problem that demands the concerted and coordinated time and attention of parents, educators and school administrators, health care providers, policy makers, families, and others concerned with the care of children, a group of federal agencies and private foundations asked the National Academies of Sciences, Engineering, and Medicine to undertake a study of what is known and what needs to be known to further the field of preventing bullying behavior. The Committee on the Biological and Psychosocial Effects of Peer Victimization:

Lessons for Bullying Prevention was created to carry out this task under the Academies’ Board on Children, Youth, and Families and the Committee on Law and Justice. The study received financial support from the Centers for Disease Control and Prevention (CDC), the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the Health Resources and Services Administration, the Highmark Foundation, the National Institute of Justice, the Robert Wood Johnson Foundation, Semi J. and Ruth W. Begun Foundation, and the Substance Abuse and Mental Health Services Administration. The full statement of task for the committee is presented in Box 1-1 .

Although the committee acknowledges the importance of this topic as it pertains to all children in the United States and in U.S. territories, this report focuses on the 50 states and the District of Columbia. Also, while the committee acknowledges that bullying behavior occurs in the school

environment for youth in foster care, in juvenile justice facilities, and in other residential treatment facilities, this report does not address bullying behavior in those environments because it is beyond the study charge.

CONTEXT FOR THE STUDY

This section of the report highlights relevant work in the field and, later in the chapter under “The Committee’s Approach,” presents the conceptual framework and corresponding definitions of terms that the committee has adopted.

Historical Context

Bullying behavior was first characterized in the scientific literature as part of the childhood experience more than 100 years ago in “Teasing and Bullying,” published in the Pedagogical Seminary ( Burk, 1897 ). The author described bullying behavior, attempted to delineate causes and cures for the tormenting of others, and called for additional research ( Koo, 2007 ). Nearly a century later, Dan Olweus, a Swedish research professor of psychology in Norway, conducted an intensive study on bullying ( Olweus, 1978 ). The efforts of Olweus brought awareness to the issue and motivated other professionals to conduct their own research, thereby expanding and contributing to knowledge of bullying behavior. Since Olweus’s early work, research on bullying has steadily increased (see Farrington and Ttofi, 2009 ; Hymel and Swearer, 2015 ).

Over the past few decades, venues where bullying behavior occurs have expanded with the advent of the Internet, chat rooms, instant messaging, social media, and other forms of digital electronic communication. These modes of communication have provided a new communal avenue for bullying. While the media reports linking bullying to suicide suggest a causal relationship, the available research suggests that there are often multiple factors that contribute to a youth’s suicide-related ideology and behavior. Several studies, however, have demonstrated an association between bullying involvement and suicide-related ideology and behavior (see, e.g., Holt et al., 2015 ; Kim and Leventhal, 2008 ; Sourander, 2010 ; van Geel et al., 2014 ).

In 2013, the Health Resources and Services Administration of the U.S. Department of Health and Human Services requested that the Institute of Medicine 1 and the National Research Council convene an ad hoc planning committee to plan and conduct a 2-day public workshop to highlight relevant information and knowledge that could inform a multidisciplinary

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1 Prior to 2015, the National Academy of Medicine was known as the Institute of Medicine.

road map on next steps for the field of bullying prevention. Content areas that were explored during the April 2014 workshop included the identification of conceptual models and interventions that have proven effective in decreasing bullying and the antecedents to bullying while increasing protective factors that mitigate the negative health impact of bullying. The discussions highlighted the need for a better understanding of the effectiveness of program interventions in realistic settings; the importance of understanding what works for whom and under what circumstances, as well as the influence of different mediators (i.e., what accounts for associations between variables) and moderators (i.e., what affects the direction or strength of associations between variables) in bullying prevention efforts; and the need for coordination among agencies to prevent and respond to bullying. The workshop summary ( Institute of Medicine and National Research Council, 2014c ) informs this committee’s work.

Federal Efforts to Address Bullying and Related Topics

Currently, there is no comprehensive federal statute that explicitly prohibits bullying among children and adolescents, including cyberbullying. However, in the wake of the growing concerns surrounding the implications of bullying, several federal initiatives do address bullying among children and adolescents, and although some of them do not primarily focus on bullying, they permit some funds to be used for bullying prevention purposes.

The earliest federal initiative was in 1999, when three agencies collaborated to establish the Safe Schools/Healthy Students initiative in response to a series of deadly school shootings in the late 1990s. The program is administered by the U.S. Departments of Education, Health and Human Services, and Justice to prevent youth violence and promote the healthy development of youth. It is jointly funded by the Department of Education and by the Department of Health and Human Services’ Substance Abuse and Mental Health Services Administration. The program has provided grantees with both the opportunity to benefit from collaboration and the tools to sustain it through deliberate planning, more cost-effective service delivery, and a broader funding base ( Substance Abuse and Mental Health Services Administration, 2015 ).

The next major effort was in 2010, when the Department of Education awarded $38.8 million in grants under the Safe and Supportive Schools (S3) Program to 11 states to support statewide measurement of conditions for learning and targeted programmatic interventions to improve conditions for learning, in order to help schools improve safety and reduce substance use. The S3 Program was administered by the Safe and Supportive Schools Group, which also administered the Safe and Drug-Free Schools and Communities Act State and Local Grants Program, authorized by the

1994 Elementary and Secondary Education Act. 2 It was one of several programs related to developing and maintaining safe, disciplined, and drug-free schools. In addition to the S3 grants program, the group administered a number of interagency agreements with a focus on (but not limited to) bullying, school recovery research, data collection, and drug and violence prevention activities ( U.S. Department of Education, 2015 ).

A collaborative effort among the U.S. Departments of Agriculture, Defense, Education, Health and Human Services, Interior, and Justice; the Federal Trade Commission; and the White House Initiative on Asian Americans and Pacific Islanders created the Federal Partners in Bullying Prevention (FPBP) Steering Committee. Led by the U.S. Department of Education, the FPBP works to coordinate policy, research, and communications on bullying topics. The FPBP Website provides extensive resources on bullying behavior, including information on what bullying is, its risk factors, its warning signs, and its effects. 3 The FPBP Steering Committee also plans to provide details on how to get help for those who have been bullied. It also was involved in creating the “Be More than a Bystander” Public Service Announcement campaign with the Ad Council to engage students in bullying prevention. To improve school climate and reduce rates of bullying nationwide, FPBP has sponsored four bullying prevention summits attended by education practitioners, policy makers, researchers, and federal officials.

In 2014, the National Institute of Justice—the scientific research arm of the U.S. Department of Justice—launched the Comprehensive School Safety Initiative with a congressional appropriation of $75 million. The funds are to be used for rigorous research to produce practical knowledge that can improve the safety of schools and students, including bullying prevention. The initiative is carried out through partnerships among researchers, educators, and other stakeholders, including law enforcement, behavioral and mental health professionals, courts, and other justice system professionals ( National Institute of Justice, 2015 ).

In 2015, the Every Student Succeeds Act was signed by President Obama, reauthorizing the 50-year-old Elementary and Secondary Education Act, which is committed to providing equal opportunities for all students. Although bullying is neither defined nor prohibited in this act, it is explicitly mentioned in regard to applicability of safe school funding, which it had not been in previous iterations of the Elementary and Secondary Education Act.

The above are examples of federal initiatives aimed at promoting the

2 The Safe and Drug-Free Schools and Communities Act was included as Title IV, Part A, of the 1994 Elementary and Secondary Education Act. See http://www.ojjdp.gov/pubs/gun_violence/sect08-i.html [October 2015].

3 For details, see http://www.stopbullying.gov/ [October 2015].

healthy development of youth, improving the safety of schools and students, and reducing rates of bullying behavior. There are several other federal initiatives that address student bullying directly or allow funds to be used for bullying prevention activities.

Definitional Context

The terms “bullying,” “harassment,” and “peer victimization” have been used in the scientific literature to refer to behavior that is aggressive, is carried out repeatedly and over time, and occurs in an interpersonal relationship where a power imbalance exists ( Eisenberg and Aalsma, 2005 ). Although some of these terms have been used interchangeably in the literature, peer victimization is targeted aggressive behavior of one child against another that causes physical, emotional, social, or psychological harm. While conflict and bullying among siblings are important in their own right ( Tanrikulu and Campbell, 2015 ), this area falls outside of the scope of the committee’s charge. Sibling conflict and aggression falls under the broader concept of interpersonal aggression, which includes dating violence, sexual assault, and sibling violence, in addition to bullying as defined for this report. Olweus (1993) noted that bullying, unlike other forms of peer victimization where the children involved are equally matched, involves a power imbalance between the perpetrator and the target, where the target has difficulty defending him or herself and feels helpless against the aggressor. This power imbalance is typically considered a defining feature of bullying, which distinguishes this particular form of aggression from other forms, and is typically repeated in multiple bullying incidents involving the same individuals over time ( Olweus, 1993 ).

Bullying and violence are subcategories of aggressive behavior that overlap ( Olweus, 1996 ). There are situations in which violence is used in the context of bullying. However, not all forms of bullying (e.g., rumor spreading) involve violent behavior. The committee also acknowledges that perspective about intentions can matter and that in many situations, there may be at least two plausible perceptions involved in the bullying behavior.

A number of factors may influence one’s perception of the term “bullying” ( Smith and Monks, 2008 ). Children and adolescents’ understanding of the term “bullying” may be subject to cultural interpretations or translations of the term ( Hopkins et al., 2013 ). Studies have also shown that influences on children’s understanding of bullying include the child’s experiences as he or she matures and whether the child witnesses the bullying behavior of others ( Hellström et al., 2015 ; Monks and Smith, 2006 ; Smith and Monks, 2008 ).

In 2010, the FPBP Steering Committee convened its first summit, which brought together more than 150 nonprofit and corporate leaders,

researchers, practitioners, parents, and youths to identify challenges in bullying prevention. Discussions at the summit revealed inconsistencies in the definition of bullying behavior and the need to create a uniform definition of bullying. Subsequently, a review of the 2011 CDC publication of assessment tools used to measure bullying among youth ( Hamburger et al., 2011 ) revealed inconsistent definitions of bullying and diverse measurement strategies. Those inconsistencies and diverse measurements make it difficult to compare the prevalence of bullying across studies ( Vivolo et al., 2011 ) and complicate the task of distinguishing bullying from other types of aggression between youths. A uniform definition can support the consistent tracking of bullying behavior over time, facilitate the comparison of bullying prevalence rates and associated risk and protective factors across different data collection systems, and enable the collection of comparable information on the performance of bullying intervention and prevention programs across contexts ( Gladden et al., 2014 ). The CDC and U.S. Department of Education collaborated on the creation of the following uniform definition of bullying (quoted in Gladden et al., 2014, p. 7 ):

Bullying is any unwanted aggressive behavior(s) by another youth or group of youths who are not siblings or current dating partners that involves an observed or perceived power imbalance and is repeated multiple times or is highly likely to be repeated. Bullying may inflict harm or distress on the targeted youth including physical, psychological, social, or educational harm.

This report noted that the definition includes school-age individuals ages 5-18 and explicitly excludes sibling violence and violence that occurs in the context of a dating or intimate relationship ( Gladden et al., 2014 ). This definition also highlighted that there are direct and indirect modes of bullying, as well as different types of bullying. Direct bullying involves “aggressive behavior(s) that occur in the presence of the targeted youth”; indirect bullying includes “aggressive behavior(s) that are not directly communicated to the targeted youth” ( Gladden et al., 2014, p. 7 ). The direct forms of violence (e.g., sibling violence, teen dating violence, intimate partner violence) can include aggression that is physical, sexual, or psychological, but the context and uniquely dynamic nature of the relationship between the target and the perpetrator in which these acts occur is different from that of peer bullying. Examples of direct bullying include pushing, hitting, verbal taunting, or direct written communication. A common form of indirect bullying is spreading rumors. Four different types of bullying are commonly identified—physical, verbal, relational, and damage to property. Some observational studies have shown that the different forms of bullying that youths commonly experience may overlap ( Bradshaw et al., 2015 ;

Godleski et al., 2015 ). The four types of bullying are defined as follows ( Gladden et al., 2014 ):

• Physical bullying involves the use of physical force (e.g., shoving, hitting, spitting, pushing, and tripping).
• Verbal bullying involves oral or written communication that causes harm (e.g., taunting, name calling, offensive notes or hand gestures, verbal threats).
• Relational bullying is behavior “designed to harm the reputation and relationships of the targeted youth (e.g., social isolation, rumor spreading, posting derogatory comments or pictures online).”
• Damage to property is “theft, alteration, or damaging of the target youth’s property by the perpetrator to cause harm.”

In recent years, a new form of aggression or bullying has emerged, labeled “cyberbullying,” in which the aggression occurs through modern technological devices, specifically mobile phones or the Internet ( Slonje and Smith, 2008 ). Cyberbullying may take the form of mean or nasty messages or comments, rumor spreading through posts or creation of groups, and exclusion by groups of peers online.

While the CDC definition identifies bullying that occurs using technology as electronic bullying and views that as a context or location where bullying occurs, one of the major challenges in the field is how to conceptualize and define cyberbullying ( Tokunaga, 2010 ). The extent to which the CDC definition can be applied to cyberbullying is unclear, particularly with respect to several key concepts within the CDC definition. First, whether determination of an interaction as “wanted” or “unwanted” or whether communication was intended to be harmful can be challenging to assess in the absence of important in-person socioemotional cues (e.g., vocal tone, facial expressions). Second, assessing “repetition” is challenging in that a single harmful act on the Internet has the potential to be shared or viewed multiple times ( Sticca and Perren, 2013 ). Third, cyberbullying can involve a less powerful peer using technological tools to bully a peer who is perceived to have more power. In this manner, technology may provide the tools that create a power imbalance, in contrast to traditional bullying, which typically involves an existing power imbalance.

A study that used focus groups with college students to discuss whether the CDC definition applied to cyberbullying found that students were wary of applying the definition due to their perception that cyberbullying often involves less emphasis on aggression, intention, and repetition than other forms of bullying ( Kota et al., 2014 ). Many researchers have responded to this lack of conceptual and definitional clarity by creating their own measures to assess cyberbullying. It is noteworthy that very few of these

definitions and measures include the components of traditional bullying—i.e., repetition, power imbalance, and intent ( Berne et al., 2013 ). A more recent study argues that the term “cyberbullying” should be reserved for incidents that involve key aspects of bullying such as repetition and differential power ( Ybarra et al., 2014 ).

Although the formulation of a uniform definition of bullying appears to be a step in the right direction for the field of bullying prevention, there are some limitations of the CDC definition. For example, some researchers find the focus on school-age youth as well as the repeated nature of bullying to be rather limiting; similarly the exclusion of bullying in the context of sibling relationships or dating relationships may preclude full appreciation of the range of aggressive behaviors that may co-occur with or constitute bullying behavior. As noted above, other researchers have raised concerns about whether cyberbullying should be considered a particular form or mode under the broader heading of bullying as suggested in the CDC definition, or whether a separate defintion is needed. Furthermore, the measurement of bullying prevalence using such a definiton of bullying is rather complex and does not lend itself well to large-scale survey research. The CDC definition was intended to inform public health surveillance efforts, rather than to serve as a definition for policy. However, increased alignment between bullying definitions used by policy makers and researchers would greatly advance the field. Much of the extant research on bullying has not applied a consistent definition or one that aligns with the CDC definition. As a result of these and other challenges to the CDC definition, thus far there has been inconsistent adoption of this particular definition by researchers, practitioners, or policy makers; however, as the definition was created in 2014, less than 2 years is not a sufficient amount of time to assess whether it has been successfully adopted or will be in the future.

THE COMMITTEE’S APPROACH

This report builds on the April 2014 workshop, summarized in Building Capacity to Reduce Bullying: Workshop Summary ( Institute of Medicine and National Research Council, 2014c ). The committee’s work was accomplished over an 18-month period that began in October 2014, after the workshop was held and the formal summary of it had been released. The study committee members represented expertise in communication technology, criminology, developmental and clinical psychology, education, mental health, neurobiological development, pediatrics, public health, school administration, school district policy, and state law and policy. (See Appendix E for biographical sketches of the committee members and staff.) The committee met three times in person and conducted other meetings by teleconferences and electronic communication.

Information Gathering

The committee conducted an extensive review of the literature pertaining to peer victimization and bullying. In some instances, the committee drew upon the broader literature on aggression and violence. The review began with an English-language literature search of online databases, including ERIC, Google Scholar, Lexis Law Reviews Database, Medline, PubMed, Scopus, PsycInfo, and Web of Science, and was expanded as literature and resources from other countries were identified by committee members and project staff as relevant. The committee drew upon the early childhood literature since there is substantial evidence indicating that bullying involvement happens as early as preschool (see Vlachou et al., 2011 ). The committee also drew on the literature on late adolescence and looked at related areas of research such as maltreatment for insights into this emerging field.

The committee used a variety of sources to supplement its review of the literature. The committee held two public information-gathering sessions, one with the study sponsors and the second with experts on the neurobiology of bullying; bullying as a group phenomenon and the role of bystanders; the role of media in bullying prevention; and the intersection of social science, the law, and bullying and peer victimization. See Appendix A for the agendas for these two sessions. To explore different facets of bullying and give perspectives from the field, a subgroup of the committee and study staff also conducted a site visit to a northeastern city, where they convened four stakeholder groups comprised, respectively, of local practitioners, school personnel, private foundation representatives, and young adults. The site visit provided the committee with an opportunity for place-based learning about bullying prevention programs and best practices. Each focus group was transcribed and summarized thematically in accordance with this report’s chapter considerations. Themes related to the chapters are displayed throughout the report in boxes titled “Perspectives from the Field”; these boxes reflect responses synthesized from all four focus groups. See Appendix B for the site visit’s agenda and for summaries of the focus groups.

The committee also benefited from earlier reports by the National Academies of Sciences, Engineering, and Medicine through its Division of Behavioral and Social Sciences and Education and the Institute of Medicine, most notably:

• Reducing Risks for Mental Disorders: Frontiers for Preventive Intervention Research ( Institute of Medicine, 1994 )
• Community Programs to Promote Youth Development ( National Research Council and Institute of Medicine, 2002 )
• Deadly Lessons: Understanding Lethal School Violence ( National Research Council and Institute of Medicine, 2003 )
• Preventing Mental, Emotional, and Behavioral Disorders Among Young People: Progress and Possibilities ( National Research Council and Institute of Medicine, 2009 )
• The Science of Adolescent Risk-Taking: Workshop Report ( Institute of Medicine and National Research Council, 2011 )
• Communications and Technology for Violence Prevention: Workshop Summary ( Institute of Medicine and National Research Council, 2012 )
• Building Capacity to Reduce Bullying: Workshop Summary ( Institute of Medicine and National Research Council, 2014c )
• The Evidence for Violence Prevention across the Lifespan and Around the World: Workshop Summary ( Institute of Medicine and National Research Council, 2014a )
• Strategies for Scaling Effective Family-Focused Preventive Interventions to Promote Children’s Cognitive, Affective, and Behavioral Health: Workshop Summary ( Institute of Medicine and National Research Council, 2014b )
• Investing in the Health and Well-Being of Young Adults ( Institute of Medicine and National Research Council, 2015 )

Although these past reports and workshop summaries address various forms of violence and victimization, this report is the first consensus study by the National Academies of Sciences, Engineering, and Medicine on the state of the science on the biological and psychosocial consequences of bullying and the risk and protective factors that either increase or decrease bullying behavior and its consequences.

Terminology

Given the variable use of the terms “bullying” and “peer victimization” in both the research-based and practice-based literature, the committee chose to use the current CDC definition quoted above ( Gladden et al., 2014, p. 7 ). While the committee determined that this was the best definition to use, it acknowledges that this definition is not necessarily the most user-friendly definition for students and has the potential to cause problems for students reporting bullying. Not only does this definition provide detail on the common elements of bullying behavior but it also was developed with input from a panel of researchers and practitioners. The committee also followed the CDC in focusing primarily on individuals between the ages of 5 and 18. The committee recognizes that children’s development occurs on a continuum, and so while it relied primarily on the CDC defini-

tion, its work and this report acknowledge the importance of addressing bullying in both early childhood and emerging adulthood. For purposes of this report, the committee used the terms “early childhood” to refer to ages 1-4, “middle childhood” for ages 5 to 10, “early adolescence” for ages 11-14, “middle adolescence” for ages 15-17, and “late adolescence” for ages 18-21. This terminology and the associated age ranges are consistent with the Bright Futures and American Academy of Pediatrics definition of the stages of development. 4

A given instance of bullying behavior involves at least two unequal roles: one or more individuals who perpetrate the behavior (the perpetrator in this instance) and at least one individual who is bullied (the target in this instance). To avoid labeling and potentially further stigmatizing individuals with the terms “bully” and “victim,” which are sometimes viewed as traits of persons rather than role descriptions in a particular instance of behavior, the committee decided to use “individual who is bullied” to refer to the target of a bullying instance or pattern and “individual who bullies” to refer to the perpetrator of a bullying instance or pattern. Thus, “individual who is bullied and bullies others” can refer to one who is either perpetrating a bullying behavior or a target of bullying behavior, depending on the incident. This terminology is consistent with the approach used by the FPBP (see above). Also, bullying is a dynamic social interaction ( Espelage and Swearer, 2003 ) where individuals can play different roles in bullying interactions based on both individual and contextual factors.

The committee used “cyberbullying” to refer to bullying that takes place using technology or digital electronic means. “Digital electronic forms of contact” comprise a broad category that may include e-mail, blogs, social networking Websites, online games, chat rooms, forums, instant messaging, Skype, text messaging, and mobile phone pictures. The committee uses the term “traditional bullying” to refer to bullying behavior that is not cyberbullying (to aid in comparisons), recognizing that the term has been used at times in slightly different senses in the literature.

Where accurate reporting of study findings requires use of the above terms but with senses different from those specified here, the committee has noted the sense in which the source used the term. Similarly, accurate reporting has at times required use of terms such as “victimization” or “victim” that the committee has chosen to avoid in its own statements.

4 For details on these stages of adolescence, see https://brightfutures.aap.org/Bright%20Futures%20Documents/3-Promoting_Child_Development.pdf [October 2015].

ORGANIZATION OF THE REPORT

This report is organized into seven chapters. After this introductory chapter, Chapter 2 provides a broad overview of the scope of the problem.

Chapter 3 focuses on the conceptual frameworks for the study and the developmental trajectory of the child who is bullied, the child who bullies, and the child who is bullied and also bullies. It explores processes that can explain heterogeneity in bullying outcomes by focusing on contextual processes that moderate the effect of individual characteristics on bullying behavior.

Chapter 4 discusses the cyclical nature of bullying and the consequences of bullying behavior. It summarizes what is known about the psychosocial, physical health, neurobiological, academic-performance, and population-level consequences of bullying.

Chapter 5 provides an overview of the landscape in bullying prevention programming. This chapter describes in detail the context for preventive interventions and the specific actions that various stakeholders can take to achieve a coordinated response to bullying behavior. The chapter uses the Institute of Medicine’s multi-tiered framework ( National Research Council and Institute of Medicine, 2009 ) to present the different levels of approaches to preventing bullying behavior.

Chapter 6 reviews what is known about federal, state, and local laws and policies and their impact on bullying.

After a critical review of the relevant research and practice-based literatures, Chapter 7 discusses the committee conclusions and recommendations and provides a path forward for bullying prevention.

The report includes a number of appendixes. Appendix A includes meeting agendas of the committee’s public information-gathering meetings. Appendix B includes the agenda and summaries of the site visit. Appendix C includes summaries of bullying prevalence data from the national surveys discussed in Chapter 2 . Appendix D provides a list of selected federal resources on bullying for parents and teachers. Appendix E provides biographical sketches of the committee members and project staff.

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Bullying has long been tolerated as a rite of passage among children and adolescents. There is an implication that individuals who are bullied must have "asked for" this type of treatment, or deserved it. Sometimes, even the child who is bullied begins to internalize this idea. For many years, there has been a general acceptance and collective shrug when it comes to a child or adolescent with greater social capital or power pushing around a child perceived as subordinate. But bullying is not developmentally appropriate; it should not be considered a normal part of the typical social grouping that occurs throughout a child's life.

Although bullying behavior endures through generations, the milieu is changing. Historically, bulling has occurred at school, the physical setting in which most of childhood is centered and the primary source for peer group formation. In recent years, however, the physical setting is not the only place bullying is occurring. Technology allows for an entirely new type of digital electronic aggression, cyberbullying, which takes place through chat rooms, instant messaging, social media, and other forms of digital electronic communication.

Composition of peer groups, shifting demographics, changing societal norms, and modern technology are contextual factors that must be considered to understand and effectively react to bullying in the United States. Youth are embedded in multiple contexts and each of these contexts interacts with individual characteristics of youth in ways that either exacerbate or attenuate the association between these individual characteristics and bullying perpetration or victimization. Recognizing that bullying behavior is a major public health problem that demands the concerted and coordinated time and attention of parents, educators and school administrators, health care providers, policy makers, families, and others concerned with the care of children, this report evaluates the state of the science on biological and psychosocial consequences of peer victimization and the risk and protective factors that either increase or decrease peer victimization behavior and consequences.

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Open Science: Recommendations for Research on School Bullying

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• Volume 5 , pages 319–330, ( 2023 )

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The open science movement has developed out of growing concerns over the scientific standard of published academic research and a perception that science is in crisis (the “replication crisis”). Bullying research sits within this scientific family and without taking a full part in discussions risks falling behind. Open science practices can inform and support a range of research goals while increasing the transparency and trustworthiness of the research process. In this paper, we aim to explain the relevance of open science for bullying research and discuss some of the questionable research practices which challenge the replicability and integrity of research. We also consider how open science practices can be of benefit to research on school bullying. In doing so, we discuss how open science practices, such as pre-registration, can benefit a range of methodologies including quantitative and qualitative research and studies employing a participatory research methods approach. To support researchers in adopting more open practices, we also highlight a range of relevant resources and set out a series of recommendations to the bullying research community.

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Bullying in school is a common experience for many children and adolescents. Such experiences relate to a range of adverse outcomes, including poor mental health, poorer academic achievement, and anti-social behaviour (Gini et al., 2018 ; Nakamoto & Schwartz, 2010 ; Valdebenito et al., 2017 ). Bullying research has increased substantially over the past 60 years, with over 5000 articles published between 2010 and 2016 alone (Volk et al., 2017 ). Much of this research focuses on the prevalence and antecedents of bullying, correlates of bullying, and the development and evaluation of anti-bullying interventions (Volk et al., 2017 ). The outcomes of this work for children and young people can therefore be life changing, and researchers should strive to ensure that their work is trustworthy, reliable, and accessible to a wide range of stakeholders both inside and outside of academia.

In recent years, the replication crisis has led to growing concern regarding the standard of research practices in the social sciences (Munafò et al., 2017 ). To address this, open science practices, such as openly sharing publications and data, conducting replication studies, and the pre-registration of research protocols, have provided the opportunity to increase the transparency and trustworthiness of the research process. In this paper, we aim to discuss the replication crisis and highlight the risks that questionable research practices pose for bullying research. We also aim to summarise open science practices and outline how these can benefit the broad spectrum of bullying research as well as to researchers themselves. Specifically, we aim to highlight how such practices can benefit both quantitative and qualitative research and studies employing a participatory research methods approach.

The Replication Crisis

In 2015, the Open Science Collaboration (Open Science Collaboration, 2015 ) conducted a large-scale replication of 100 published studies from three journals. The results questioned the replicability of research findings in psychology. In the original 100 studies, 97 reported a significant effect compared to only 35 of the replications. Furthermore, the effect sizes reported in the original studies were typically much larger than those found in the replications. The findings of the Open Science Collaboration received significant academic and mainstream media attention, which concluded that psychological research is in crisis (Wiggins & Chrisopherson, 2019 ). While these findings are based on the analysis of psychological research, challenges in replicating research findings have been reported in a range of disciplines including sociology (Freese & Peterson, 2017 ) and education studies (Makel & Pluker, 2014 ). Shrout and Rodgers ( 2018 ) suggest that the notion that science is in crisis is further supported by (1) the number of serious cases of academic misconduct such as that of Diederick Stapel (Nelson et al., 2018 ) and (2) the prevalence of questionable research practices and misuse of inferential statistics and hypothesis testing (see Ioannidis, 2005 ). The replication crisis has called into question the degree to which research across the social sciences accurately describes the world that we live in or whether this literature is overwhelmingly populated by misleading claims based on weak and error-strewn findings.

The trustworthiness of research reflects the quality of the method, rigour of the design, and the extent to which results are reliable and valid (Cook et al., 2018 ). Research on school bullying has grown exponentially in recent years (Smith & Berkkun, 2020 ) and typically focuses on understanding the nature, prevalence, and consequences of bullying to inform prevention and intervention efforts. If our research is not trustworthy, this can impede theory development and call into question the reliability of our research and meta-analytic findings (Friese & Frankenbach, 2020 ). Ultimately, if our research findings are untrustworthy, this undermines our efforts to prevent bullying and help and support young people. Bullying research exists within a broader academic research culture, which facilitates and incentivises the ways that research is undertaken and shared. As such, the issues that have been identified have direct relevance to those working in bullying.

The Incentive Culture in Academia

“The relentless drive for research excellence has created a culture in modern science that cares exclusively about what is achieved and not about how it is achieved.”

Jeremy Farrar, Director of the Wellcome Trust (Farrar, 2019 ).

In academia, career progression is closely tied to publication record. As such, academics feel under considerable pressure to publish frequently in high-quality journals to advance their careers (Grimes et al., 2018 ; Munafò et al., 2017 ). Yet, the publication process itself is biased toward accepting novel or statistically significant findings for publication (Renkewitz & Heene, 2019 ). This bias fuels a perception that non-significant results will not be published (the “file drawer problem”: Rosenthal, 1979 ). This can result in researchers employing a range of questionable research practices to achieve a statistically significant finding in order to increase the likelihood that a study will be accepted for publication. Taken together, this can lead to a perverse “scientific process” where achieving statistical significance is more important than the quality of the research itself (Frankenhuis & Nettle, 2018 ).

Questionable Research Practices

Questionable research practices (QRPs) can occur at all stages of the research process (Munafò et al., 2017 ). These practices differ from research misconduct in that they do not typically involve the deliberate intent to deceive or engage in fraudulent research practices (Stricker & Günther, 2019 ). Instead, QRPs are characterised by misrepresentation, inaccuracy, and bias (Steneck, 2006 ). All are of direct relevance to the work of scholars in the bullying field since each weakens our ability to achieve meaningful change for children and young people. QRPs emerge directly from “researcher degrees of freedom” that occur at all stages of the research process and which simply reflect the many decisions that researchers make with regard to their hypotheses, methodological design, data analyses, and reporting of results (see Wicherts et al., 2016 for an extensive list of researcher degrees of freedom). These decisions pose fundamental threats to how robust a study is as each compromises the likelihood that findings accurately model a psychological or social process (Munafò et al., 2017 ). QRPs include p -hacking; hypothesising after the result is known (HARKing); conducting studies with low statistical power; and the misuse of p values (Chambers et al., 2014 ). Such QRPs may reflect a misunderstanding of inferential statistics (Sijtsma, 2016 ). A misunderstanding of statistical theory can also lead to a lack of awareness regarding the nature and impact of QRPs (Sijtsma, 2016 ). This includes the prevailing approach to quantitative data analysis, Null Hypothesis Significance Testing (NHST) (Lyu et al., 2018 ; Travers et al., 2017 ), which is overwhelmingly the approach used in the bullying field. QRPs can fundamentally threaten the degree to which research in bullying can be trusted, replicated, and effective in efforts to implement successful and impactful intervention or prevention programs.

P -hacking (or data-dredging) reflects methods of re-analysing data in different ways to find a significant result (Raj et al., 2018 ). Such methods can include the selective deletion of outliers, selectively controlling for variables, recoding variables in different ways, or selectively reporting the results of structural equation models (Simonsohn et al., 2014 ). While there are various methods of p -hacking, the end goal is the same: to find a significant result in a data set, often when initial analyses fail to do so (Friese & Frankenbach, 2020 ).

There are no available data on the degree to which p -hacking is a problem in bullying research per se, but the nature of the methods commonly used mean it is a clear and present danger. For example, the inclusion of multiple outcome measures (allowing those with the “best” results to be cherry-picked for publication), measures of involvement in bullying that can be scored or analysed in multiple ways (e.g. as a continuous measure or as a method to categorise participants as involved or not), and the presence of a diverse selection of demographic variables (which can be selectively included or excluded from analyses) all provide researchers with an array of possible analytic approaches. Such options pose a risk for p -hacking as decisions can be made on the results of statistical fishing (i.e. hunting to find significant effects) rather than on any underpinning theoretical rationale.

P -hacking need not be driven by a desire to deceive; rather, it can be used by well-meaning researchers and their wish to honestly identify useful or interesting findings (Wicherts et al., 2016 ). Sadly, even in this case, the impact of p- hacking remains profoundly problematic for the field. The p- hacking process biases the literature towards erroneous significant results and inflated effect sizes, impacting on our understanding of any issue that we seek to understand better, and biasing effect size estimates reported in meta-analyses (Friese & Frankenbach, 2020 ). While such effects may seem remote or of only academic interest, they compromise all that we in the bullying field seek to accomplish because they make it much less likely that effective, impactful, and meaningful intervention and prevention strategies can be identified and implemented.

Typically, quantitative research follows the hypothetico-deductive model (Popper, 1959 ). From this perspective, hypotheses are formulated based on appropriate theory and previous research (Rubin, 2017 ). Once written, the study is designed, and data are collected and analysed (Rubin, 2017 ). Hypothesising after the result is known, or HARKing (Kerr, 1998 ), occurs when researchers amend their hypotheses to reflect their completed data analysis (Kerr, 1998 ). HARKing results in confusion between confirmatory and exploratory data analysis (Shrout & Rodgers, 2018 ), creating a literature where hypotheses are always confirmed and never falsified. This inhibits theory development (Rubin, 2017 ) in part because “progress” is, in fact, the accumulation of type 1 errors.

Low Statistical Power

Statistical power reflects the power in a statistical test to find an effect if there is one to find (Cohen, 2013 ). There are concerns regarding the sample sizes used in bullying research, as experiences of bullying are typically of a low frequency and positively skewed (Vessey et al., 2014 ; Volk et al., 2017 ). Low statistical power is problematic in two ways. First, it increases the type II error rate (the probability of falsely rejecting the null hypothesis), meaning that researchers may fail to report important and meaningful effects. Statistically significant effects can still be found under the conditions of low statistical power; however, the size of these effects is likely to be exaggerated due to a lower positive predictive value (the probability of a statistically significant result being genuine) (Button et al., 2013 ). In this case, researchers may find significant effects even in small samples, but those effects are at risk of being inflated.

QRPs in Qualitative Research

Apart from the previously discussed issues, there are also QRPs in qualitative work. Mainly, these involve issues pertaining to trustworthiness such as credibility, transferability, dependability, and confirmability (See Shenton, 2004 ). One factor that can influence perceptions about qualitative work is the possibility of subjectivity or different interpretations of the same data (Haven & Van Grootel, 2019 ). Additionally, the idea that the researcher will be biased and that their experiences, beliefs, and personal history will all influence how they both collect and interpret data has also been discussed (Berger, 2015 ). Clearly stating the positionality of the researcher and how their experiences informed their current research (the process of reflexivity) can help others better understand their interpretation of the data (Berger, 2015 ). Finally, one decision that qualitative researchers should consider when thinking about their designs is their stopping criteria. This might imply code or meaning saturation (see Hennink et al., 2017 , for more detail on how these two types are different from one another). Thus, making it clear in the conceptualisation process when and how the data collection will stop is important to assure transparency and high-quality research. This is not a complete list of QRPs in qualitative research, but these seem to be the most urgent when it comes to bullying research when thinking about open science.

The Prevalence and Impact of QRPs

Identifying the prevalence of QRPs and academic misconduct is challenging as this is reliant on self-reports. In their survey of 2155 psychologists, John et al. ( 2012 ) identified that 78% of participants had not reported all dependent measures, 72% had collected more data after finding their statistical effects were not statistically significant, 67% reported selective reporting of studies that “worked” (yielded a significant effect), and 9% reported falsifying data. Such problematic practices have serious implications for the reliability of effects reported in the research literature (John et al., 2012 ), which can impact interventions and treatments such evidence may inform. Furthermore, De Vries et al. ( 2018 ) have highlighted how biases in the publication process threaten the validity of treatment results reported in the literature. Although focused on the treatment of depression, their work has clear lessons for the bullying research community. They demonstrate how the bias towards reporting more positive, significant effects, distorts a literature in favour of treatments that appear efficacious but are much less so in practice (Box 1 ).

Box 1 The Replication Crisis

Munafò et al. ( 2017 ) outline a manifesto for reproducible research, highlighting problems with current research practices.

Shrout and Rodgers  ( 2018 ) provide an overview of the replication crisis and questionable research practices.

Steneck ( 2006 ) provides a detailed overview of definitions of academic misconduct, questionable research practices, and academic integrity.

Open Science

Confronting these challenges can be daunting, but open science offers several strategies that researchers in the bullying field can use to increase the transparency, reproducibility, and openness of their research. The most common practices include openly sharing publications and data, encouraging replication, pre-registration, and open peer-review. Below, we provide an overview of open science practices, with a particular focus on pre-registration and replication studies. We recommend that researchers begin by using those practices that they can most easily integrate into their work, building their repertoire of open science actions over time. We provide a series of recommendations for the school bullying research community alongside summaries of useful supporting resources (Box 2 ).

Box 2 Key Reading on Open Science

Banks et al. ( 2019 ) discuss frequently asked questions about open science providing a good overview of open science practices and contemporary debates.

Crüwell et al. ( 2019 ) provide an annotated reading list on important papers in open science.

Gehlbach and Robinson ( 2021 ) in their introduction to a special edition of the journal Educational Psychologist they discuss the adoption of open science practices in the context of what they term “old school” research practices.

Lindsay ( 2020 ) outlines a series of steps researchers can take to integrate open science practices into their research.

Open Publication, Open Data, and Reporting Standards

Open publication.

Ensuring research publications are openly available by providing access to pre-print versions of papers or paying for publishers to make articles openly available is now a widely adopted practice (Concannon et al., 2019 ; McKiernan et al., 2016 ). Articles can be hosted on websites such as ResearchGate and/or on institutional repositories, allowing a wider pool of potential stakeholders to access relevant bullying research and increasing the impact of research (Concannon et al., 2019 ). This process also supports access for the research and practice communities in low- and middle-income countries where even Universities may be unable to pay journal subscriptions. The authors can also share pre-print versions of their papers for comment and review before submitting them to a journal for review using an online digital repository, such as PsyArXiv. Sharing publications in this way can encourage both early feedback on articles and the faster dissemination of research findings (Chiarelli et al., 2019 ).

Making data and data analysis scripts openly available is also encouraged, can enable further data analysis (e.g. meta-analysis), and facilitates replication (Munafò et al., 2017 ; Nosek & Bar-Anan, 2012 ). It also enables the collation of larger data sets, and secondary data analyses to test different hypotheses. Several publications on bullying in school are based on the secondary analysis of openly shared data (e.g. Dantchev & Wolke, 2019 ; Przybylski & Bowes, 2017 ) and highlight the benefits of such analyses. Furthermore, although limited in number, examples of papers on school bullying where data, research materials, and data analysis scripts are openly shared are emerging (e.g. Przybylski, 2019 ).

Bullying data often includes detailed personal accounts of experiences and the impact of bullying. Such data are highly sensitive, and there may be a risk that individuals can be identified. To address such sensitivities, Meyer ( 2018 ) (see box 3 ) proposes a tiered approach to the consent process, where participants are actively involved in decisions around what parts of their data and where their data are shared. Meyer ( 2018 ) also highlights the importance of selecting the right repository for your data. Some repositories are entirely open, whereas others only provide access to suitably qualified researchers. While bullying data pose particular ethical challenges, the sharing of all data is encouraged (Bishop, 2009 ; McLeod & O’Connor, 2020 ).

Reporting Standards

Reporting standards are standards for reporting a research study and provide useful guidance on what methodological and analytical information should be included in a research paper (Munafò et al., 2017 ). Such guidelines aim to ensure sufficient information is provided to enable replication and promote transparency (Munafò et al., 2017 ). Journal publishers are now beginning to outline what open science practices should be reported in articles. For example, from July 2021, when submitting a paper for review in one of the American Psychological Association journals, the authors are now required to state whether their data will be openly shared and whether or not their study was pre-registered. In a bullying context, Smith and Berkkun ( 2020 ) have highlighted that important contextual data is often missing from publications and recommend, for example, that the gender and age of participants alongside the country and date of data collection should be included as standard in papers on bullying in school.

Recommendations:

Researchers to start to share all research materials openly using an online repository. Box 3 provides some useful guidance on how to support the open sharing of research materials.

Journal editors and publishers to further promote the open sharing of research material.

Researchers to follow the recommendations set out by Smith and Berkkun ( 2020 ) and follow a set of reporting standards when reporting bullying studies.

Reviewers be mindful of Smith and Berkkun ( 2020 ) recommendations when reviewing bullying papers.

Box 3 Useful Resources on Openly Sharing Research Materials & Reporting Standards

Banks et al. ( 2019 ) provide a helpful overview of open science practices, alongside a set of recommendations for ensuring research is more open.

Meyer ( 2018 ) provides some useful guidance on managing the ethical issues of openly sharing data.

The Equator Network ( https://www.equator-network.org/reporting-guidelines/ ) is a useful resource for the sharing of different reporting standards, for example, the PRISMA guidelines for systematic reviews and STROBE standards for observational studies.

The Foster website is an online e-learning portal with a wealth of resources to help researchers develop open science practices https://www.fosteropenscience.eu/ , including sharing resources and pre-prints.

The Open Science Framework has resources to support open science practices and to use their platform https://www.cos.io/products/osf .

Smith and Berkkun ( 2020 ) provide a review of contextual information reported in bullying research papers and offer recommendations on what information to include.

The PsyArXiv https://psyarxiv.com and SocArXiv https://osf.io/preprints/socarxiv repositories accept pre-print publications in psychology and sociology.

Replication Studies

Replicated findings increase confidence in the reliability of that finding, ensuring research findings are robust and enabling science to self-correct (Cook et al., 2018 ; Drotar, 2010 ). Replication reflects the ability of a researcher to duplicate the results of a prior study with new data (Goodman et al., 2018 ). There are different forms of replication that can be broadly categorised into two: those that aim to recreate the exact conditions of an earlier study (exact/direct replication) and those that aim to test the same hypotheses again using a different method (conceptual replication) (Schmidt, 2009 ). Replication studies are considered fundamental in establishing whether study findings are consistent and trustworthy (Cook et al., 2018 ).

To date, few replication studies have been conducted on bullying in schools. A Web of Science search using the Boolean search term bully* alongside the search term “replication” identified two replication studies (Berdondini & Smith, 1996 ; Huitsing et al., 2020 ). Such a small number of replications may reflect concerns regarding the value of these and concerns about how to conduct such work when data collection is so time and resource-intensive. In addition, school gatekeepers are themselves interested in novelty and addressing their own problems and may be reluctant to participate in a study which has “already been done”. One possible solution to this challenge is to increase the number of large-scale collaborations among bullying researchers (e.g. multiple researchers across many sites collecting the same data). Munafò et al. ( 2017 ) highlight the benefits of collaboration and “team science” to build capacity in a research project. They argue that greater collaboration through team science would enable researchers to undertake higher-powered studies and relieve the pressure on single researchers. Such projects also have the benefit of increasing generalisability across settings and populations.

Undertake direct replications or, as a more manageable first step, include aspects of replication within larger studies.

Journal editors to actively promote the submission of replication studies on school bullying.

Journal editors, editorial panels, and reviewers to recognise the value of replication studies rather than favouring new or novel findings (Box 4 ).

Box 4 Useful Resources on Replication Studies

Brandt et al. ( 2014 ) provide a useful step by step guide on conducting replication studies, including a registration template form for pre-registering a replication study (available here: https://osf.io/4jd46/ ).

Coyne et al. ( 2016 ) discuss the benefits of replication to research in educational research (with a particular focus on special education).

Duncan et al. ( 2014 ) discuss the benefits of replication to research in developmental psychology.

Pre-Registration

Pre-registration requires researchers to set out, in advance of any data collection, their hypotheses, research design, and planned data analysis (van’t Veer & Giner-Sorolla, 2016 ). Pre-registering a study reduces the number of researcher degrees of freedom as all decisions are outlined at the start of a project. However, to date, there have been few pre-registered studies in bullying. There are two forms of pre-registration: the pre-registration of analysis plans and registered reports. In a pre-registered analysis plan, the hypotheses, research design, and analysis plan are registered in advance. These plans are then stored in an online repository (e.g. the Open Science Framework (OSF) or AsPredicted website), which is then time-stamped as a record of the planned research project (van’t Veer & Giner-Sorolla, 2016 ). Registered reports, however, integrate the pre-registration of methods and analyses into the publication process (Chambers et al., 2014 ). With a registered report, researchers can submit their introduction and proposed methods and analyses to a journal for peer review. This creates a two-tier peer-review process, where the registered reports can be accepted in principle or rejected in the first stage of review, based on the rigour of the proposed methods and analysis plans rather than on the findings of the study (Hardwicke & Ioannidis, 2018 ). In the second stage of the review process, the authors then submit the complete paper (at a later date after data have been collected and analyses completed), and this is also reviewed. The decision to accept a study is therefore explicitly based on the quality of the research process rather than the outcome (Frankenhuis & Nettle, 2018 ) and in practice, almost no work is ever rejected following an in-principal acceptance at stage 1 (C. Chambers, personal communication, December 11, 2020). At the time of writing, over 270 journals accept registered reports, many of which are directly relevant to bullying researchers (e.g. Developmental Science, British Journal of Educational Psychology, Journal of Educational Psychology).

Pre-registration offers one approach for improving the validity of bullying research. Employing greater use of pre-registration would complement other recommendations on how to improve research practices in bullying research. For example, Volk et al. ( 2017 ) propose a “bullying research checklist” (see Box 5 ).

Box 5 Volk et al. ( 2017 ) Bullying Research Checklist ( reproduced with permission )

State and justify your chosen definition of bullying.

Outline the theoretical logic underlying your hypotheses and how it pertains to your chosen definition and program of research/intervention.

Use one's logic model and theoretical predictions to determine which kind of measurements are most appropriate for testing one's hypotheses. There is no gold standard measure of bullying, but be aware of the strengths and weaknesses of the different types of measures. Where possible, use complementary forms of measurement and reporters to offset any weaknesses.

Implement an appropriate research or intervention design (longitudinal if possible) and recruit an appropriate sample.

Reflect upon the final product, its associations with the chosen logic model and theory, and explicitly discuss important pertinent limitations with a particular emphasis on issues concerning the theoretical validity of one's findings.

Volk et al.’s ( 2017 ) checklist highlights the importance of setting out in advance the definition of bullying, alongside the theoretical underpinnings for the hypotheses.

Pre-Registering Quantitative Studies

The pre-registration of quantitative studies requires researchers to state the hypotheses, method, and planned data analysis in advance of any data collection (van’t Veer & Giner-Sorolla, 2016 ). When outlining the hypotheses being tested, researchers are required to outline the background and theoretical underpinning of the study. This reflects the importance of theoretically led hypotheses (van’t Veer & Giner-Sorolla, 2016 ), which are more appropriately tested using NHST and inferential statistics in a confirmatory rather than exploratory design (Wagenmakers et al., 2012 ). Requiring researchers to state their hypotheses in advance of any data collection adheres to the confirmatory nature of inferential statistics and reduces the risk of HARKing (van’t Veer & Giner-Sorolla, 2016 ). Following a description of the hypotheses, researchers outline the details of the planned method, including the design of the study, the sample, the materials and measures, and the procedure. Information on the nature of the study and how materials and measures will be used and scored are outlined in full. Researchers are required to provide a justification for and an indication of the desired sample size.

The final stage of the pre-registration process requires researchers to consider and detail all steps of the data analysis process. The data analysis plan should be outlined in terms of what hypotheses are tested using what analyses and any plans for follow-up analysis (e.g. post hoc testing and any exploratory analyses). Despite concerns to the contrary (Banks et al., 2019 ; Gonzales & Cunningham, 2015 ), the aim of pre-registration is not to devalue exploratory research, but rather, to make more explicit what is exploratory and what is confirmatory (van’t Veer & Giner-Sorolla, 2016 ). While initially, the guidance on pre-registration focused more on confirmatory analyses, more recent guidance considers how researchers can pre-register exploratory studies (Dirnagl, 2020 ), and make a distinction between confirmatory versus exploratory research in the publication process (McIntosh, 2017 ). Irrespective of whether confirmatory or exploratory analyses are planned, pre-registering an analysis reduces the risk of p -hacking (van’t Veer & Giner-Sorolla, 2016 ). A final point, often a concern to those unfamiliar with open science practices, is that a pre-registration does not bind a researcher to a single way of analysing data. Changes to plans are entirely acceptable when they are deemed necessary and are described transparently.

Pre-Registering Qualitative Studies

Pre-registration of qualitative studies is still relatively new (e.g. Kern & Gleditsch, 2017a , b ; Piñeiro & Rosenblatt, 2016 ). This is because most of the work uses inductive and hypothesis-generating approaches. Coffman and Niederle ( 2015 ) argue that this hypothesis-generation is one of the most important reasons why pre-registering qualitative work is so important. This could help distinguish between what hypotheses are generated from the data and which were hypotheses conceptualised from the start. Therefore, it could even be argued that pre-registering qualitative research encourages exploratory work. Using pre-registration prior to a hypothesis-generating study will also help with the internal validity of this same study, as it will be possible to have a sense of how the research evolved from before to post data collection.

Using investigator triangulation, where multiple researchers share and discuss conclusions and findings of the data, and reach a common understanding, could improve the trustworthiness of a qualitative study (Carter et al., 2014 ). Similarly, where establishing intercoder reliability is appropriate, the procedures demonstrating how this is achieved can be communicated and recorded in advance. One example of this would be the use of code books. When analysing qualitative data, developing a code book that could be used by all the coders could help with intercoder reliability and overall trustworthiness (Guest et al., 2012 ). These are elements that could be considered in the pre-registration process by clearly outlining if intercoder reliability is used and, if so, how this is done. To improve the transparency of pre-registered qualitative work, it has also been suggested that researchers should clearly state whether, if something outside the scope of the interview comes to light, such novel experiences will also be explored with the participant (Haven & Van Grootel, 2019 ; Kern & Gleditsch, 2017a , b ). Issues of subjectivity, sometimes inherent to qualitative work, can be reduced as a result of pre-registering because it allows the researcher to clearly consider all the elements of the study and have a plan before data collection and analysis, which reduces levels of subjectivity.

Kern and Gleditsch ( 2017a , b ) provide some practical suggestions on how to use pre-registration with qualitative studies. For example, when using in-depth interviews, one should make the interview schedule and questions available to help others to comprehend what the participants were asked. Similarly, they suggest that all recruitment and sampling strategy plans should be included to improve transparency (Haven & Van Grootel, 2019 ; Kern & Gleditsch, 2017a , b ). Piñeiro and Rosenblatt ( 2016 ) provide an overview of how these pre-registrations could be achieved. They suggested three main elements: conceptualisation of the study, theory (inductive or deductive in nature), and design (working hypothesis, sampling, tools for data collection). More recently, Haven and Van Grootel ( 2019 ) highlighted a lack of flexibility in the existing pre-register templates to adapt to qualitative work, as such, they adapted an OSF template to a qualitative study.

Integrating Participatory Research Methods into Pre-Registration

Participatory research methods (PRMs) aim to address power imbalances within the research process and validate the local expertise and knowledge of marginalised groups (Morris, 2002 ). The key objective of PRM is to include individuals from the target population, also referred to as “local experts”, as meaningful partners and co-creators of knowledge. A scoping review of PRM in psychology recommends wider and more effective use (Levac et al., 2019 ). Researchers are calling specifically for youth involvement in bullying studies to offer their insight, avoid adult speculation, and assist in the development of appropriate support materials (O’Brien, 2019 ; O’Brien & Dadswell, 2020 ). PRM is particularly appropriate for research with children and young people who experience bullying behaviours given their explicit, defined powerlessness. Research has shown that engaging young people in bullying research, while relatively uncommon, provides lasting positive outcomes for both researchers and participants (Gibson et al., 2015 ; Lorion, 2004 ).

Pre-registration has rarely been used in research undertaking a PRM approach. It is a common misconception that pre-registration is inflexible and places constraints on the participant-driven nature of PRM (Frankenhuis & Nettle, 2018 ). However, pre-registration still allows for the exploratory and subjective nature of PRM but in a more transparent way, with clear rationale and reasoning. An appropriate pre-registration method for PRM can utilise a combination of both theoretical and iterative pre-registration. Using a pre-registration template, researchers should aim to document the research process highlighting the main contributing theoretical underpinnings of their research, with anticipatory hypotheses and complementary analyses (Haven & Van Grootel, 2019 ). This initial pre-registration can then be supported using iterative documentation detailing ongoing project development. This can include utilising workflow tools or online notebooks, which show insights into the procedure of co-researchers and collaborative decision making (Kern & Gleditsch, 2017a , b ). This creates an evidence trail of how the research evolved, providing transparency, reflexivity, and credibility to the research process.

The Perceived Challenges of Pre-Registration.

To date, there have been few pre-registered studies in bullying. A Web of Science search using the Boolean search terms bully* peer-vict*, pre-reg*, and preregist* identified four pre-registered studies on school bullying (Kaufman et al., 2022 ; Legate et al., 2019 ; Leung, 2021 ; Noret et al., 2021 ). The lack of pre-registrations may reflect concerns that it is a difficult, rigid, and time-consuming process. Reischer and Cowan ( 2020 ) note that pre-registration should not be seen as a singular time-stamped rigid plan but as an ongoing working model with modifications. Change is possible so long as this is clearly and transparently articulated, for example, in an associated publication or in an open lab notebook (Schapira et al., 2019 ). The move to pre-registering a study requires a change in workflow rather than more absolute work. However, this early and detailed planning (especially concerning analytical procedures) can improve the focus on the quality of the research process (Ioannidis, 2008 ; Munafò et al., 2017 ).

The Impact of Pre-Registration.

The impact of pre-registration on reported effects can be extensive. The pre-registration of funded clinical trials in medicine has been a requirement since 2000. In an analysis of randomised control trials examining the role of drugs or supplements for intervening in or treating cardiovascular disease, Kaplan and Irvin ( 2015 ) identified a substantial change in the number of significant effects reported once pre-registration was introduced (57% reported significant effects prior to the requirement but and only 8% after). More recently, Scheel et al. ( 2021 ) compared the results of 71 pre-registered studies in psychology with the results published in 152 studies that were not pre-registered. They found that only 44% of the pre-registered studies reported a significant effect, compared to 96% of studies that were not pre-registered. As a result, the introduction of pre-registration has increased the number of null effects reported in the literature and presents a more reliable picture of the effects of particular interventions.

When conducting your next research study on bullying, consider pre-registering the study.

Journal editors and publishers to actively encourage registered reports as a submission format.

The Benefits of Open Science for Researchers

Employing more open science practices can often be challenging, in part because they force us to reconsider methods that are already “successful” (often synonymous with “those which result in publication”). Based on our own experience, this takes time and is best approached by beginning small and building up to a wider application of the practices we have outlined in this article. Alongside increasing the reliability of research, open science practices are associated with several career benefits for the researcher. Articles which use open science practices are more likely to be accepted for publication, are more visible, and are cited more frequently (Allen & Mehler, 2019 ). Open science can also lead to the development of more supportive networks for collaboration (Allen & Mehler, 2019 ). In terms of career advancement, Universities are beginning to reward engagement with science principals in their promotion criteria. For example, the University of Bristol (UK) will consider open research practices such as data sharing and pre-registration in promotion cases in 2020–21. Given that formal recognition such as this has been recommended by the European Union for some time (O’Carroll et al., 2017 ), it is likely to be an increasingly important part of career progression in academia (Box 6 ).

Box 6 Pre-Registration

van't Veer and Giner-Sorolla ( 2016 ) provide a clear overview of the pre-registration process and provide a template for the pre-registration of studies.

Center for Open Science YouTube channel https://www.youtube.com/watch?v=PboPpcg6ik4 includes several webinars on pre-registration and the replication crisis. The OSF website also includes a number of pre-registration templates for researchers to use https://osf.io/zab38/wiki/home/?view , and provide a list of journals that accept registered reports https://www.cos.io/initiatives/registered-reports

Haven and Van Grootel ( 2019 ) review the issues around pre-registering of qualitative work and adapted an existing pre-registering OSF template to suit these types of studies.

This paper sought to clarify the ways in which bullying research is undermined by a failure to engage with open science practices. It highlighted the potential benefits of open science for the way we conduct research on bullying. In doing so, we aimed to encourage the greater use of open science practices in bullying research. Given the importance of this for the safety and wellbeing of children and young people, the transparency and reliability of this research is paramount and is enhanced via greater use of open science practices. Ultimately, researchers working in the field of bullying are seeking to accurately understand and describe the experiences of children and young people. Open science practices make it more likely that we will achieve this goal and, as a result, be well-placed to develop and implement successful evidence-based intervention and prevention programs.

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Nathalie Noret

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Noret, N., Hunter, S.C., Pimenta, S. et al. Open Science: Recommendations for Research on School Bullying. Int Journal of Bullying Prevention 5 , 319–330 (2023). https://doi.org/10.1007/s42380-022-00130-0

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The Effectiveness of Policy Interventions for School Bullying: A Systematic Review

William hall.

University of North Carolina at Chapel Hill

Associated Data

Bullying threatens the mental and educational well-being of students. Although anti-bullying policies are prevalent, little is known about their effectiveness. This systematic review evaluates the methodological characteristics and summarizes substantive findings of studies examining the effectiveness of school bullying policies.

Searches of 11 bibliographic databases yielded 489 studies completed since January 1, 1995. Following duplicate removal and double-independent screening based on a priori inclusion criteria, 21 studies were included for review.

Substantially more educators perceive anti-bullying policies to be effective rather than ineffective. Whereas several studies show that the presence or quality of policies is associated with lower rates of bullying among students, other studies found no such associations between policy presence or quality and reductions in bullying. Consistent across studies, this review found that schools with anti-bullying policies that enumerated protections based on sexual orientation and gender identity were associated with better protection of lesbian, gay, bisexual, transgender, and queer (LGBTQ) students. Specifically, LGBTQ students in schools with such policies reported less harassment and more frequent and effective intervention by school personnel. Findings are mixed regarding the relationship between having an anti-bullying policy and educators’ responsiveness to general bullying.

Conclusions

Anti-bullying policies might be effective at reducing bullying if their content is based on evidence and sound theory and if they are implemented with a high level of fidelity. More research is needed to improve on limitations among extant studies.

Bullying in schools is a pervasive threat to the well-being and educational success of students. Bullying refers to unwanted aggressive behaviors enacted intentionally over time by an individual or group using some form of power to cause physical and/or psychological harm to another individual or group in a shared social context ( Gladden, Vivolo-Kantor, Hamburger, & Lumpkin, 2014 ; Olweus, 2013 ). Bullying is also a widespread phenomenon. A meta-analysis of 82 studies conducted in 22 countries in North America, South America, Europe, Southern Africa, East Asia, and Australia and Oceania found that 53% of youth were involved in bullying as bullies, victims, or both bullies and victims ( Cook, Williams, Guerra, & Kim, 2010 ).

Involvement in bullying as perpetrators, victims, bully–victims, and bystanders has been linked with deleterious outcomes by both cross-sectional and longitudinal studies. Youths who are bullied can experience immediate negative effects that include physical injury, humiliation, sadness, rejection, and helplessness ( Kaiser & Rasminsky, 2009 ). Over time, a number of mental and behavioral health problems can emerge, including low self-esteem, anxiety, depression, suicidal ideation and behavior, conduct problems, psychosomatic problems, psychotic symptoms, and physical illness ( Arseneault, Bowes, & Shakoor, 2010 ; Dake, Price, & Telljohann, 2003 ; Gini & Pozzoli, 2009 ; Kim & Leventhal, 2008 ; Klomek, Sourander, & Gould, 2010 ; Reijntjes et al., 2011 ; Reijntjes, Kamphuis, Prinzie, & Telch, 2010 ; Ttofi, Farrington, Lösel, & Loeber, 2011a ). In addition, students who have been bullied may not feel safe at school and may disengage from the school community due to fear and sadness, which may, in turn, contribute to higher rates of absenteeism and lower academic performance ( Arseneault et al., 2006 ; Buhs & Ladd, 2001 ; Buhs, Ladd, & Herald, 2006 ; Glew, Fan, Katon, Rivara, & Kernic, 2005 ; Juvonen, Nishina, & Graham, 2000 ; Nakamoto & Schwartz, 2010 ).

Youths who bully also face psychosocial difficulties. These youths often grow up in harsh social environments with few resources ( Hong & Espelage, 2012 ), and bullies often lack impulse control and empathy for others ( O’Brennan, Bradshaw, & Sawyer, 2009 ; van Noorden, Haselager, Cillessen, & Bukowski, 2015 ). Students who bully are more likely to skip school, perform poorly, and drop out ( Jankauskiene, Kardelis, Sukys, & Kardeliene, 2008 ; Ma, Phelps, Lerner, & Lerner, 2009 ). Bullying perpetration also is associated with depressive symptoms, suicidal ideation and behavior, and violent and criminal behavior (e.g., assault, robbery, vandalism, carrying weapons, and rape; Dake et al., 2003 ; Kim& Leventhal, 2008 ; Klomek et al., 2010 ; Ttofi, Farrington, & Lösel, 2012 ; Ttofi, Farrington, Lösel, & Loeber, 2011b ). Compared to nonperpetrators, students who bully have an increased risk of violent and criminal behaviors into adulthood. A meta-analysis of longitudinal studies found that school bullies were 2.5 times more likely to engage in criminal offending over an 11-year follow-up period ( Ttofi et al., 2011b ).

Other youths involved in bullying include bully–victims and bystanders. Bully–victims are students who have been bullied but also engage in bullying others. Bully–victims can experience a combination of internalizing and externalizing problems ( Cook, Williams, Guerra, Kim, & Sadek, 2010 ). Student bystanders are present in up to 90% of bullying incidents ( Atlas & Pepler, 1998 ; Craig & Pepler, 1995 ; Glew et al., 2005 ; Hawkins, Pepler, & Craig, 2001 ). Youths who witness bullying often report emotional distress, including increased heart rate and higher levels of fear, sadness, and anger when recalling bullying incidents ( Barhight, Hubbard, & Hyde, 2013 ; Janson & Hazler, 2004 ). Thus, across the literature, bullying is associated with problematic outcomes for perpetrators, victims, bully–victims, and bystanders alike.

Policy as an Intervention for Bullying

Perspectives vary on how to best address bullying in schools. Intervention strategies have included suspending and expelling bullies, training teachers on intervening, teaching empathy and respect to students through classroom lessons, maintaining constant adult supervision throughout school settings, collaborating with parents about student behavior, and enacting school-wide policies about bullying. In the United States, policies addressing bullying emerged in 1999 following the Columbine High School shootings. These policies have spread due to increased awareness and concern about student violence and school safety ( Birkland & Lawrence, 2009 ). A policy is a system of principles created by governing bodies or public officials to achieve specific outcomes by guiding action and decision making. Policy is an umbrella term that refers to various regulatory measures, including laws, statutes, policies, regulations, and rules. These terms vary based on the jurisdiction and legal authority of the individual or group who established the policy. In the United States, K–12 education policy, which includes school bullying policy, can be established at the federal, state, and local levels ( Mead, 2009 ).

One advantage of policy interventions for bullying is that they can influence student, teacher, and administrator behavior as well as school organizational practices. For example, school bullying policies typically prohibit certain behaviors, such as threatening and harassing other students or retaliating against students who witness and then report bullying incidents. Policies may also require behaviors, such as requiring teachers to report bullying incidents to administrators and requiring administrators to investigate reports of bullying. Further, policies may promote certain behaviors by explicitly stating positive behavioral expectations for students or discourage behaviors by explicitly stating punishments associated with aggressive behaviors. At the school level, policies can guide organizational practices, such as establishing bullying incident reporting procedures and creating school-safety teams tasked with developing and executing school-safety plans. Thus, bullying policies can influence individual and organizational behaviors.

Another advantage of bullying policies is that they are upstream interventions that provide a foundation for downstream interventions. In other words, policies are systems-level interventions that typically require more targeted intervention programs, practices, and services at the organizational, group, and individual levels ( McKinlay, 1998 ). For example, a bullying policy may be adopted within a state or district; the policy then applies to all schools within the state or district. This policy may require training all school employees on bullying prevention strategies, integrating bullying awareness and education into classroom lessons and curricula, and providing counseling for students involved in bullying. Thus, policy lays the groundwork for an array of more specific and targeted interventions to be deployed in schools by outlining goals and directives in the policy document.

Policy design is important because the content influences a cascade of actions throughout school systems, which may result in positive or negative outcomes. For example, a bullying policy that requires schools to provide counseling services and positive behavioral reinforcement to students who perpetrate bullying is markedly different than a policy that requires schools to suspend or expel students who have carried out multiple acts of bullying. Research shows that overly harsh and punitive policies (e.g., “three strikes and you’re out” policies or “zero-tolerance” policies) are not effective at reducing aggression or improving school safety ( American Psychological Association Zero Tolerance Task Force, 2008 ). Thus, bullying policies should be crafted and revised using evidence-based strategies.

Anti-bullying laws have been enacted in a number of countries, including Canada, the Philippines, the United Kingdom, and the United States. Although the United States does not have a federal law against school bullying currently, all states have enacted anti-bullying laws ( U.S. Department of Health and Human Services, 2015 ). The content of these laws was reviewed in a U.S. Department of Education report, which shows some consistency but also variability in the inclusion of policy components (see Table 1 ; Stuart-Cassel, Bell, & Springer, 2011 ). These state laws apply to approximately 98,000 K–12 public schools and have a goal of protecting more than 50 million students from involvement in bullying ( Snyder & Dillow, 2013 ; Stuart-Cassel et al., 2011 ).

Percentage of State Anti-Bullying Laws That Included Key Policy Components Identified by the U.S. Department of Education

Note. The percentages are based on 46 state bullying laws passed between 1999 and 2011.

Source: Stuart-Cassel, Bell, & Springer, 2011 .

Despite the widespread adoption and application of anti-bullying policies within the United States and in other countries, relatively few studies have examined the effectiveness of these interventions. Instead, research has focused on programmatic interventions (e.g., Cool Kids Program, Fear Not!, Friendly Schools, KiVa, and Steps to Respect). Numerous systematic or meta-analytic reviews have been completed on the effectiveness of programmatic interventions for school bullying (e.g., Baldry & Farrington, 2007 ; Evans, Fraser, & Cotter, 2014 ; Ferguson, San Miguel, Kilburn, & Sanchez, 2007 ; Lee, Kim, & Kim, 2013 ; Merrell, Gueldner, Ross, & Isava, 2008 ; Ttofi & Farrington, 2011 ). However, a systematic review of the literature on the effectiveness of policy interventions for school bullying has not been completed.

Given the proportion of students directly or indirectly involved in bullying, the array of educational and psychological problems associated with bullying, the extensive adoption of anti-bullying policies, and the absence of a review of the research on these policy interventions, the need for a systematic review on this topic is imperative. The following questions drove this review: Are school policies effective in reducing or preventing bullying behavior among students? What is the state or quality of the research on school bullying policy effectiveness? What additional research is needed on school bullying policy effectiveness? Given these questions, the objectives of this review were threefold: to systematically identify, examine, and evaluate the methodological characteristics of studies investigating the effectiveness of school bullying policies; to summarize the substantive findings from these studies; and to provide recommendations for future research.

In preparation of this review, the author adhered to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) criteria ( Moher, Liberati, Tetzlaff, & Altman, 2009 ). Before undertaking the search for relevant studies, the author developed protocols for bibliographic database searches, study inclusion and exclusion criteria, and a data extraction tool. In addition, this review was registered with PROSPERO, an international database of systematic reviews regarding health and social well-being.

Search Procedure

A behavioral and social sciences librarian was consulted to assist with developing a search string and identifying relevant computerized bibliographic databases in which to search. The following search string was used to search all databases for studies published between January 1, 1995, and November 8, 2014: school AND bullying AND (law OR policy OR policies OR legislation OR statute) AND (effect OR effects OR effectiveness OR efficacy OR impact OR influence). The search of multiple databases increased the likelihood of identifying all possible studies falling within the scope of the review; thus, the author searched 11 databases, some of which included gray literature sources (e.g., conference papers, government reports, and unpublished papers). Searches were performed in the following databases via EBSCO using terms searched within the abstracts: CINAHL (Cumulative Index to Nursing and Allied Health Literature), Educational Full Text, ERIC (Education Research Information Center), PsycINFO, and Social Work Abstracts. The following databases were searched via ProQuest using terms searched within the titles, abstracts, and subject headings: ASSIA (Applied Social Sciences Index and Abstracts), Dissertations & Theses Full Text, and Social Services Abstracts. In addition, the Conference Proceedings Citations Index was searched using terms searched within titles, abstracts, and keywords. Finally, PubMed was searched using terms searched within titles and abstracts. These more formal bibliographic database searches were supplemented with internet searches using Google Scholar.

Inclusion Criteria

Studies were included in the review if they met the following criteria: (a) collected data and reported results on the effectiveness of policy interventions for bullying in school settings; (b) written in English; and (c) completed since January 1, 1995. Policy interventions for bullying were defined as statutes, policies, regulations, or rules established at the national, state, district, or school levels with the goal of reducing bullying in K–12 schools. Effectiveness referred to the extent to which a policy intervention prevented or reduced student bullying behavior. Given that school bullying policy is a nascent area of empirical inquiry with relatively few empirical investigations and evaluations, the author did not use stringent exclusion criteria in terms of study designs and methods. Only studies written in English were included due to the researchers’ language proficiency. Finally, the time period selected allowed for a comprehensive and contemporary review of the empirical literature completed in this area over the past 20 years.

Study Screening

After performing the bibliographic database searches, 481 results were imported into the RefWorks program to assist with organization and duplicate removal. Following duplicate removal, 414 studies remained. An additional 8 studies were added from Google Scholar searches that were not present among the 414 studies. The author and a trained research assistant independently screened each of the 422 studies to determine eligibility. A checklist of the inclusion criteria was created prior to the search and was used for eligibility assessment. Studies had to meet all three inclusion criteria to be screened in. Most studies were included or excluded after reading the title and abstract; however, it was also necessary to examine the full source document of some studies to determine eligibility. To examine interrater agreement, the decisions of the two screeners were compared, and Cohen’s kappa was calculated with SPSS (Version 21), which showed excellent agreement: kappa=0.97, p < .05 ( Landis & Koch, 1977 ). There were only six disagreements between the screeners, which were resolved by the author examining the source documents. After screening, 401 studies were excluded because they did not meet all of the inclusion criteria. The most common reasons for exclusion included papers that were not empirical, lack of evaluation of effectiveness, lack of evaluation of policy, and studies that were not conducted in schools. After completing the search and screening processes, 21 studies were included for extraction and review ( Figure 1 ).

Flow diagram depicting the identification, screening, and inclusion of studies.

Data Extraction

A data extraction sheet was developed to assist with identifying and collecting relevant information from the 21 included studies. Information extracted included the citation, purpose of the study, study design, sampling strategy and location, response rate, sample size and characteristics, measurement of relevant variables, analyses performed, and results and findings. The author extracted this information and a research assistant then compared the completed extraction sheets with the source documents to assess the accuracy of the extractions. There were only six points of disagreement between the extractor and checker, which they then resolved together by examining the source documents and extractions simultaneously.

Data Synthesis

Initial review of the included studies revealed that a quantitative synthesis, such as a meta-analysis, was not advisable due to the methodological heterogeneity of the studies and differences in approaches to evaluating policy effectiveness. Thus, a narrative thematic synthesis approach was used ( Thomas, Harden, & Newman, 2012 ). The substantive findings on policy effectiveness were first categorized based on the outcome evaluated and then synthesized within each category.

A total of 21 studies were included in this review: 9 peer-reviewed journal articles, 6 research reports that were not peer-reviewed, 5 doctoral dissertations, and 1 master’s thesis. A summary of the methodological characteristics of these studies is presented—including a synthesis of the substantive findings regarding the effectiveness of school bullying policies—in Table S1 (available online).

Methodological Characteristics of the Studies

Of the 21 studies, 12 (57%) used mixed methods, 8 (38%) used quantitative methods, and 1 (5%) used qualitative methods. All studies relied on cross-sectional designs. Most studies (65%) used convenience sampling, whereas the remaining studies used some form of probability sampling. More than half (57%) of studies used national samples, whereas 24% used samples from a single city or local region, 15% used statewide samples, and 5% used samples from areas in multiple countries. Over 80% of studies sampled participants in the United States, with other studies drawing participants from Europe, Australia, East Asia, and Southwest Asia. The most common recruitment sites were schools, followed by listservs, websites, community groups or organizations, professional associations, and personal contacts. Most studies reported participant response rates which varied from 21% to 98%, and the average response rate across studies was 57% ( SD = 29%). Eight studies did not report response rates.

Across studies, sample sizes varied from 6 to 8,584 participants. Only the qualitative study had fewer than 50 participants, and two studies had between 50 and 100 participants. Most studies had relatively large samples with more than 500 respondents. The most commonly used participants were students, followed by teachers. Other respondents included administrators, school psychologists, school counselors, education support professionals, and parents. About one third of studies included multiple participant groups (e.g., students and teachers). Most studies (62%) recruited participants from K–12 settings, whereas other studies recruited participants from a single school level: elementary, middle, or high school. Among adult participants, about 75% were female and 90% were White. These percentages are similar to those reported by the U.S. Department of Education, which show that 76% of teachers are female and 82% are White ( Snyder & Dillow, 2013 ).

Samples of students were diverse in terms of race/ethnicity, with most studies consisting of about two-thirds White participants as well as Black, Hispanic/Latino/Latina, Asian, Native American Indian, Middle Eastern, and multiracial students. In addition, student samples were closer to having equal proportions of males and females. Five studies included student participants who were exclusively lesbian, gay, bisexual, transgender, or queer (LGBTQ), whereas 6 studies did not report information about student sexual orientation or gender identity. In addition, studies typically did not measure or report participant national origin, immigrant/citizenship status, religious identity, socioeconomic status, or ability/disability status. Finally, most students were high school students.

Evaluation methods

All studies relied on self-report data to evaluate school bullying policy effectiveness. However, studies varied based on the outcome used in their evaluations: Eight studies examined school members’ perceptions of policy effectiveness, 5 studies examined student bullying perpetration and/or victimization behaviors, 6 studies investigated anti-LGBTQ bullying victimization, and 2 studies considered educator intervention in bullying. The level of policies evaluated also varied: Eleven studies examined school-level policies, 3 studies examined district-level policies, 3 studies examined state laws, 3 studies examined both state laws and school-level policies, and one study examined a national policy.

Studies also varied in terms of the analytic approaches used to evaluate effectiveness: Nine studies used bivariate analyses, 8 studies used descriptive statistics of perceived effectiveness, 3 studies used multivariate analyses, and one study used both bivariate and multivariate analyses. Studies that used a bivariate analytic approach compared measures of teachers’ responsiveness to bullying or measures of student bullying between those in schools with and without anti-bullying policies or between schools with high- versus low-quality anti-bullying policies. In these studies, distinctions between high- and low-quality policies were made by the researchers in each study using content analyses of policy strategies that were theoretically and empirically associated with effectiveness in the bullying literature (e.g., having a definition of bullying, ensuring adult supervision of students, and outlining consequences for bullies; Ordonez, 2006 ; Woods & Wolke, 2003 ). Policy content analysis scores were then used to distinguish between high- and low-quality policies. Descriptive statistical analyses of effectiveness entailed participants responding to a single self-report item about their perceptions of policy effectiveness (e.g., “How effective do you feel that your school’s anti-bullying policy is in reducing bullying?”), with Likert-type response options related to agreement/disagreement or categorical response options (e.g., yes or no). Multivariate analytic approaches primarily used student bullying scores as the dependent variable and either a continuous anti-bullying policy score or a dichotomous variable indicating whether or not the school had an anti-bullying policy as the independent variable. Continuous school bullying policy scores were based on either a set of items about the perceived presence of an anti-bullying policy (e.g., “I think my school clearly set forth anti-bullying policies and rules”) or a content analysis of policy documents to identify the presence of criteria or strategies associated with effectiveness (e.g., having a definition of bullying, establishing procedures and consequences for bullies, having educational events about the school’s bullying guidelines, ensuring adult supervision in school areas prone to bullying, and formulating a school task group to coordinate anti-bullying efforts).

The measures used to assess bullying among students varied; some studies used established scales (e.g., Olweus Bullying Questionnaire), whereas other studies used items developed by the researchers. The number of items used to measure bullying varied from 3 to 23 ( M =18.2, SD =6.1). Of the 11 studies that measured bullying, the majority measured bullying victimization ( n = 8). Only 2 studies measured both bullying victimization and perpetration, and one study measured just perpetration. In terms of the types of bullying measured, 5 studies measured physical, verbal, social, electronic, and sexual bullying; 3 studies measured physical, verbal, and social bullying; one study measured physical, verbal, social, and electronic bullying; one study measured physical, verbal, social, and property bullying; and one study measured verbal bullying. In addition to student bullying, educators’ responsiveness to bullying was another outcome variable that was used in 8 studies. Only one study used a scale to measure educator responsiveness, and the remaining 7 studies used one to four items regarding educators responding to student bullying.

Results on Policy Effectiveness

Given that the 21 studies differed on the outcomes used in their evaluations of school bullying policy effectiveness, substantive results are presented by each outcome category: school members’ perceptions of policy effectiveness, student bullying perpetration and/or victimization, anti-LGBTQ bullying victimization, and educator intervention in bullying.

Perceptions of policy effectiveness

Eight studies reported results on participants’ perceptions of policy effectiveness. Results showed that 5% to 88%( M =49.4%, SD = 33.4%) of educators perceived school bullying policies to be effective to some degree, 4% to 79% ( M =24.5%, SD =23.6%) of educators perceived policies to be ineffective , and 16% to 70% ( M =51.3%, SD =30.6%) of educators were uncertain about policy effectiveness ( Barnes, 2010 ; Bradshaw, Waasdorp, O’Brennan, & Gulemetova, 2013 ; Hedwall, 2006 ; Isom, 2014 ; Sherer & Nickerson, 2010 ; Terry, 2010 ). Only one study measured students’ perceptions of policy effectiveness, and results showed that they perceived policies to be moderately effective ( Ju, 2012 ). In addition, only one of the 21 studies collected multiple waves of data, although different sets of respondents were used at each of the two waves ( Samara & Smith, 2008 ). In this study, researchers examined perceived effectiveness before and after the passage of an anti-bullying policy; however, there were no significant changes in perceived effectiveness.

Student bullying perpetration and victimization

Five studies reported findings on the influence of policy on general student bullying outcomes. Two of these 5 studies examined policy content in relation to effectiveness. One study found that students in schools with high-quality bullying policies reported lower rates of verbal and physical bullying victimization than students in schools with low-quality policies; however, no differences were found for social/relational or property bullying victimization ( Ordonez, 2006 ). In this study, policy quality was evaluated based on the inclusion of the following elements: a definition of bullying; procedures and consequences for bullies; plans for disseminating the policy to students, school personnel, and parents; programs or practices that encourage acceptance of diversity, empathy for others, respect toward others, peer integration, and responsible use of power; supervision of students in school areas prone to bullying (e.g., playground, cafeteria, and hallways); and socio-emotional skills training for victims and bullies ( Ordonez, 2006 ). Similarly, another study found lower rates of verbal, physical, and property bullying victimization among students in schools with high-quality bullying policies, yet higher rates of social/relational bullying perpetration ( Woods & Wolke, 2003 ). In this study, policy quality was evaluated based on the inclusion of the following elements: a definition of bullying; recognition of negative outcomes associated with bullying; discussion of locations where bullying can occur; evaluation of the prevalence of bullying; involvement of stakeholders in policy development; supervision of students in school areas; formulation of a school task group to coordinate anti-bullying efforts; classroom rules about bullying; classroom sessions about bullying; discussion of bullying at PTA/PTO meetings; involvement of parents in bullying prevention efforts; and follow-up with victims and bullies after incidents ( Woods & Wolke, 2003 ).

Other studies examined associations between policy presence and bullying outcomes. Three significant or marginally significant ( p ≤ .095) associations were found: the presence of an anti-bullying policy was inversely related to general bullying victimization, social/relational bullying perpetration, and verbal bullying perpetration ( Farrington & Ttofi, 2009 ; Lee, 2007 ). Conversely, eight nonsignificant associations were found between school bullying policy presence and scores of general, physical, verbal, and social/relational bullying perpetration, as well as physical, verbal, and social/relational bullying victimization ( Farrington & Ttofi, 2009 ; Khoury-Kassabri, 2011 ; Lee, 2007 ). In addition, having a bullying policy was not associated with increases in general bullying perpetration or victimization ( Farrington & Ttofi, 2009 ).

Anti-LGBTQ bullying

Six studies with rather large samples of primarily LGBTQ students consistently found that compared to students in schools without an anti-bullying policy or with an anti-bullying policy that did not explicitly prohibit bullying based on sexual orientation and gender identity, students in schools with comprehensive anti-bullying policies that included protections based on sexual orientation and gender identity reported lower rates of anti-LGBTQ bullying, more school personnel frequently intervening when anti-LGBTQ comments were made in their presence, and more school personnel being effective in their anti-LGBTQ bullying responses ( Kosciw&Diaz, 2006 ; Kosciw, Diaz,&Greytak, 2008 ; Kosciw, Greytak, Diaz, & Bartkiewicz, 2010 ; Kosciw, Greytak, Bartkiewicz, Boesen, & Palmer, 2012 ; Kosciw, Greytak, Palmer, & Boesen, 2014 ; Phoenix et al., 2006 ). These differences were consistent in analyses of both local anti-bullying policies and state anti-bullying laws.

Educator intervention in bullying

Educators play a key role in reducing bullying behavior among students. One study found that compared to those in schools without a bullying policy, educators in schools with bullying policies were more likely to enlist the help of parents and colleagues in responding to a bullying incident and were less likely to ignore bullying ( Bauman, Rigby, & Hoppa, 2008 ). Conversely, a large, national study of educators found no relationship between having an anti-bullying policy and educators’ comfort intervening in both general and discriminatory bullying ( O’Brennan, Waasdorp, & Bradshaw, 2014 ).

The findings are discussed according to the research questions that drove the review.

Are Policies Effective at Reducing Bullying?

Educators were divided in their perceptions of the effectiveness of policies for school bullying; however, on average, about twice as many educators reported that policies were effective to some degree as those who reported that they were not effective. Nonetheless, descriptive summaries of perceptions of effectiveness are typically not viewed as compelling sources of evidence for the effectiveness of an intervention ( Petticrew & Roberts, 2003 ). However, educators are considered key informants who know what goes on in schools.

Two studies found lower rates of verbal and physical bullying in schools with high- rather than low-quality policies; however, in terms of social/relational bullying, one study found no difference, and another study found higher rates of social/relational bullying in schools with high-quality policies ( Ordonez, 2006 ; Woods & Wolke, 2003 ). This tentative finding suggests that improving the quality of bullying policies may be effective for direct and overt forms of bullying (e.g., hitting and name-calling) but may not effect social/relational bullying. Across the two studies, elements of policy quality associated with decreases in verbal and physical bullying included a comprehensive definition of bullying; school and classroom rules and procedures about bullying; plans for communicating the policy within the school community; supervision of students across school areas; involvement of parents in anti-bullying efforts; involvement of multiple stakeholders in school-wide anti-bullying actions; and working with and educating students around social, emotional, and behavioral issues to prevent bullying. Extant policies may overemphasize traditional notions of what bullying is (i.e., physical and verbal harassment) and underemphasize or neglect to address more recent understandings of social/relational aggression as bullying. In addition, direct and overt forms of bullying may be more amenable to policy interventions because educators can directly observe these behaviors and then proceed with their response, whereas social/relational bullying often occurs away from the direct supervision of educators ( Young, Nelson, Hottle, Warburton, & Young, 2013 ). Educators have reported difficulty in responding to bullying incidents that they did not witness ( Mishna, Pepler, & Wiener, 2006 ). Similarly, although many educators are aware of cyberbullying, few take steps to address it and many are uncertain about how to confront cyberbullying, which often occurs outside of school ( Cassidy, Brown, & Jackson, 2012 ; Stauffer, Heath, Coyne, & Ferrin, 2012 ; Vandebosch, Poels, & Deboutte, 2014 ). Nonetheless, educators can address cyberbullying occurring on or off school grounds if the aggression creates a hostile school environment and substantially disrupts a student’s learning environment ( Stuart-Cassel et al., 2011 ).

Findings among the few studies that examined associations between policy presence and student bullying were mixed, although more nonsignificant than significant associations were found. At first glance, one may conclude from these findings that the presence of bullying policies does not influence bullying among students; however, the presence of a policy is necessary but is not sufficient to affect student behavior. Indeed, after a policy has been adopted, it must be put into practice. The mere adoption or presence of a policy does not mean that it will be immediately and consistently put into practice exactly as intended. The implementation of a policy is a complex, dynamic, and ongoing process involving a vast assortment of people, resources, organizational structures, and actions. No study that examined the implementation of school bullying policies found that the policies were being implemented precisely as intended ( Hall & Chapman, 2016a , 2016b ; Hedwall, 2006 ; Holmgreen, 2014 ; Jordan, 2014 ; LaRocco, Nestler-Rusack, & Freiberg, 2007 ; MacLeod, 2007 ; Robbins, 2011 ; Schlenoff, 2014 ; Smith-Canty, 2010 ; Terry, 2010 ). Indeed, the extent of faithful implementation in these studies varied considerably by location and policy component. Therefore, fidelity of implementation (i.e., the extent that a policy is put into practice as intended based on the directives expressed in the policy document) may mediate the relationship between policy adoption or presence and the targeted policy outcome of student bullying. However, none of the studies reviewed measured policy implementation fidelity. Thus, one can conclude from this evidence that in some cases, policy presence was associated with decreases in bullying; in other cases, however, there were no such associations. Because data on implementation were not collected in any study, it is not known if the lack of significant associations was related to lack of faithful implementation of policies.

One area of consistent agreement in the findings relates to the benefits for LGBTQ students who are in schools with anti-bullying policies that explicitly provide protections based on sexual orientation and gender identity. These benefits included lower rates of victimization and higher rates of intervention by educators. Numerous studies have demonstrated that LGBTQ youths experience high rates of bullying victimization ( Berlan, Corliss, Field, Goodman, & Austin, 2010 ; Espelage, Aragon, Birkett, & Koenig, 2008 ; Kosciw & Diaz, 2006 ; Kosciw et al., 2008 ; Kosciw et al., 2010 ; Kosciw et al., 2012 ; Kosciw et al., 2014 ; McGuire, Anderson, Toomey, & Russell, 2010 ; Varjas et al., 2008 ). However, only 20 states (40%) have enumerated protections based on sexual orientation and gender identity/expression in their anti-bullying laws ( Human Rights Campaign, 2015 ). Given the evidence for the effectiveness of enumerated policies, all policies should prohibit harassment and bullying based on sexual orientation and gender identity.

Aside from the LGBTQ-focused studies, only two other studies examined educators’ responsiveness to bullying. Findings from these studies were somewhat contradictory, as one found a connection between having a bullying policy and responding to a bullying incident, whereas the other study found no relationship between having a policy and educators’ comfort in responding to bullying. However, the study that found no relationship included several other relevant independent variables (i.e., receiving training on how to implement the school’s bullying policy and having resources available in the school to help educators intervene), which were significantly associated with increased comfort in responding to bullying ( O’Brennan et al., 2014 ). Thus, the relationship between the presence of a school bullying policy and educators’ responsiveness to bullying incidents may be mediated by training about putting the policy into practice and having resources available for intervention.

Finally, there was no evidence that one level of policy was more effective than another. Across the studies, school, district, and state policies all showed evidence for effectiveness as well as ineffectiveness. Policies do vary in terms of their weight in law. For example, a state statute has more legal force than an informal school policy established by a principal. Nonetheless, a school policy set by a principal is more proximal than a state policy, and therefore, the proximity may facilitate implementation of the policy at the school. Policy level may not be related to effectiveness. What likely matters more in terms of effectiveness are the strategies contained within a policy and the ways they are implemented.

What is the State of the Research on School Bullying Policy Effectiveness?

Systematic reviews summarize what is substantively known about a topic area and also provide a state of the research on a particular topic. Research to date on school bullying policy effectiveness has several strengths. In terms of designs, most studies have used a mixed-methods approach, which is advantageous because it capitalizes on the strengths of both quantitative and qualitative research and offsets weaknesses of using one or the other. Including quantitative methods allows for precise, numerical estimates related to distribution or the strength and direction of relationships, and including qualitative methods allows for rich, in-depth data related to context or complexity. Other strengths are related to sampling: More than one third of the studies used some form of probability sampling, over half of the studies used national samples, and many studies reported high response rates. These sampling strengths are beneficial in terms of generalizing findings. Also, almost all studies had sample sizes greater than 200, and two thirds of studies had large samples (i.e., approximately 500 to 8,500 participants). Larger samples can be more representative of a population and are beneficial in terms of statistical power. A final strength was that many studies collected data from multiple participants groups (e.g., teachers and students). Having multiple participant groups allows for a more comprehensive assessment and the triangulation of data sources, which can be used to compare and contrast findings and may help researchers corroborate findings.

On the other hand, several prominent methodological limitations were identified among the studies reviewed. First, the studies relied on evidence from cross-sectional surveys, which are vulnerable to selection bias and confounding. In addition, cross-sectional studies cannot examine a key criterion of causality: a temporal relationship wherein an anti-bullying policy was adopted and implemented, which then led to decreases in bullying over time. Second, most studies used convenience sampling. Although convenience sampling may be highly feasible and efficient, it can lead to the under representation or overrepresentation of particular groups within a sample. Thus, convenience samples may not be representative of the populations of interest, which undermines the generalizations that can be made from the findings. Third, most of the studies used descriptive statistics or bivariate analyses to evaluate the effectiveness of bullying policies. Such analyses can be oversimplified and leave out relevant explanatory or contextualizing variables. In addition, some of the studies that used bivariate analyses did not report the exact statistical test used (e.g., independent groups t-test and chi-square test) or effect sizes and instead focused on substantive findings. Although these reports seemed to be aimed at a more general, nonscholarly audience, the omission of this information can become problematic in understanding the methods used and drawing conclusions about the results. Fourth, many studies asked participants to report whether their school had an anti-bullying policy. This question might be problematic for student respondents because they might not know about the policies in their schools.

A final limitation involved the measurement of bullying. The main goal of policy interventions for bullying is to prevent and reduce bullying behavior among students. Thus, studies evaluating the effectiveness of these interventions should measure bullying among students as a primary outcome. Nonetheless, only half of the studies directly measured student bullying, and most of these studies did not measure both bullying perpetration and victimization. Policies are aimed at influencing multiple actors involved in the bullying dynamic, which includes bullies, targets, victims, bully–victims, bystanders, parents, and school personnel. Thus, studies that do not measure bullying perpetration and victimization among students are not assessing the two main targeted behavioral outcomes of anti-bullying policies. In addition, bullying behaviors can manifest in many forms, including physical bullying, verbal bullying, social/relational bullying, cyberbullying, property bullying, and sexual bullying ( Hall, 2016 ). However, none of the studies in this review measured all of the dimensions of bullying.

What Future Research is Needed on School Bullying Policy Effectiveness?

Undoubtedly, research on the effectiveness of policy interventions for school bullying will continue to expand. In order to build upon and address gaps and limitations in the extant literature, six recommendations are presented for future research on school bullying policy effectiveness. These recommendations are based on the critical analysis of studies in this systematic review.

First, future studies should employ more rigorous designs to evaluate the effectiveness of policy interventions for bullying. The randomized controlled trial (RCT) is the “gold standard” approach for measuring the impact of an intervention; however, RCTs are often infeasible for evaluating public policy interventions due to the political and legal nature of policies, which are implemented across large organizational systems and typically with prescribed timelines ( Oliver et al., 2010 ). Thus, researchers may need to rely on other rigorous and feasible designs for evaluating policy effectiveness: pretest/posttest cohort designs, pretest/posttest matched comparison group designs, and interrupted time series designs ( Oliver et al., 2010 ; Shadish, Cook, & Campbell, 2002 ). These study designs are superior to cross-sectional studies in determining the effectiveness of interventions ( Coalition for Evidence-Based Policy, 2003 ; Petticrew & Roberts, 2003 ; Pilcher & Bedford, 2011 ).

Second, studies should collect data on outcomes and the implementation of policy components. None of the studies assessed implementation fidelity. When bullying policies do not successfully achieve targeted outcomes, we do not know whether those policies were implemented as intended and failed or whether lack of implementation fidelity is to blame. Implementation data, if collected, could be used to ensure that policies are being activated as intended with high levels of fidelity and reported along with outcome evaluation data in the study designs mentioned previously. These data also could be used to examine the predictive relationship between implementation fidelity and outcomes. Theory would suggest an inverse relationship where higher levels of implementation fidelity are associated with lower levels of bullying among students; however, this remains an untested hypothesis. Also, bullying policies are comprised of an array of directives to be put into action. Data on the fidelity of implementation of all components of an anti-bullying policy would allow researchers to examine the relative or combined impact of policy components on outcomes.

Third, analyzing policy content—versus only considering the presence of absence of a bullying policy—is needed for more nuanced understanding of which policies work, for whom, and why. A national review of state anti-bullying laws showed broad inclusion of some policy components (e.g., outlining the consequences for students who bully) and limited inclusion of other components (e.g., providing mental health services to perpetrators or victims of bullying; Stuart-Cassel et al., 2011 ). Theoretically and empirically based guidance about specific actions that can be prescribed in bullying policies is small but growing ( Cornell & Limber, 2015 ; Nickerson, Cornell, Smith, & Furlong, 2013 ). Future research should analyze the relationships between policy content and bullying outcomes, which could help identify the most influential policy components. Examining only policy presence or absence is insufficient because a school district may indeed have an anti-bullying policy, but its content may not be evidence-based. Policies can also vary in the way they are written, as some policies are lengthy, vague, and contradictory, whereas other policies are clear, concise, and specific. This area of content could also be analyzed and may relate to educators’ comprehension of policies, which would influence implementation actions by educators, and subsequently, policy outcomes.

Fourth, future studies should use multivariate and multilevel analyses. The effectiveness of policy interventions for bullying are influenced by several variables, including policy content, fidelity of implementation, and school environmental factors. By using more complex statistical methods (e.g., regression modeling, structural equation modeling, propensity score matching, and hierarchical linear modeling), researchers will be able to examine the influence of multiple variables, examine moderating and mediating relationships, control for extraneous variables, match intervention participants with control participants, and account for clustered data (e.g., students or teachers nested within schools). These statistical methods will be essential to execute the recommended study designs and analytic methods described previously. The use of these statistical methods will help ensure the integrity of future findings on policy effectiveness.

Fifth, studies should improve sampling practices. To attain more representative samples, researchers should partner with school districts, state departments of education, and departments of public instruction, and they should employ some form of probability sampling. Many of the studies in this review that used probability sampling involved data collection collaborations with state- and district-level educational agencies. Educational agencies have a vested interest in the implementation and success of bullying policies, especially those codified as law. In addition, future studies should sample from multiple respondent groups—such as administrators, teachers, school mental health professionals, and students—to gain a more comprehensive and multiperspective understanding of the implementation and effectiveness of school bullying policies. Researchers also should sample across the K–12 spectrum because state and district policy guidelines typically apply across these grade levels. Yet, there may be differences in policy effectiveness between elementary, middle, and high school. Certain policy strategies also may need to be tailored based on student developmental differences and differences in school structure across the K–12 system.

Finally, future studies should use scales to measure both bullying perpetration and victimization, and these measures should assess all of the dimensions of bullying: physical, verbal, social/relational, electronic, sexual, and property bullying. Researchers may find that policies are more effective at addressing certain types of bullying than others (e.g., direct vs. indirect bullying). Multifactor scales with a sufficient number of items are needed to measure the full range of bullying behaviors. The Centers for Disease Control and Prevention created a compendium of bullying measures that is available to the public (see Hamburger, Basile, & Vivolo, 2011 ). However, caution should be taken in selecting instruments because some measures have low internal consistency reliability values (i.e., α < .70), low test-retest reliability coefficients (i.e., r < .70), no recall time frames, overly long and complex definitions of bullying, limited evidence of construct validity, limited evidence of criterion validity, and limited evidence regarding respondents’ understanding of the measure’s instructions and items ( Hall, 2016 ). In addition, as opposed to questionnaires about bullying behaviors, peer and/or teacher nomination methods to identify students who are bullying victims or perpetrators may be more developmentally appropriate for elementary school-age children.

Strengths and Limitations of the Review

This review used a rigorous approach to identify relevant studies by searching 11 databases using an expert-informed search string. In addition, search records were independently screened by two screeners based on a priori inclusion criteria. Further, research reports and dissertations (forms of gray literature) were included to minimize publication bias. Nonetheless, unpublished research may be underrepresented in this review. Another limitation relates to the variability of studies: Studies varied in the respondents, sample locations, the types of policies examined, and the ways effectiveness was evaluated. This variability presented challenges for combining and comparing results. Another limitation of this review relates to the methodological limitations of some of the included studies. However, by presenting the methodological characteristics and substantive findings by study in Table S1 (available online), readers are able to assess the methodological rigor and trustworthiness of findings accordingly.

Bullying is a widespread problem in which about half of students are directly involved and up to 90% of students are indirectly involved ( Atlas &Pepler, 1998 ; Cook, Williams, Guerra, & Kim, 2010 ; Craig & Pepler, 1995 ; Glew et al., 2005 ; Hawkins et al., 2001 ). Policy interventions are an approach to bullying that establishes legal mandates for schools, influences the behavior of students and school personnel, and guides the implementation of other targeted interventions within schools. Findings on the effectiveness of policy interventions for bullying are primarily mixed, and there are limitations in the evaluation methods used. Research on school bullying policy will undoubtedly continue to expand with the growing understanding of the need for evidence-based education policies and as bullying policies continue to be introduced and revised in schools across the globe. Future research must use more rigorous methods and designs and may indeed find that policy interventions play a key role as one of a constellation of intervention strategies for preventing and reducing school bullying.

Supplementary Material

Acknowledgments.

I would like to thank Mimi Chapman, Natasha Bowen, Barbara Fedders, Mark Fraser, and Kathleen Rounds for their advice and feedback regarding this paper. I also thank Rachele McFarland for her research assistance. The author was supported by the National Research Service Award Postdoctoral Traineeship from the National Institute of Mental Health, sponsored by Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, and the Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine (grant number T32 MH019117).

* Asterisks indicate studies that were included in the systematic review.

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Action Research: Bullying - A Proposal

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A new model for science funding

29 May 2024

Science and technology , Auckland Bioengineering Institute , Faculty of Medical and Health Sciences

Opinion: The Government is looking for a new model of science funding, so along with a small group of senior scientists and engineers we've come up with some recommendations.

New Zealand science is at a crunch point. The coalition Government is looking for a new model to provide increased efficiency and effectiveness. Over the last few weeks, we have been part of a small group of senior scientists and engineers who got together to think about what this change might look like, and we have just submitted our recommendations to the Science System Advisory Group. Here are some of our thoughts.

Research matters

Research funding should not be seen as a luxury for the benefit of an elite few to satisfy their scientific curiosity, but rather as an essential investment in the country’s prosperity. If we don’t invest in innovation, we will not maintain our quality of life.

In 2021 the combined investment by the New Zealand Government and industry was 1.47 percent which compares with Australia 1.66 percent, Denmark 2.89 percent, the UK 2.0 percent and Sweden 3.41 percent. The OECD report puts New Zealand Government funding at 0.29 percent of GDP (OECD average is 0.5 percent). As much of that isn’t linked to inflation, the actual budget for funding research has been eroded substantially.

New Zealand’s science community is relatively small but highly connected. We must avoid parochialism and exploit complementary skill sets and resources across the whole country. We would like to see more Centres of Research Excellence along the lines of the present CoREs, but with a clear mandate to deliver outputs in both basic and applied science and, in combination with industry, to deliver outcomes that have health, social, environmental, educational or economic impact for the New Zealand taxpayer.

Working with industry

The national university sector needs to have much greater connection with end-users. This could be through creating more industry-linked PhD scholarships, encouraging more internships, or providing incentives for universities and industry to work together. Growing industry-academic engagement would enhance innovation in industry, provide more relevance for some university research, and enhance job opportunities for postgraduate research students. The UK and Australia have introduced ‘doctoral training programmes’ – typically four-year PhD programmes (as opposed to the normal three-year model) which can include internships, clinical placements, project management and/or entrepreneurial skills training.

New Zealand and the world

If we want world-class research, our teams must participate in international science projects and apply to international science funding agencies. In assessing proposals, funders should formally prioritise those which intend to work with globally top-ranked researchers and institutions. This ensures that the quality of research is judged against international standards, allows researchers to tap into much larger research funds, and leads to new international collaborations and new career opportunities for graduating PhD students. It can also help with creating international connections for the startup companies that come out of research labs.

New Zealand has an opportunity to attract top international research students, particularly as anti-immigration policies in the US make that a less attractive option. The Government’s foresighted policies of allowing international PhD students to pay only domestic fees and granting these students post-study work rights, are critical to making us an attractive destination – we cannot afford to retreat on either. We should also look to ensure we reduce delays in processing student visas for graduate students – waiting several months is a significant deterrent.

Meanwhile, we need to invest more in getting talented young Kiwi scientists and engineers to return home after gaining overseas experience. The Rutherford Discovery Fellowships are valuable, but we need more of them and they need to offer more funding to make a difference.

Longer funding cycles

If we want significant economic outcome from scientific research, we need to take a longer-term approach to research funding. The typical three-year grant cycle is very challenging for continuity and momentum. Our current model of annual grant project submissions with no opportunity to revise and submit a better proposal is a wasteful barrier to innovation and many researchers can only survive by writing many grants for relatively small amounts of funding. In the US, for example, the National Institutes of Health has three funding cycles a year, and explicitly allows for resubmission and renewals. Funding agencies should also be required to provide much better feedback to failed applicants than they currently do.

Science equipment infrastructure

We urgently need a national fund for essential items of research equipment that are too expensive for one research group, or even one university, to fund. We cannot attract top quality people and we cannot do world-class science with second-rate equipment.

Innovation parks

We need innovation or technology development parks. Creating startup companies out of research labs is on the first step on the path to economic benefit, but these companies must be supported for many years as they grow to become self-sustainable. All require help with business management, IP protection, financial investment, dealing with regulatory issues (especially in the biotech and MedTech areas), and gaining access to national and international markets. Many also need access to resources such as clean rooms and specialised manufacturing equipment that is too expensive for a startup company but can easily be shared across a sector. Keeping these innovation parks close to the research heart of a university is important for access to the research skills and IP from the university, but also for ensuring that these companies help graduate students see the impact of their research.

Distinguished Professor Sir Peter Hunter, co-founder and former director of the Auckland Bioengineering Institute.

Professor Julian Paton, Faculty of Medical and Health Sciences, University of Auckland

Professor Kurt Krause, Department of Biochemistry, University of Otago

Distinguished Professor Geoff Chase, Faculty of Engineering, University of Canterbury

This article reflects the opinion of the authors and not necessarily the views of Waipapa Taumata Rau University of Auckland.

This article was first published on Newsroom, A new model for science funding, 29 May,. 2024

Media contact

Margo White I Research communications editor Mob 021 926 408 Email margo.white@auckland.ac.nz

Panel rejects psychedelic drug MDMA as a PTSD treatment in possible setback for advocates

WASHINGTON (AP) — A first-of-a-kind proposal to begin using the mind-altering drug MDMA as a treatment for PTSD was roundly criticized Tuesday — a potentially major setback to psychedelic advocates who hope to win a landmark federal approval and bring the banned drugs into the medical mainstream .

The panel of advisers to the Food and Drug Administration voted 10-1 against the overall benefits of MDMA when used to treat post-traumatic stress disorder. They cited flawed study data, questionable research conduct and significant drug risks, including the potential for heart problems, injury and abuse.

“It seems like there are so many problems with the data — each one alone might be OK, but when you pile them on top of each other … there’s just a lot of questions I would have about how effective the treatment is,” said Dr. Melissa Decker Barone, a psychologist with the Department of Veterans Affairs.

The FDA is not required to follow the group’s advice and is expected to make its final decision by August, but the negative opinion could strengthen FDA’s rationale for rejecting the treatment.

The vote followed hours of pointed questions and criticisms about the research submitted on MDMA — sometimes called ecstasy or molly. Panelists pointed to flawed studies that could have skewed the results, missing follow-up data on patient outcomes and a lack of diversity among participants. The vast majority of patients studied were white, with only five Black patients receiving MDMA, raising questions about the generalizability of the results.

“The fact that this study has so many white participants is problematic because I don’t want something to roll out that only helps this one group,” said Elizabeth Joniak-Grant, the group’s patient representative.

The FDA advisers also drew attention to allegations of misconduct in the trials that have recently surfaced in news stories and a report by the nonprofit Institute for Clinical and Economic Review , which evaluates experimental drug treatments. The incidents include a 2018 report of apparent sexual misconduct by a therapist interacting with a patient.

Lykos Therapeutics, the company behind the study, said it previously reported the incident to the FDA and regulators in Canada, where the therapist is based. Lykos is essentially a corporate spinoff of the nation’s leading psychedelic advocacy group , the Multidisciplinary Association for Psychedelic Studies, or MAPS, which funded the studies. The group was founded in 1986 to promote the benefits of MDMA and other mind-altering substances.

MDMA is the first in a series of psychedelics — including LSD and psilocybin — that are expected to come before the FDA in the next few years. The panel’s negative ruling could further derail financial investments in the fledgling industry, which has mainly been funded by a small number of wealthy backers.

MDMA’s main effect is triggering feelings of intimacy, connection and euphoria. When used to enhance talk therapy, the drug appears to help patients process their trauma and let go of disturbing thoughts and memories.

But the panel struggled with the reliability of those results, given the difficulties of objectively testing psychedelic drugs.

Because MDMA causes intense, psychological experiences, almost all patients in two key studies of the drug were able to guess whether they had received the MDMA or a dummy pill. That’s the opposite of the approach generally required for high-quality drug research, in which bias is minimized by “blinding” patients and researchers to whether they received the drug under investigation.

“I’m not convinced at all that this drug is effective based on the data I saw,” said Dr. Rajesh Narendran, a University of Pittsburgh psychiatrist who chaired the panel.

Panelists also noted the difficulty of knowing how much of patients’ improvement came from MDMA versus simply undergoing the extensive therapy, which totaled more than 80 hours for many patients. Results were further marred by other complicating factors, including a large number of patients who had previously used MDMA or other psychedelics drugs recreationally.

Nearly three dozen public speakers also addressed the panel, including veterans who said they benefitted from MDMA therapy, medical professionals who advised against its use and journalists and independent researchers who reiterated the allegations of misconduct in the trials.

The meeting concluded with several experts encouraging Lykos and the FDA to continue studying psychedelics, citing the field’s potential to help patients.

“I think this is a really exciting treatment and I’m encouraged by the results to date,” said Dr. Paul E. Holtzheimer of the VA’s National Center for PTSD, “but from a safety and efficacy standpoint I feel it’s still premature.”

The Associated Press Health and Science Department receives support from the Howard Hughes Medical Institute’s Science and Educational Media Group. The AP is solely responsible for all content.

Copyright 2024 The Associated Press. All rights reserved.

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