research on adolescence problems

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• HHS Author Manuscripts

Research on Adolescence in the Twenty-First Century

Robert crosnoe.

1 Department of Sociology and Population Research Center, University of Texas at Austin, Austin, Texas 78712

Monica Kirkpatrick Johnson

2 Department of Sociology, Washington State University, Pullman, Washington 99164-4020

Recent methodological advances have allowed empirical research on adolescence to do better justice to theoretical models. Organized by a life course framework, this review covers the state of contemporary research on adolescents' physical, psychological, interpersonal, and institutional pathways; how these pathways connect within primary ecological contexts; and how they relate to broader patterns of societal stratification and historical change. Looking forward, it also emphasizes three future challenges/opportunities, including efforts to illuminate biosocial processes, link adolescence to other life stages, and account for the influence of major social changes (e.g., the new media).

Introduction

First coined by Hall (1904) only a century ago, adolescence was “created” by the convergence of multiple trends, including labor and schooling laws, that extended dependency beyond childhood and delayed entry into adult roles ( Modell & Goodman 1990 ). Adolescence as a period of dependency and preparation for adulthood has since been reinforced through more recent social changes, including economic restructuring and changing cultural norms about parenting ( Goldin & Katz 2008 , Settersten et al. 2005 ). Research on adolescence has also changed dramatically. This review discusses recent developments in this literature, being cognizant of their historical underpinnings while focusing on the future. Given our background in the life course tradition, as well as the inherent importance of transitions, trajectories, and context to understanding this life stage, we use a life course framework to organize our review. Owing to space constraints, we focus primarily on American adolescents.

In his 1989 review, Dornbusch wrote that research on adolescence was turning from psychologists studying “individual adolescents carrying out their developmental tasks” (p. 233) to contextual approaches emphasizing transactions between adolescents and their environments. This trend has since intensified, reflecting refinements of theoretical models, including human ecology ( Bronfenbrenner & Morris 1998 ) and the life course paradigm ( Elder 1998 ). A central imagery of the latter, our focus here, is of lives as a tapestry of three threads—developmental trajectories (physical and psychological growth), social pathways (sequences of institutional roles and activities), and social convoys (continuity and change in interpersonal relations)—situated in settings of daily life, larger structures of society, and the broader sweep of history.

Unfortunately, studying this dynamic, multilayered model of adolescence has taxed methodological and data resources ( Elder & Giele 2009 ). Recently, however, data sets on children have aged into adolescence (e.g., Children of the National Longitudinal Survey of Youth), and data sets on adolescents have aged into adulthood (e.g., National Longitudinal Study of Adolescent Health, or Add Health). Data sets are also integrating biological, behavioral, and setting data. At the same time, significant advances in longitudinal and multilevel modeling have allowed researchers to capture individual and population trajectories and to identify person-context effects ( Bollen & Curran 2006 , Bryk et al. 2002 ). Of note is that qualitative and mixed methods research projects are also increasingly emphasizing context, longitudinal change, and the multiple strands of adolescent development ( Giordano et al. 2006 ).

In other words, sociologists are making progress on a more holistic understanding of adolescents in society. In reviewing this progress, we focus on each of the three main strands of the adolescent life course before turning to the ways in which their interweaving is embedded in ecological contexts and both reflects and contributes to population-level inequalities.

Three Threads in the Life Course Tapestry

Exhaustively reviewing recent research on the three main strands of the life course is impossible. As just one example, the United States has a high teen pregnancy rate that contributes to the overall rate of nonmarital fertility, and early parenthood relates to past and future socioeconomic disadvantages in complex ways ( Mollborn 2007 ). As a result, this topic could fill an entire review article, and in fact has ( Furstenberg 2003 ). Also regrettably left out are issues such as disordered eating and bullying. Consequently, this review should be viewed as an effort to put forward a limited set of illustrative examples of new ways to think about old issues.

Developmental Trajectories

Adolescence is a period of rapid change. This change is dramatically crystallized in the flood of hormonal activity and rapid physiological development that constitutes puberty ( Susman et al. 2003 ). Great psychological and emotional change also occurs during adolescence. In the years following puberty, adolescents are faced with the task of establishing their own identity separate from their parents, which may be stressful ( Kroger 2007 ). At the same time, rates of risky behavior (e.g., substance use, delinquency, sexual activity) also rise markedly, especially among boys ( Bachman et al. 2002 ). A hallmark of adolescence is that maturation can occur at different velocities in different domains of development, so that youth may look or feel like adults in some ways but not in others.

Beginning with puberty, a great deal of attention has been focused on pubertal timing, following earlier work outside the United States ( Stättin & Magnusson 1990 ). Primarily among girls, going through puberty earlier than the norm is associated with a host of adjustment problems, including risky sex and delinquency. Sociologists have elucidated many mechanisms underlying these patterns, which are not entirely hormonal or biological in nature. One concerns premature self- and other-perceptions of early maturers, especially girls, as adults. In other words, they are adult-like physically and, as a result, may engage in actions or put themselves in situations that are ahead of their emotional or cognitive capacities ( Cavanagh 2004 , Haynie 2003 ). Another mechanism is increased distress related to growing size in the context of strict norms about female body weight ( Ge et al. 2001 ). These socioemotional difficulties in early adolescence can then disrupt academic functioning ( Cavanagh et al. 2007 ). Pubertal timing, therefore, represents an intersection of biological, emotional, social, and institutional processes.

Turning to mental health, adolescence marks the emergence of gender differences in depression—with girls higher than boys—that persist for decades ( Hankin et al. 2007 ). Efforts to explain this trend have focused primarily on social psychological phenomena, including gender differences in self-concept, management of daily stressors, experiences of puberty, and the rigidity and enforcement of societal standards of appearance and behavior ( Martin 1996 , Rosenfield et al. 2000 ). A particularly insightful sociological approach to adolescent depression, regardless of gender, concerns how it is interpreted by others. For example, depression can be strongly stigmatized in social groups when it is perceived as mental illness as opposed to a health problem, leading depressed youth to be isolated from others just when they need more support ( Martin et al. 2007 ). Indeed, social responses to adolescent distress influence whether it can have long-term effects on other areas of life, including education ( McLeod & Fettes 2007 ). Thus, socialized perspectives on depression and other psychological constructs reveal insight into the complex dance between self and other that characterizes adolescence.

Identity development is another psychological process that has been studied from a variety of angles. The consensus is that it is a highly social process, with young people slowly integrating the different pieces of themselves that they come to understand through social interactions into a cohesive sense of who they are and where they fit in the world ( Kroger 2007 ). In the past two decades, considerable research has centered on the development of group-based identities. For example, racial identity taps into the significance and meaning attached to race within individuals' overall senses of self. According to work by Sellers and associates (1998) on African American youth, racial identity has four dimensions: ( a ) salience (how much race is part of one's self-concept), ( b ) centrality (whether one defines him or herself through race), ( c ) regard (the degree of positive or negative feelings about one's race), and ( d ) ideology (beliefs about how someone of a certain race should act). Across minority groups, these dimensions tend to increase as adolescence unfolds and are strongly related to mental health ( Mandara et al. 2009 , Umaña-Taylor et al. 2009 ). For the most part, the benefits of racial identity are strongest when minority adolescents have reached the achieved stage of identity development, meaning that they have committed to a particular identity after exploring what it means and what alternative identities might be possible ( Seaton et al. 2006 ). Similar research has been done on sexual identity, tracing the gradual process by which adolescents come to see themselves as homosexual and the role that this process plays in healthy development ( Russell & Sigler-Andrews 2003 ).

As for risky behavior, understanding why adolescents become more reckless even as they develop critical thinking skills has long been a major activity of adolescence researchers. One explanation is that adolescence is a time of heightened sensitivity to social influences and greater propensity toward emotional stimulation. These developmental changes have traditionally been viewed as by-products of identity development, but recent neurological research is shedding new light on this phenomenon ( Dahl & Spear 2004 ). Specifically, magnetic resonance imaging (MRI) studies suggest that increased risky behavior during adolescence reflects different rates of growth in the brain's socioemotional and cognitive control systems. After puberty, dopamine receptors increase rapidly in regions that control sensation-seeking, which encourages behaviors that bring some emotional or sensory reward ( Steinberg 2008 ). Peer approval is one such reward, and ample evidence indicates that engaging in some level of dangerous behavior can elicit peer esteem and popularity ( Allen et al. 2005 , Kreager & Staff 2009 ). Importantly, structural changes of equivalent magnitude do not occur in the prefrontal cortex, which controls cognition, until adolescents approach young adulthood. That enhanced self-regulation skills tend to come after the increased propensity toward sensation-seeking helps to explain the increase in risky behavior that characterizes the years between the end of childhood and the start of adulthood ( Dahl & Spear 2004 , Steinberg 2008 ). Clearly, other factors are also at work, including changing cultural norms about permissible behavior and increasing opportunities for engaging in certain behaviors, but neurological development is certainly a piece of the puzzle.

As is evident even from this very selective discussion, adolescent development crosses many different psychological, physiological, cognitive, and behavioral domains. As a result, understanding one domain often requires consideration of others.

Social Pathways

Beyond the family, two key institutions structure the social pathways of adolescence. Beginning with schools, sociologists have traditionally studied the organization of high schools via academic tracks (e.g., vocational, college preparatory). As formal tracking has been largely dismantled ( Lucas 2001 ), new organizational schemas have been identified, including patterns of course-taking, critical courses (e.g., advanced math), and course trajectories ( Gamoran & Hannigan 2000 , McFarland 2006 , Riegle-Crumb 2006 ). Math is a clear example, as it is highly structured and strongly predicts educational and occupational attainment ( Adelman 2006 , Frank et al. 2008 , Riegle-Crumb 2006 ). Case studies have yielded new insights on the implications of curricular structure. McFarland (2006) , for example, examined student flow across math courses in two high schools, one characterized by five math trajectories with fewer lower-ability courses over time, and the other with a branching tree structure in which students move from a single trunk into four eventual trajectories of increasing differentiation. In each structure, specific courses represent critical junctions between trajectories and in math persistence altogether.

Thus, students' school pathways are far more complex than the traditional view of tracking suggests. Studying these pathways also reveals new insights into gender differences in education. Girls have been surpassing boys in most academic domains in secondary and postsecondary education for some time, especially among African Americans. Research on coursework trajectories suggests that girls have now also closed the gap with boys in math and science in terms of the course credits they accrue in high school. However, despite their advantage in college enrollment and graduation ( Buchman & DiPrete 2006 ), they remain underrepresented in these curricula in college ( Riegle-Crumb 2006 ).

Studies in the past decade have also emphasized the changing role of higher education in adolescents' lives. Expectations to earn four-year and graduate degrees have risen dramatically, faster than actual attainment ( Jacob & Wilder 2010 , Reynolds et al. 2006 ). In line with a “college for all” norm ( Rosenbaum 2001 ), expectations to complete college have become less tied to social class and previous achievement ( Goyette 2008 , Reynolds et al. 2006 , Schneider & Stevenson 1999 ). More than 80% of high school seniors in 2008 reported that they would probably or definitely earn a four-year college degree ( Bachman et al. 2009 ). Some of the least educationally ambitious students may have dropped out of school before senior year and, therefore, would be absent from such statistics, but educational expectations are actually even higher when measured at eighth or tenth grade instead ( Goyette 2008 , Jacob & Wilder 2010 ). The rise in expectations to earn a college degree has been even steeper among girls, who now expect BAs at higher rates than boys, with little difference within gender between blacks and whites ( Jacob & Wilder 2010 ).

Commonly cited explanations for rising educational expectations include ( a ) an increase in the earnings payoff to college (versus high school) graduation; ( b ) expanding higher education options, including online degrees and community colleges; and ( c ) trends in the educational attainment of parents ( Berg 2007 , Goldin & Katz 2008 , Goyette 2008 , Schneider & Stevenson 1999 ). Regarding the latter, the relative risk aversion thesis suggests that adolescents strive for at least as much education as their parents have. As parents' average education levels rise across cohorts, therefore, so do adolescents' educational expectations ( Breen & Goldthorpe 1997 ).

Paid work is another institution shaping adolescence, with nearly all high school students employed during the school year at some point while in high school ( Apel et al. 2007 , Mortimer 2003 , National Research Council 1998 ). Building on foundational studies from the 1980s and 1990s, recent research has elucidated the mix of risks and benefits of paid work for adolescents. Although adolescent work often starts earlier, most studies focus on high school, when employment is more likely to occur in the formal sector and for longer hours. Moreover, school-year employment continues to garner the most attention, despite higher rates of summer employment ( Mortimer 2003 , Perreira et al. 2007 ). These foci reflect concerns about potentially competing demands of school and employment, key institutions that structure the social pathways of adolescence. The question is whether (or under what conditions) employment facilitates educational attainment and builds human capital useful later in the labor market or whether employment, especially working 20 h or more per week, can distract from academic pursuits and foster various problem behaviors, including delinquency and substance use ( Lee & Staff 2007 , McMorris & Uggen 2000 , Mortimer 2003 , Paternoster et al. 2003 ).

In the past two decades, a major activity has been in understanding the variable meaning and consequence of paid work in adolescence. For example, the outcomes linked to work hours depend on the goal of working, including saving for college and supporting the self or family ( Marsh 1991 , Newman 1996 ). Recent evidence indicates that work can promote educational attainment among those with low academic promise ( Staff & Mortimer 2007 ) and among poor and/or minority students ( Entwisle et al. 2005 ). For example, teenagers in Newman's (1999) ethnography of fast food workers often rejected the delinquency of peers in choosing to work, and their jobs brought them coworkers and supervisors that supported and rewarded their educational pursuits. Along these same lines, Lee & Staff (2007) compared adolescents who work intensively and those who do not do so but who share similar preexisting background characteristics. They found no effect on dropout among adolescents with backgrounds indicative of a high propensity to work intensively. These students tended to be from socioeconomically disadvantaged families and have weaker school performance. Additional studies indicate that the association between intensive employment and substance use is largely limited to whites ( Johnson 2004 ) and that intensive employment can actually help curb substance use and delinquency for adolescents with earlier histories of these problem behaviors ( Apel et al. 2007 ).

More effort also has been devoted to promoting causal inference in research on adolescent employment. Both spuriousness and bidirectionality are concerns in studies of work hour effects on adolescent behavior. Longitudinal studies adjusting for known covariates, including lagged measures of the outcome, often indicate that that preexisting differences account for many observed effects ( Schoenhals et al. 1998 , Warren et al. 2000 ). Links to substance use and some academic outcomes, however, persist ( McMorris & Uggen 2000 , Mortimer & Johnson 1998 , Paternoster et al. 2003 , Schoenhals et al. 1998 ). Other techniques, such as fixed and random effects models and propensity score matching, have revealed no evidence of work hour effects on adolescent behavior or effects only on adolescents with low or moderate propensities to work ( Lee & Staff 2007 , Paternoster et al. 2003 ), but they have been applied to a limited set of behavioral dimensions to date.

Thus, research is moving toward a clearer picture of how developmental, educational, human capital, and behavioral outcomes are linked to employment in adolescence. The same can be said of studies on other social pathways of adolescents (e.g., academic pathways).

Social Convoys

Adolescence is a time of both quantitative and qualitative change in the matrix of social relationships. In particular, the push and pull between parents and peers has been a dominant theme of research on adolescence for years.

Over time, the normative break with parents in adolescence has been reconceptualized as a renegotiation of parent and child roles, not disengagement. In other words, adolescents may spend less time with, and seek more autonomy from, parents, but they typically do so in the context of stable strong connections and parental influence ( Larson et al. 1996 ). Similar trends extend to other family relationships (e.g., with siblings and grandparents), which may loosen more in terms of shared time than in emotional bonds ( Crouter et al. 2004 , King et al. 2003 ).

The idea of parent-adolescent renegotiation has led to new ways of thinking about oft-studied issues. One of the best examples concerns parental monitoring. The general consensus has long been that adolescents engage in fewer problem behaviors when their parents keep close track of what they do and with whom they associate, in part because monitoring constrains opportunities to engage in such behaviors and in part because it helps to develop adolescent self-control ( Browning et al. 2005 , Hay 2006 ). Yet, Stättin & Kerr (2000) have argued that the most common indicator of parental monitoring—parental knowledge about adolescents' activities and peers—may be an effect of adolescent behavior more than a cause. In other words, well-behaved adolescents share their lives with their parents, creating the appearance of monitoring being behaviorally protective. More likely, this link is reciprocal—monitoring promoting prosocial behavior that, in turn, increases parent-adolescent relationship quality, adolescents' openness to parental monitoring, and adolescents' willingness to self-disclose to parents ( Fletcher et al. 2004 , Yau et al. 2009 ). This debate has driven home the need to think of adolescents' developmental trajectories and social convoys as intertwined over time.

Along these same lines, adolescents are increasingly viewed as eliciting parenting, not just being shaped by it. For example, changes in U.S. antipoverty policy that emphasize the role of fathers have brought attention to nonresident fathers ( Furstenberg 2007 ). Although the assumption is that having involved fathers is good for adolescents, this link partially reflects the tendency for nonresident fathers to be more involved in the lives of well-adjusted adolescents ( Hawkins et al. 2007 ). As another example, the normative increase in parent-child conflict during adolescence is less pronounced for second- or later-born children, as parents learn what to expect from their first-born children ( Shanahan et al. 2007 ). Another line of research that views both sides of the parent-adolescent relationship concerns the degree to which the characteristics and behaviors of parents and adolescents are aligned. Consider that religious mismatches within the family (e.g., religious mother and nonreligious adolescent, or vice versa) appear to engender adolescent problem behavior ( Pearce & Haynie 2004 ). Approaching parent-adolescent relationships as evolving, two-sided, and mutually influential, therefore, is crucial.

Of course, peers continue to be a primary focus of research on adolescence. Much of this research concerns how friends influence each other and how adolescents select into different kinds of friendships, but more attention is now being paid to the larger peer groupings in which these friendships are embedded. For example, boys are at greater risk for emotional distress when they are members of networks that are large and cohesive, but girls are at greater risk in networks that are large and noncohesive. This gendered pattern reflects differences in the interpersonal styles of girls and boys ( Falci & McNeely 2009 ). As another example, friendships tend to have greater influence on adolescent delinquency when they are embedded in dense networks ( Haynie 2001 ). Many social and institutional settings, such as schools and neighborhoods, can also be thought of as peer contexts, in that they organize the friendship market and serve as a center of youth culture ( Harding 2009 ). Peer relations and dynamics within such contexts may be better characterized by qualitative groupings of youth (e.g., crowds) as opposed to quantitatively measurable collectives (e.g., networks). Indeed, many meaningful peer groups are fluid but matter because they provide common identity and serve as the practical universe of potential friends ( Akerlof & Kranton 2002 , Brown & Klute 2003 ). Barber and associates (2001) , for example, used the archetypal characters from the movie The Breakfast Club (e.g., the jock, the rebel, the princess) as a way of organizing data collection on such peer crowds. Importantly, interpersonal processes that occur within larger bands of peers seem to do as much, if not more, to predict the positive and negative mental health and educational outcomes of adolescents than intimate friendships, especially in the long term.

Historically, scholars studied another key peer relation—romantic relationships—in terms of major developmental tasks (e.g., preparation for adult relationships), leading to a focus on their benefits ( Shulman & Collins 1998 ). Later, risks took the spotlight, including links of girls' dating with depression, stress, and abuse, and more attention was paid to the consequences of stricter norms about appropriate dating (and sexual) behavior for girls ( Hagan & Foster 2001 , Joyner & Udry 2000 , Kreager & Staff 2009 ). Increasingly, however, scholars have recognized that adolescent romance may be developmentally positive or negative depending on the characteristics of the partners, the quality of the relationship, and the context in which it occurs. For example, romantic relationships may foster early sexual activity but also reduce the psychological strain of sex and increase contraceptive use. They may be especially important as buffers against the potential harm of weak bonds with parents or as a stand-ins for close friends ( Giordano et al. 2006 , Manlove et al. 2007 , McCarthy & Casey 2008 ). Importantly, although boys were long thought to be less oriented to and affected by romance, emerging evidence suggests that boys may have equally strong ties to their partners as girls and be more influenced by them. Along with their lower confidence in their romantic skills, these qualities might leave boys vulnerable emotionally to the vicissitudes of adolescent romance ( Giordano et al. 2006 ).

An emerging task is to add a wider variety of extrafamilial and other familial relationships to this traditional focus on parents and peers. Taking such a holistic view of overlapping relationships as they evolve is the best way to capture the concept of social convoys.

The Social Embeddedness of Adolescence

As alluded to throughout the prior discussion, the three main strands of the life course play out—and come together—within social contexts, ranging from small primary and secondary groups (e.g., families) to larger societal institutions (e.g., schools) to macro-level social structures, such as stratification systems based on gender, race, and class. Here, we highlight some recent explorations of this social embeddedness of adolescence.

The Ecological Contexts of Adolescence

Because adolescents have limited mobility, neighborhoods can powerfully structure their lives physically and socially. As a result, studies of neighborhood effects have proliferated in recent years, aided by neighborhood data in specific locales (e.g., Project on Human Development in Chicago Neighborhoods, L.A. Family and Neighborhood Survey), on the national level (e.g., Add Health), and through demonstration projects moving low-income families to new communities (e.g., the Moving to Opportunity, or MTO, experiment), as well as by qualitative studies of neighborhoods and communities. Most of these studies focus on neighborhood disadvantage and adolescent risk-taking ( Bellair & Roscigno 2000 , Browning et al. 2005 , Dance 2002 , Harding 2003 , Kling et al. 2007 ).

Motivating much of this research is Wilson's (1996) perspective on spatially concentrated disadvantage, which is thought to disrupt networks of social capital that socialize and supervise youth and to hinder the effectiveness of local institutions (e.g., schools, churches) and informal networks in providing social control. Contemporary scholars have sought to identify the mechanisms involved in these processes. For example, Browning and associates (2005) reported that adolescents in neighborhoods of concentrated poverty experienced sexual onset earlier than others but that higher neighborhood collective efficacy delayed sexual onset, at least among adolescents experiencing lower levels of parental monitoring. These findings suggest conditional effects between neighborhood conditions and family functioning, appearing to contradict prior studies downplaying the possibility of multiplicative contextual influences ( Cook et al. 2002 ). Importantly, studies such as another by Browning and associates (2008) raise the issue of rates of risky sex in turn affecting the concentration of STD risk in neighborhoods, with individuals shaping context. Such micro-to-macro examples are rare but need more attention.

As in all examinations of contextual effects, causality has been a concern in neighborhood research. Browning and associates (2005) have argued that findings varying by level of neighborhood exposure suggest true effects. In line with this argument, Harding (2003) reported that neighborhood poverty effects on adolescents persisted when propensity score matching was employed. He also noted that controlling for individual-level factors may obscure real neighborhood effects if they are affected by neighborhood features themselves, a point echoed by Chuang and associates (2005) in arguing that parents may adjust their parenting based on neighborhood conditions. Indeed, instead of isolating neighborhood effects by controlling individual, economic, and family factors, Bellair & Roscigno (2000) have advocated for viewing labor market opportunities as preceding neighborhood disadvantage, family income, and adolescent attachments, all of which affect adolescent behavior. In other words, instead of controlling for family income, family structure, and adolescents' attachments to family, school, and peers to evaluate the link between local labor market conditions and delinquency, they map the effects of local labor market conditions on delinquency through its effects on family income and structure and adolescents' attachments.

With an experimental design, MTO revealed compelling findings about the implications of switching from low-income to middle-income neighborhoods for adolescents. Interestingly, the benefits of such moves were limited to girls, including improvements in mental health and decreases in delinquency. The qualitative components of the experiment suggested several mechanisms underlying these gendered effects, including girls' greater freedom from sexual fears, boys' (especially minority boys') greater difficulty integrating into new peer networks, and boys' continued strong ties to peers from their former communities ( Clampet-Lundquist et al. 2006 , Kling et al. 2007 ). Outside MTO, other qualitative studies of minority youth have detailed the gendered dilemma of youth adaptation to neighborhood disadvantage, especially crime. Girls must live up to feminized social expectations of them while trying to survive often violent conditions, and boys must develop fearsome personae that protect them on the streets but may disadvantage them in other contexts ( Dance 2002 , Jones 2010 ).

Another major ecological setting of adolescence is the school, where young people spend a large proportion of their waking hours. Scholars continue to decipher the effects of the organizational structure of schools (e.g., size, sector, and racial and socioeconomic composition) on student outcomes (see Arum 2000 for a recent review). Yet, the past decade has witnessed considerably more interest in the normative and social climate of schools, as captured by the rates of behaviors and social characteristics in the student body as a whole. These aggregated aspects of the student body tap into the value systems and opportunity structures to which adolescents are exposed on a daily basis, socializing them as well as affecting their ability to act on or against their own proclivities ( Crosnoe 2011 ). For example, adolescents attending schools in which a high proportion of their fellow students come from single-parent homes transition to first sex earlier than others, as this feature of the student body indicates reduced parental supervision of adolescents and their peers and also speaks to normative understandings of sexual relationships and families among students ( Harris et al. 2002 ). As another example, the average body size of students in a school sets the standard of comparison for adolescents' self-evaluations, affecting whether their own body size has implications for their socioemotional functioning ( Crosnoe 2011 ). As a final example, behavioral patterns in the student body as a whole can constrain or strengthen close friends' similarities on substance use ( Cleveland & Wiebe 2003 ). The peer culture of the school, therefore, provides opportunities that condition selection and socialization processes. Importantly, schools do not just expose students to a student body, they also organize peer subsets within the student body through activity and curricular offerings. Consider that the aforementioned Breakfast Club groups ( Barber et al. 2001 ) often arise from extracurricular activities. Moreover, Frank and associates (2008) used school transcripts to identify adolescents sharing the same social and academic space in school, peer groups that were significantly related to student outcomes.

As for the connection between neighborhoods and schools, ethnographic work has been especially insightful. For example, several studies have illuminated the unique challenges faced by working class and low-income African American youth, especially boys, as they simultaneously navigate their neighborhoods and their schools with very different sets of racialized expectations for youth. For such boys, the tough and seemingly defiant posture that they develop among peers in their neighborhoods is often misconstrued and viewed negatively by the middle-class personnel in their schools, leading to academic marginalization and fueling pernicious ideas about the oppositional culture of minority youth ( Dance 2002 , Carter 2006 ).

The point of this neighborhood and school research is that ecological settings create social networks and contexts in which the powerful peer and family processes of adolescence operate. Thus, going beyond structural dimensions of such settings to capture social processes is important.

Adolescence and Social Stratification

The adolescent population is quite diverse in terms of race/ethnicity, social class, and other markers of social location. Especially among sociologists, such diversity has motivated a great deal of research concerning the ways that adolescents' experiences are both a product of and contributor to major systems of social stratification ( Morgan 2005 ).

In part because adolescence is a relatively healthy period in the life course, major health disparities are less common and consistent during this stage compared with others ( Crockett & Peterson 1993 ). Indeed, adolescents from historically disadvantaged minority groups often are similar to or lower than whites in rates of many risky health behaviors, such as drinking ( Harris et al. 2006 ). Yet, the recent rise in obesity has also been problematic from a long-term health perspective, particularly for African American and Latino/a youth ( Ogden et al. 2010 ). Thus, adolescence may play a positive and negative role in race/ethnic disparities across the life course.

On a structural level, school segregation continues to be an issue of great interest ( Rothstein 2004 ). Studies of school composition suggest that racial desegregation has academic benefits for both white and non-white students by exposing them to different ways of thinking and by leading to greater equity in school resources. Yet, students may also feel lowered senses of belonging and perceive more discrimination in diverse schools ( Goldsmith 2004 , Johnson et al. 2001 , Rumberger & Palardy 2005 ). Progress in school desegregation has also often come with increased within-school segregation ( Mickelson 2001 ). Recently, Parents Involved , in which the Supreme Court curtailed use of race in school assignment, has shifted attention from race to socioeconomic status. Efforts to socioeconomically desegregate schools, however, also demonstrate a mixture of benefits and risks, with research suggesting that academic gains might be accompanied by psychosocial problems and that socioeconomically integrating schools would not alter levels of racial segregation ( Crosnoe 2009 , Reardon et al. 2006 ).

On an interpersonal level, Ogbu's (1997) oppositional culture thesis—which, among other things, argues that African American and Latino/a peers de-emphasize achievement and equate it with acting white—has continued to generate debate. Quantitative examinations have provided little evidence of this phenomenon ( Ainsworth-Darnell & Downey 1998 , Harris 2006 ). Mixed methods examinations have suggested that it does occur occasionally but with some important caveats: ( a ) It is rooted in schools' long-term misunderstanding of minority group culture, and ( b ) it is not racialized but instead happens in youth culture more generally, in ways that are manifested differently by race and class ( Carter 2006 , Tyson et al. 2005 ). In total, research on oppositional culture has probably done less to unpack race/ethnic achievement gaps than it has to illuminate the nexus of youth culture and schooling.

For the most part, research on socioeconomic disparities has continued to focus on socioeconomic disadvantage (e.g., poverty), especially after the contentious public debate about welfare reform ( Gennetian et al. 2008 ). Much of this research suggests that poverty is clearly detrimental to adolescents but perhaps less so than it is for children ( Duncan et al. 1998 ). At the same time, the past decade has also witnessed significant advances in our understanding of socioeconomic advantage. Lareau's (2004) work has been enormously influential. This research has demonstrated that middle-class parents tend to follow an approach to parenting, concerted cultivation, that prioritizes providing children cognitively and socially stimulating activities at home and in formal organizations that develop skills, enhance their senses of entitlement, and teach them how to work institutional systems. Such parenting is so well aligned with the American educational system that it gives their children a competitive edge in school. Initially, Lareau focused on elementary school, but her basic insights have been replicated in studies of adolescence ( Crosnoe & Huston 2007 , Kim & Schneider 2005 ). Moreover, Lareau's recent follow-up of her sample in young adulthood revealed that parenting-related socioeconomic advantages persisted into adolescence and beyond.

Turning to immigration, traditional assimilation perspectives posited improved outcomes for the descendants of immigrants compared with immigrants themselves. Yet, newer research suggests that the foreign- and U.S.-born children of immigrants outperform third-plus-generation youth, despite higher levels of socioeconomic disadvantage among immigrants. Evidence of this immigrant paradox is more consistent among adolescents than children ( Glick & Hohmann-Marriott 2007 , Kao 1999 , Portes & Rumbaut 2001 , Suarez-Orozco et al. 2009 ). This age difference could reflect adolescents' greater time to adapt to American schools and culture. It could also reflect biases in high school data sets, as immigrants from many regions are more likely to drop out of or bypass school ( Oropesa & Landale 2009 ). Perhaps more importantly, evidence of the immigrant paradox varies widely according to national origin, race/ethnicity, and socioeconomic status. For example, adolescents whose parents emigrated from Asia best illustrate the immigrant paradox, at least in the academic realm. Asia is a region in which migration is positively selective on education and income, but, beyond socioeconomic status, Asian immigrant parents tend to have high standards of academic success, go to great lengths to secure educational opportunities for adolescents, and are highly planful (especially financially) about education ( Kao 2004 , Zhou 2009 ). This diversity in immigrant outcomes has supported theoretical reconceptualizations, such as segmented assimilation ( Portes & Zhou 1993 ), contending that the outcomes of assimilation depend on the context in which it occurs.

Of course, the adolescent population is stratified by factors beyond race and family background that also shape trajectories into adulthood. Two examples are obesity and homosexuality. Because of the stigma of obesity in American culture, obese youth are at heightened risk for psychosocial difficulties, which appear to disrupt their educational trajectories ( Crosnoe 2011 ). Similarly, same-sex-attracted youth often face strong social sanctions during high school that can filter into multiple domains, including academic progress ( Pearson et al. 2007 , Russell & Joyner 2001 ). In both cases, adolescents' characteristics position them on a social hierarchy to create short-term problems with long-term consequences. These stratifying processes are similar to gender, race, class, and immigration in that their significance in adolescence may create and reinforce unequal life chances.

New Directions for Research on Adolescence

Attempts by sociologists and other scholars over the past two decades to answer many of the tough questions about adolescence have raised additional questions. Having looked back, therefore, we now look forward. Given the space allowed, we have decided to focus on three specific future directions that touch on particularly provocative and timely debates and discussions in the field.

Biosocial Processes

In recent years, the integration of biomarkers with psychological and social data has helped empirical activity catch up with developmental theory. The sociological value of this activity is not in establishing genetic effects on adolescent behavior but instead in understanding the interplay of genes and environment at work in adolescent behavior ( Guo et al. 2008 ).

Understanding latent genetic influences has been aided by the creation of sibling samples, which allow assessments of sibling similarity in behavioral or other outcomes across sibling pairs of different degrees of genetic relatedness. Analyses of data from one such sample, the Nonshared Environment in Adolescent Development project, have elucidated the ways in which genetic traits select adolescents into different relationships and elicit different kinds of parenting. They have also demonstrated how the experiences that siblings have outside the home differentiate them on developmental outcomes, despite their genetic relatedness ( Reiss et al. 2000 ). Research on Add Health's diverse sibling pairs subsample has been particularly insightful about variability in shared environment and observed heritability of behaviors across social settings ( Boardman et al. 2008 ). For example, adolescent aggression is genetically influenced in both socioeconomically advantaged and disadvantaged communities, but the effects of shared environments (e.g., social influences experienced by both siblings) are significantly stronger in disadvantaged communities ( Cleveland 2003 ).

Turning to specific genetic influences, the collection of genetic data in behavioral studies has encouraged deeper exploration of gene-environment interactions. For example, Caspi and associates (2003) , drawing on biological and psychosocial data from New Zealand, reported that stressful life events had a larger impact on depression among youth with short alleles of the 5-HTT promoter polymorphism, which reduces efficiency of serotonin reuptake in the brain. Research by Guo and associates (2008) with the genetic data in Add Health demonstrated that the significance for delinquency of DRD2 alleles, which reduce efficiencies in the dopaminergetic system, is weaker in families with well-organized routines. Such studies push for a transactional view of biology, development, and environment.

Particularly important are genetically informed studies comparing adolescence with other life stages. For example, Dick and associates (2006) , working with genetic and psychosocial data from the United States, reported that the presence of a gene-regulating neurotransmitters, GABRA2, was associated with conduct disorder in adolescence and then with alcohol use in young adulthood. Thus, a genetic predisposition toward risky behavior is manifested differently across stages. A sociological interpretation is that entry into new settings across the transition from adolescence to adulthood might account for such changes.

As for other biomarkers, cortisol is a central hormone in stress response. Because cortisol levels tend to decline over the day, flatter diurnal patterns may signal health risks through the overactivation of physiological stress response ( Susman 2006 ). Efforts to integrate saliva samples and time diaries have revealed that minority youth report higher levels of chronic stress and demonstrate flatter cortisol patterns across the day than whites. Thus, identifying biological mechanisms underlying links between environmental stress and adolescent health may shed light on the role of adolescence in health disparities ( DeSantis et al. 2007 ). Similarly, immunological processes provide a window into environmental effects on youth. For example, McDade (2001) has combined samples of Epstein-Barr virus antibodies with lifestyle data. This work indicates that the stress that adolescents feel from modernization in developing countries is manifested in reduced immune functioning. Like neuroscience, this biomarker research is more common outside sociology, but it touches on core sociological questions, such as the effects of social integration on life chances, thereby representing a growth area for sociologists.

The nature versus nurture debate, therefore, seems to be dying. Indeed, research on adolescence is turning to the synergistic interplay between nature and nurture. Sociologists interested in adolescence have a significant role to play in uncovering the complexities of this interplay moving forward.

Linking Life Stages

Adolescence is better understood when it is viewed within the full life course, and we are now well poised to theorize and empirically evaluate linkages between adolescence and other life stages ( Johnson et al. 2011 ). As noted in the opening section of this review, advances in longitudinal sampling and modeling have facilitated asking and answering questions that involve processes unfolding over time and across contexts. At least in some domains (e.g., education, work), scholars of adolescence are accustomed to thinking about how adolescent experiences affect adult life. Both looking back to childhood and looking forward to adulthood, however, will enable us to elucidate the role of adolescence in the life course.

For example, initial curricular placements and academic achievement in high school are recognized as important to concurrent and future well-being. Yet, the past decade has also witnessed greater emphasis on understanding proximate and distal factors involved in producing varying levels of high school achievement. By following Baltimore schoolchildren from first grade into early adulthood, Alexander and associates (2007) were able to capture the full educational career and, in the process, identify critical periods. Socioeconomic disparities in academic progress at the start of high school were traced back to corresponding disparities in place at the start of first grade and to summer learning differences by socioeconomic status during the elementary school years. These ninth grade differences were then linked to curricular track, high school completion, and college attendance. Their interpretation emphasized how foundational the skills are that are learned in the early years of schooling and the ways in which the in-school and out-of-school settings and experiences that stratify early learning can have lasting, even accumulating, consequences for the life course. Exclusive focus on the adolescent years, and particularly the high school years, misses these processes set in motion much earlier and likely obscures the best points of intervention ( Heckman 2006 ).

As another example, pubertal timing may be a conduit in the connection between disadvantage in childhood and adulthood. Consider that family adversity is among the myriad biological and environmental factors accelerating pubertal timing ( Belsky et al. 2007 ). Cavanagh and associates (2007) have reported that early pubertal timing during middle school is linked to lower grades and the likelihood of course failure at the start of high school, and that as a result, high school completion and the grades of those who graduate are also affected. By stepping back to view longer-term processes, we see additional mechanisms through which family disadvantage impacts children's success in adolescence and adulthood, operating via biological and social processes, as well as their complex interactions.

Finally, charting individual trajectories over time provides important context for understanding what is observed in adolescence. The influential differentiation between life course persistence and adolescence desistance in criminal behavior is one example ( Moffitt 1993 ). Another concerns adolescent substance use, which is embedded within a variety of long-term trajectories that have distinct meaning and consequence. Following cohorts of adolescents in the Monitoring the Future Surveys into adulthood, Schulenberg and associates (2005) linked different patterns of substance use to the pathways through which adolescents transition into adulthood. Levels of substance use in adolescence anticipated the configuration of role transitions young people experienced in the years immediately following, but were also shaped by them. Young people who worked and did not attend school during these years binge drank more frequently during high school. Those who moved away from home for college were less frequent binge drinkers in high school but quickly caught up. These patterns suggest the varied settings and conditions that different adult statuses bring but also the potential for psychosocial preparation for these statuses during adolescence.

The life course paradigm emphasizes that development is lifelong and that no life stage can be understood in isolation. These examples highlight the advances that can be made if we rise to the challenge posed in this life course principle.

Social Change

Of course, linkages among life stages are also shaped by broader changes in the structure of society. Economic restructuring, for example, is dramatically affecting education and employment in young adulthood and beyond, and we need to better understand what this means for adolescents. Changes in the relative size of the manufacturing and service sectors have occurred in such a way as to reduce the availability of jobs with benefits, increase the income premium of higher education, and create greater fluidity between jobs ( Goldin & Katz 2008 ). Furthermore, Fullerton & Wallace (2007) characterized a set of interrelated changes occurring since the 1970s, including declining unionization, downsizing, growing use of contingent labor, and organizational restructuring as a “flexible turn in U.S. labor relations (p. 201),” which has eroded workers' perceptions of job security. Such changes are increasing the importance of adolescents' educational experiences in the status attainment process, thereby magnifying the significance of all of the factors discussed in this review that matter to these experiences.

In this context, the process of becoming adult has clearly changed, with scholars suggesting that adolescence has been extended to older ages or even that a new life stage should be recognized ( Settersten et al. 2005 ). Demands for and returns to education have risen, and relatedly, the period of dependency and semi-autonomy has lengthened. We know young people are staying in school longer, more often combining employment with higher education, and marrying later ( Bernhardt et al. 2001 , Fitzpatrick & Turner 2007 , U.S. Census Bureau 2006 ). Although race/ethnic and socioeconomic variability in these patterns has long been recognized ( Settersten et al. 2005 ), we are only just beginning to address a number of other important questions related to these broad social changes, including what they mean for the achievement of social and financial autonomy and relationships with others, including parents, and what we need to equip adolescents with in order for them to successfully navigate the transition to adulthood.

Two major collaborative efforts have laid an important foundation for understanding the implications of these social changes for adolescence. The first is the MacArthur Research Network on Transitions to Adulthood and Public Policy ( Settersten et al. 2005 ). It has reported, among other things, that parents, especially those with more resources, increasingly support their children through the transition to adulthood financially and otherwise. About one-third of 18–34 year olds in the Panel Study of Income Dynamics received cash support from their parents, at an average of just over $3,400 per year ( Schoeni & Ross 2005 ). This and other forms of ongoing material assistance (e.g., support of higher education pursuits, allowing children to remain in the home, assistance in establishing independent households, providing childcare) may be yet another way in which parents' level of education and income can affect the status attainment of their children. The second effort is the Society for Research on Adolescence's Study Group on Adolescence in the Twenty-First Century ( Larson et al. 2002 ). One of its reports has argued that changes in family size, structure, and relationships; increased participation in school and after-school activities; and the advent of the Internet have created new opportunities for adolescents to develop more flexible social skills and capacities to move between diverse social worlds. It also notes, however, that those from families in poverty and those in elite families are more deprived when it comes to the social experience that builds these skills.

Another major social change concerns the transformation of social interaction though new media and technologies. The Pew Internet and American Life Project has reported that, in 2009, 75% of 12–17 year olds had cell phones and 93% went online ( Lenhart et al. 2010 ). The report also indicated that 76% of families with adolescents now had broadband access at home. Adolescents also go online via cell phones and portable gaming devices, in addition to computers at home. These technologies offer new opportunities for leisure, shopping, and staying in touch with others, as well as broader access to information and support. Roughly one-third of adolescents in the Pew study who went online used the Internet to gather information on health, dieting, or physical fitness, and 17% looked online for information about sensitive health topics, such as those related to drug use, mental health, and sex ( Lenhart et al. 2010 ).

Importantly, the Internet can also be thought of as a new kind of peer context. A recent study of 800 American youth revealed that, for most youth, new media technologies are used primarily to maintain and extend friendship networks ( Ito et al. 2010 ). Moreover, the Internet provides opportunities for socially isolated youth to connect with others in meaningful ways while also enabling the peer cultures of high school—including negative dimensions, such as bullying and gossiping—to follow young people home ( Crosnoe 2011 , Raskauskas & Stoltz 2007 ). Thus, new media represent a potential context of resource and risk related to peers.

Other potential risks ranging from driving accidents related to texting or talking on cell phones to exposure to questionable online content or social interactions (e.g., pornography, gambling, sexual solicitation) have concerned parents, educators, and lawmakers. Debates continue over whether risks can also accrue from the potentially sensitive or identifying information, including pictures and videos, adolescents post online about themselves and one another, or whether this is a healthy part of adolescents' self-expression and identity exploration. Nearly three-quarters of online youth use a social networking Web site such as Facebook or MySpace ( Lenhart et al. 2010 ). A recent content analysis of teenagers' MySpace pages indicated that 40% of adolescent users restricted access to their pages to identified friends. Yet, 10% of adolescent users who did not restrict access posted their full name, and many more listed their hometowns and the name of their schools, which could be used to identify them ( Hinduja & Patchin 2008 ).

Relevant empirical evidence about these concerns, however, is rare, and the topic is notably absent from the top sociological publishing outlets. Yet, sociologists have much to contribute, as adolescents' use of new media raises important questions about social networks, personal relationships, and identity development. What are the implications of cell phone use or online communication for parental monitoring and peer interactions? Do electronic interactions replace or complement face-to-face interactions? Do online venues provide a safe or dangerous place for identity work? As an example highlighting the potential work to be done, Blais and associates (2008) reported that Internet activity was related to changes in the quality of best friendships and romantic relationships over the course of a year among Canadian adolescents. Specifically, use of instant messaging, which occurs with known others, enhanced these relationships, but visits to chat rooms, which primarily involve communicating with strangers, were associated with worsening relationship quality over time. As these findings suggest, we will need to be specific about the types of media being used when we attempt to understand their implications for today's adolescents.

As is evident from this review, the rich sociological tradition of research on adolescence has continued into the new century. Still, the sociology of adolescence may be at something of a crossroads. The mapping of the human genome and the increasing sophistication of brain imaging are reshaping the scientific agenda in ways that, at first glance, do not tap into the traditional strengths of sociologists. At the same time, the renewed interest in childhood as a critical period—generated by findings that early interventions bring greater long-term returns to investments than those targeting adolescence ( Heckman 2006 )—has shifted attention to earlier stages. Another way of looking at these developments, however, is that they are opportunities. Indeed, sociologists are well-positioned to demonstrate how biological processes cannot be understood absent a firm sociological understanding of the environment in which they play out over time, explain how the long reach of childhood is channeled through adolescence, and identify ways in which adolescence produces turning points and deflections in the life course.

Summary Points

• Research on adolescence has moved in a sociological direction by emphasizing the role of context in shaping adolescents' lives and the link between adolescent development and societal inequality, fueled in part by recent advances in data collection and methodology.
• Early childhood experiences are very important to long-term health, educational, and behavioral trajectories, but adolescent experiences play key roles in this process by magnifying or deflecting children's trajectories.
• Many of the major developmental trajectories of adolescence, including those related to puberty, risky behavior, academic achievement, health, and identity development, reflect a complex interplay of biology, personal agency, and environment.
• Adolescents' navigation of institutional systems, such as school and work, have become increasingly complex and interrelated, with high school coursework more consequential to long-term outcomes in the globalized economy and paid work during adolescence becoming more common and potentially either risky or beneficial for educational attainment depending on motivation, background, and academic competence.
• Adolescents tend to spend less time with parents and other relatives and seek more autonomy while becoming more immersed in expanding peer networks, including romantic networks, but they typically do so while maintaining strong emotional ties to their families.
• Although much of the research on school and neighborhood effects on adolescent behavior has focused on the structural features of these contexts, more attention is being paid to the ways in which they organize peer groups that differ widely in terms of norms, values, and behavioral opportunities, as well as the ways families affect and respond within them.
• Gender, race, social class, and immigration stratify adolescents' lives, with poor and/or minority youth particularly vulnerable in the educational system, through a variety of structural inequalities and interpersonal processes, but immigrant youth often demonstrate a high level of resilience in the face of similar risks.

Acknowledgments

Support for R.C. came from a faculty scholar award from the William T. Grant Foundation, as well as a center grant to the Population Research Center at the University of Texas at Austin from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (R24 HD042849; PI: Mark Hayward). The authors thank Anna Thornton for her help with this review.

Disclosure Statement : The authors are not aware of any affiliations, memberships, funding, or financial holdings that might be perceived as affecting the objectivity of this review.

Literature Cited

• Adelman C. The Toolbox Revisited: Paths to Degree Completion from High School through College. Washington, DC: U.S. Dep. Educ; 2006. [ Google Scholar ]
• Ainsworth-Darnell J, Downey D. Assessing racial/ethnic differences in school performance. Am Sociol Rev. 1998; 63 :536–53. [ Google Scholar ]
• Akerlof GE, Kranton RA. Identity and schooling: some lessons for the economics of education. J Econ Lit. 2002; 40 :1167–201. [ Google Scholar ]
• Alexander K, Entwisle D, Olson L. Lasting consequences of the summer learning gap. Am Sociol Rev. 2007; 72 :167–80. [ Google Scholar ]
• Allen JP, Porter MR, McFarland CF, Marsh P, McElhaney KB. The two faces of adolescents' success with peers: adolescent popularity, social adaptation, and deviant behavior. Child Dev. 2005; 76 :747–60. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Apel R, Bushway S, Brame R, Haviland AM, Nagin DS, Paternoster R. Unpacking the relationship between adolescent employment and antisocial behavior: a matched samples comparison. Criminology. 2007; 45 :67–97. [ Google Scholar ]
• Arum R. Schools and communities: ecological and institutional dimensions. Annu Rev Sociol. 2000; 26 :395–418. [ Google Scholar ]
• Bachman JG, Johnston LD, O'Malley PM. Monitoring the Future: Questionnaire Responses from the Nation's High School Seniors. Ann Arbor, MI: Inst. Soc. Res; 2009. [ Google Scholar ]
• Bachman JG, O'Malley P, Schulenberg J, Johnston LD, Bryant A, Merline A. The Decline of Substance Use in Young Adulthood: Changes in Social Activities, Roles, and Beliefs. Mahwah, NJ: Erlbaum; 2002. [ Google Scholar ]
• Barber BL, Eccles JS, Stone MR. Whatever happened to the jock, the brain, and the princess? Young adult pathways linked to adolescent activity involvement and social identity. J Adolesc Res. 2001; 16 :429–55. [ Google Scholar ]
• Bellair PE, Roscigno VJ. Labor market opportunity and adolescent delinquency. Soc Forces. 2000; 78 :1509–38. [ Google Scholar ]
• Belsky J, Steinberg LD, Houts R, Friedman S, DeHart G, et al. Family rearing antecedents of pubertal timing. Child Dev. 2007; 78 :1302–21. [ PubMed ] [ Google Scholar ]
• Berg GA. Lessons from the Edge: For-Profit and Nontraditional Higher Education in America. New York: Praeger; 2007. [ Google Scholar ]
• Bernhardt A, Morris M, Handcock MS, Scott MA. Divergent Paths: Economic Mobility in the New American Labor Market. New York: Russell Sage Found; 2001. [ Google Scholar ]
• Blais JJ, Craig WM, Pepler D, Connolly J. Adolescents online: the importance of internet activity choices to salient relationships. J Youth Adolesc. 2008; 37 :522–36. [ Google Scholar ]
• Boardman JD, Saint Onge JM, Haberstick BC, Timberlake DS, Hewitt JK. Do schools moderate the genetic determinants of smoking? Behav Genet. 2008; 38 :234–46. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Bollen KA, Curran PJ. Latent Curve Models: A Structural Equation Approach. Hoboken, NJ: Wiley; 2006. [ Google Scholar ]
• Breen R, Goldthorpe JH. Explaining educational differentials: towards a formal rational action theory. Ration Soc. 1997; 9 :275–305. [ Google Scholar ]
• Bronfenbrenner U, Morris P. The ecology of developmental processes. In: Damon W, Lerner RM, editors. Handbook of Child Psychology. New York: Wiley; 1998. pp. 993–1028. [ Google Scholar ]
• Brown BB, Klute C. Friendships, cliques, and crowds. In: Adams G, Berzonsky MD, editors. Blackwell Handbook of Adolescence. Malden, MA: Blackwell; 2003. pp. 330–48. [ Google Scholar ]
• Browning CR, Burrington LA, Leventhal T, Brooks-Gunn J. Neighborhood structural inequality, collective efficacy, and sexual risk behavior among urban youth. J Health Soc Behav. 2008; 49 :269–85. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Browning CR, Leventhal T, Brooks-Gunn J. Sexual initiation in early adolescence: the nexus of parental and community control. Am Sociol Rev. 2005; 70 :758–78. [ Google Scholar ]
• Bryk AS, Raudenbush SW, Congdon RT. Hierarchical Linear Models. Chicago: Sci. Softw. Inc; 2002. [ Google Scholar ]
• Buchmann C, DiPrete TA. The growing female advantage in college completion. Am Sociol Rev. 2006; 71 :515–41. [ Google Scholar ]
• Carter P. Keepin' It Real: School Success Beyond Black and White. New York: Oxford Univ. Press; 2006. [ Google Scholar ]
• Caspi A, Sugden K, Moffitt TE, Taylor A, Craig IW, et al. Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science. 2003; 301 :386–89. [ PubMed ] [ Google Scholar ]
• Cavanagh SE. The sexual debut of girls in early adolescence: the intersection of race, pubertal timing, and friendship group dynamics. J Res Adolesc. 2004; 14 :285–312. [ Google Scholar ]
• Cavanagh SE, Riegle-Crumb C, Crosnoe R. Early pubertal timing and the education of girls. Soc Psychol Q. 2007; 70 :186–98. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Chuang YC, Ennett ST, Bauman KE, Foshee VA. Neighborhood influences on adolescent cigarette and alcohol use: mediating effects through parent and peer behaviors. J Health Soc Behav. 2005; 46 :187–204. [ PubMed ] [ Google Scholar ]
• Clampet-Lundquist S, Edin K, Kling J, Duncan G. IRS Work Pap 509. Princeton Univ; 2006. Moving at-risk teenagers out of high-risk neighborhoods: why girls fare better than boys. [ PubMed ] [ Google Scholar ]
• Cleveland HH. Disadvantaged neighborhoods and adolescent aggression: behavioral genetic evidence of contextual effects. J Res Adolesc. 2003; 13 :211–38. [ Google Scholar ]
• Cleveland HH, Wiebe RP. The moderation of adolescent–to–peer similarity in tobacco and alcohol use by school levels of substance use. Child Dev. 2003; 74 :279–91. [ PubMed ] [ Google Scholar ]
• Cook TD, Herman M, Phillips M, Settersten RA., Jr Some ways in which neighborhoods, nuclear families, friendship groups and schools jointly affect changes in early adolescent development. Child Dev. 2002; 73 :1283–309. [ PubMed ] [ Google Scholar ]
• Crockett LJ, Petersen AC. Adolescent development: health risks and opportunities for health promotion. In: Millstein SG, Petersen AC, Nightingale EO, editors. Promoting the Health of Adolescents: New Directions for the 21st Century. New York: Oxford; 1993. pp. 13–37. [ Google Scholar ]
• Crosnoe R. Low-income students and the socioeconomic composition of public high schools. Am Sociol Rev. 2009; 74 :709–30. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Crosnoe R. Fitting In, Standing Out: Navigating the Social Challenges of High School to Get an Education. New York: Cambridge Univ. Press; 2011. [ Google Scholar ]
• Crosnoe R, Huston A. Socioeconomic status, schooling, and the developmental trajectories of adolescents. Dev Psychol. 2007; 43 :1097–1110. [ PubMed ] [ Google Scholar ]
• Crouter AC, Head MR, McHale SM, Tucker CJ. Family time and the psychosocial adjustment of adolescent siblings and their parents. J Marriage Fam. 2004; 66 :147–62. [ Google Scholar ]
• Dahl RE, Spear LP. Adolescent brain development: vulnerabilities and opportunities. Ann N Y Acad Sci. 2004; 1021 :1–22. [ PubMed ] [ Google Scholar ]
• Dance J. Tough Fronts: The Impact of Street Culture on Schooling. London: Routledge Falmer; 2002. [ Google Scholar ]
• DeSantis A, Adam EK, Doane L, Mineka S, Zinbarg R, Craske M. Racial/ethnic differences in cortisol diurnal rhythms in a community sample of adolescents. J Adolesc Health. 2007; 41 :3–13. [ PubMed ] [ Google Scholar ]
• Dick DM, Bierut L, Hinrichs A, Fox L, Bucholz KK, et al. The role of GABRA2 in risk for conduct disorder and alcohol and drug dependency across developmental stages. Behav Genet. 2006; 36 :577–90. [ PubMed ] [ Google Scholar ]
• Dornbusch SM. The sociology of adolescence. Annu Rev Sociol. 1989; 15 :233–59. [ Google Scholar ]
• Duncan GJ, Brooks-Gunn J, Yeung WJ, Smith JR. How much does childhood poverty affect the life chances of children? Am Sociol Rev. 1998; 63 :406–23. [ Google Scholar ]
• Elder GH., Jr The life course as developmental theory. Child Dev. 1998; 69 :1–12. [ PubMed ] [ Google Scholar ]
• Elder GH Jr, Giele JZ, editors. The Craft of Life Course Research. New York: Guilford; 2009. [ Google Scholar ]
• Entwisle DR, Alexander KL, Olson LS. Urban teenagers: work and dropout. Youth Soc. 2005; 37 :3–32. [ Google Scholar ]
• Falci C, McNeely C. Too many friends: social integration, network cohesion and adolescent depressive symptoms. Soc Forces. 2009; 87 :2031–2061. [ Google Scholar ]
• Fitzpatrick MD, Turner SE. Blurring the boundary: changes in the transition from college participation to adulthood. In: Danzinger S, Rouse C, editors. The Price of Independence: The Economics of Early Adulthood. New York: Russell Sage Found; 2007. pp. 107–37. [ Google Scholar ]
• Fletcher AC, Steinberg LD, Williams-Wheeler M. Parental influences on adolescent problem behavior: revisiting Stattin and Kerr. Child Dev. 2004; 75 :781–96. [ PubMed ] [ Google Scholar ]
• Frank KA, Schiller KS, Riegle-Crumb C, Mueller AS, Crosnoe R, et al. The social dynamics of mathematics coursetaking in high school. Am J Sociol. 2008; 113 :1645–96. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Fullerton AS, Wallace M. Traversing the flexible turn: U.S. workers' perceptions of job security, 1977–2002. Soc Sci Res. 2007; 36 :201–21. [ Google Scholar ]
• Furstenberg FF. Teenage childbearing as a public issue and private concern. Annu Rev Sociol. 2003; 29 :23–29. [ Google Scholar ]
• Furstenberg FF. Should government promote marriage? J Policy Anal Manag. 2007; 26 :956–60. [ Google Scholar ]
• Gamoran A, Hannigan EC. Algebra for everyone? Benefits of college-preparatory mathematics for students with diverse abilities in early secondary school. Educ Eval Policy Anal. 2000; 22 :241–54. [ Google Scholar ]
• Ge X, Elder GH, Jr, Regnerus M, Christine C. Pubertal transitions, perceptions of being overweight, and adolescents' psychological maladjustment: gender and ethnic differences. Soc Psychol Q. 2001; 64 :363–75. [ Google Scholar ]
• Gennetian LA, Lopoo LM, London AS. Maternal work hours and adolescents' school outcomes among low-income families in four urban counties. Demography. 2008; 45 :31–43. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Giordano PC, Longmore MA, Manning WD. Gender and the meanings of adolescent romantic relationships: a focus on boys. Am Sociol Rev. 2006; 71 :260–87. [ Google Scholar ]
• Glick JE, Hohmann-Marriott B. Academic performance of young children in immigrant families: the significance of race, ethnicity, and national origin. Int Migr Rev. 2007; 41 :371–402. [ Google Scholar ]
• Goldin C, Katz LF. The Race between Technology and Education. Cambridge, MA: Harvard Univ. Press; 2008. [ Google Scholar ]
• Goldsmith PA. Schools' racial mix, students' optimism, and the black-white and Latino-white achievement gaps. Sociol Educ. 2004; 77 :121–47. [ Google Scholar ]
• Goyette KA. College for some to college for all: social background, occupational expectations, and educational expectations over time. Soc Sci Res. 2008; 37 :461–84. [ PubMed ] [ Google Scholar ]
• Guo G, Roettger M, Cai T. The integration of genetic propensities into social control models of delinquency and violence among male youths. Am Sociol Rev. 2008; 73 :543–68. [ Google Scholar ]
• Hagan J, Foster H. Youth violence and the end of adolescence. Am Sociol Rev. 2001; 66 :874–99. [ Google Scholar ]
• Hall GS. Adolescence. New York: Appleton; 1904. [ Google Scholar ]
• Hankin BL, Mermelstein R, Roesch L. Sex differences in adolescent depression: stress exposure and reactivity models. Child Dev. 2007; 78 :279–95. [ PubMed ] [ Google Scholar ]
• Harding DJ. Counterfactual models of neighborhood effects: the effect of neighborhood poverty on dropping out and teenage pregnancy. Am J Sociol. 2003; 109 :676–719. [ Google Scholar ]
• Harding DJ. Violence, older peers, and the socialization of adolescent boys in disadvantaged neighborhoods. Am Sociol Rev. 2009; 74 :445–64. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Harris A. I (don't) hate school: revisiting oppositional culture theory of blacks' resistance to schooling. Soc Forces. 2006; 85 :797–833. [ Google Scholar ]
• Harris KM, Duncan GJ, Boisjoly J. Evaluating the role of “nothing to lose” attitudes on risky behavior in adolescence. Soc Forces. 2002; 80 :1005–39. [ Google Scholar ]
• Harris KM, Gordon-Larsen P, Chantala K, Udry JR. Longitudinal trends in race/ethnic disparities in leading health indicators from adolescence to young adulthood. Arch Pediatr Adolesc Med. 2006; 160 :74–81. [ PubMed ] [ Google Scholar ]
• Hawkins D, Amato P, King V. Nonresident father involvement and adolescent well-being: father effects or child effects? Am Sociol Rev. 2007; 72 :990–1010. [ Google Scholar ]
• Hay C. Parenting, self-control, and delinquency: a test of self-control theory. Criminology. 2006; 39 :707–36. [ Google Scholar ]
• Haynie DL. Delinquent peers revisited: Does network structure matter? Am J Sociol. 2001; 106 :1013–1057. [ Google Scholar ]
• Haynie DL. Contexts of risk? Explaining the link between girls' pubertal development and their delinquency involvement. Soc Forces. 2003; 82 :355–97. [ Google Scholar ]
• Heckman J. Skill formation and the economics of investing in disadvantaged children. Science. 2006; 312 (5782):1900–2. [ PubMed ] [ Google Scholar ]
• Hinduja S, Patchin JW. Personal information and adolescents on the Internet: a quantitative content analysis of MySpace. J Adolesc. 2008; 31 :125–46. [ PubMed ] [ Google Scholar ]
• Ito M, Baumer S, Bittanti M, Boyd D, Cody R, et al. Hanging Out, Messing Around, and Geeking Out: Kids Living and Learning with New Media. Cambridge, MA: MIT Press; 2010. [ Google Scholar ]
• Jacob BA, Wilder T. NBER Work Pap No 15683. Natl. Bur. Econ. Res; 2010. Educational expectations and attainment. [ Google Scholar ]
• Johnson MK. Further evidence on adolescent employment and substance use: differences by race and ethnicity. J Health Soc Behav. 2004; 45 :187–97. [ PubMed ] [ Google Scholar ]
• Johnson MK, Crosnoe R, Elder GH., Jr Student attachment and academic engagement: the role of race and ethnicity. Sociol Educ. 2001; 74 :318–40. [ Google Scholar ]
• Johnson MK, Crosnoe R, Elder GH., Jr Insights on adolescence from a life course perspective. J Res Adolesc. 2011; 21 :273–380. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Jones N. Between Good and Ghetto: African American Girls and Inner City Violence. New Brunswick, NJ: Rutgers Univ. Press; 2010. [ Google Scholar ]
• Joyner K, Udry JR. You don't bring me anything but down: adolescent romance and depression. J Health Soc Behav. 2000; 41 :369–91. [ PubMed ] [ Google Scholar ]
• Kao G. Parental influences on the educational outcomes of immigrant youth. Int Migr Rev. 2004; 38 :427–49. [ Google Scholar ]
• Kao G. Psychological well-being and educational achievement among immigrant youth. In: Hernandez DJ, editor. Children of Immigrants: Health, Adjustment, and Public Assistance. Washington, DC: Natl. Acad; 1999. pp. 410–77. [ PubMed ] [ Google Scholar ]
• Kim DH, Schneider B. Social capital in action: alignment of parental support in adolescents' transition to postsecondary education. Soc Forces. 2005; 84 :1181–206. [ Google Scholar ]
• King V, Silverstein M, Elder GH, Jr, Bengtson VL, Conger RD. Relations with grandparents: rural Midwest versus urban southern California. J Fam Issues. 2003; 24 :1044–1069. [ Google Scholar ]
• Kling J, Liebman J, Katz L. Experimental analysis of neighborhood effects. Econometrica. 2007; 75 :83–119. [ Google Scholar ]
• Kreager DA, Staff J. The sexual double standard and adolescent peer acceptance. Soc Psychol Q. 2009; 72 :143–64. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Kroger J. Identity Development: Adolescence through Adulthood. 2nd Thousand Oaks, CA: Sage; 2007. [ Google Scholar ]
• Lareau A. Unequal Childhoods: Class, Race, and Family Life. Berkeley: Univ. Calif. Press; 2004. [ Google Scholar ]
• Larson R, Brown BB, Mortimer J, editors. Adolescents' preparation for the future: perils and promise (special issue) J Res Adolesc. 2002; 12 (1):1–166. [ Google Scholar ]
• Larson RW, Richards MH, Moneta G, Holmbeck G, Duckett E. Changes in adolescents' daily interactions with their families from ages 10 to 18: disengagement and transformation. Dev Psychol. 1996; 32 :744–54. [ Google Scholar ]
• Lee JC, Staff J. When work matters: the varying impact of work intensity on high school dropout. Sociol Educ. 2007; 80 :158–78. [ Google Scholar ]
• Lenhart A, Purcell K, Smith A, Zickuhr K. Social Media and Mobile Internet Use Among Teens and Young Adults. Washington, DC: Pew Res Cent; 2010. [ Google Scholar ]
• Lucas SR. Effectively maintained inequality: education transitions, track mobility, and social background effects. Am J Sociol. 2001; 106 :1642–90. [ Google Scholar ]
• Mandara J, Gaylord-Harden NK, Richards MH, Ragsdale BL. The effects of changes in racial identity and self-esteem on changes in African American adolescents' mental health. Child Dev. 2009; 80 :1660–75. [ PubMed ] [ Google Scholar ]
• Manlove J, Ryan S, Franzetta K. Contraceptive use patterns across teens' sexual relationships: the role of relationships, partners, and sexual histories. Demography. 2007; 44 :603–21. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Marsh HW. Employment during high school: character building or a subversion of academic goals? Sociol Educ. 1991; 64 :172–89. [ Google Scholar ]
• Martin JK, Pescosolido BA, Olafsdottir S, Mcleod JD. The construction of fear: Americans' preferences for social distance from children and adolescents with mental health problems. J Health Soc Behav. 2007; 48 :50–67. [ PubMed ] [ Google Scholar ]
• Martin K. Puberty, Sexuality, and the Self: Boys and Girls at Adolescence. New York: Routledge; 1996. [ Google Scholar ]
• McCarthy B, Casey T. Love, sex, and crime: adolescent romantic relationships and offending. Am Sociol Rev. 2008; 73 :944–69. [ Google Scholar ]
• McDade TW. Lifestyle incongruity, social integration, and immune function in Samoan adolescents. Soc Sci Med. 2001; 53 :1351–62. [ PubMed ] [ Google Scholar ]
• McFarland DA. Curricular flows: trajectories, turning points, and assignment criteria in high school math careers. Sociol Educ. 2006; 79 :177–205. [ Google Scholar ]
• McLeod JD, Fettes DL. Trajectories of failure: the educational careers of children with mental health problems. Am J Sociol. 2007; 113 :653–701. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• McMorris BJ, Uggen C. Alcohol and employment in the transition to adulthood. J Health Soc Behav. 2000; 41 :276–94. [ PubMed ] [ Google Scholar ]
• Mickelson R. Subverting Swann: first- and second-generation segregation in the Charlotte-Mecklenburg schools. Am Educ Res J. 2001; 38 :215–52. [ Google Scholar ]
• Modell J, Goodman M. Historical perspectives. In: Feldman SS, Elliott GR, editors. At the Threshold: The Developing Adolescent. Cambridge, MA: Harvard Univ. Press; 1990. pp. 93–122. [ Google Scholar ]
• Moffitt TE. Adolescence-limited and life-course-persistent antisocial behavior: a developmental taxonomy. Psychol Rev. 1993; 100 :674–701. [ PubMed ] [ Google Scholar ]
• Mollborn S. Making the best of a bad situation: material resources and teenage parenthood. J Marriage Fam. 2007; 69 :92–104. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Morgan SL. On the Edge of Commitment: Educational Attainment and Race in the United States. Stanford, CA: Stanford Univ. Press; 2005. [ Google Scholar ]
• Mortimer JT. Working and Growing Up in America. Cambridge, MA: Harvard Univ. Press; 2003. [ Google Scholar ]
• Mortimer JT, Johnson MK. Adolescent part-time work and educational achievement. In: Borman K, Schneider B, editors. The Adolescent Years: Social Influences and Educational Challenges. Chicago: Univ. Chicago Press; 1998. pp. 183–206. [ Google Scholar ]
• Natl. Res. Counc. Protecting Youth at Work. Washington, DC: Natl Acad. Press; 1998. [ Google Scholar ]
• Newman KS. Working poor: low-wage employment in the lives of Harlem youth. In: Graber JA, Brooks-Gunn J, Petersen AC, editors. Transitions through Adolescence: Interpersonal Domains and Context. Mahwah, NJ: Lawrence Erlbaum; 1996. pp. 323–43. [ Google Scholar ]
• Newman KS. No Shame in my Game: The Working Poor in the Inner City. New York: Russell Sage Found; 1999. [ Google Scholar ]
• Ogbu JU. African American education: a cultural-ecological perspective. In: McAdoo HP, editor. Black Families. Thousand Oaks, CA: Sage; 1997. pp. 234–50. [ Google Scholar ]
• Ogden C, Carroll M, Curtin L, Lamb M, Flegal K. Prevalence of high body mass index in U.S. children and adolescents 2007–2008. JAMA. 2010; 303 :242–49. [ PubMed ] [ Google Scholar ]
• Oropesa RS, Landale N. Why do immigrant youths who never enroll in U.S. schools matter? Sociol Educ. 2009; 82 :240–66. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Paternoster R, Bushway S, Brame R, Apel R. The effect of teenage employment on delinquency and problem behaviors. Soc Forces. 2003; 82 :297–335. [ Google Scholar ]
• Pearce LD, Haynie DL. Intergenerational religious dynamics and adolescent delinquency. Soc Forces. 2004; 82 :1553–72. [ Google Scholar ]
• Pearson J, Muller C, Wilkinson L. Adolescent same-sex attraction and academic outcomes: the role of school attachment and engagement. Soc Probl. 2007; 54 :523–42. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Perreira KM, Harris KM, Lee D. Immigrant youth in the labor market. Work Occup. 2007; 34 :5–34. [ Google Scholar ]
• Portes A, Rumbaut RG. Legacies: The Story of the Immigrant Second Generation. Berkeley: Univ. Calif. Press; 2001. [ Google Scholar ]
• Portes A, Zhou M. The new second generation: segmented assimilation and its variants among post-1965 immigrant youth. Ann Am Acad Polit Soc Sci. 1993; 530 :740–98. [ Google Scholar ]
• Raskauskas J, Stoltz AD. Involvement in traditional and electronic bullying among adolescents. Dev Psychol. 2007; 43 :564–75. [ PubMed ] [ Google Scholar ]
• Reardon SF, Yun YT, Kurlaender M. Implications of income-based school assignment policies for racial school segregation. Educ Eval Policy Anal. 2006; 28 :49–75. [ Google Scholar ]
• Reiss D, Neiderhiser JM, Hetherington EM, Plomin R. The Relationship Code: Deciphering Genetic and Social Patterns in Adolescent Development. Cambridge, MA: Harvard Univ. Press; 2000. [ Google Scholar ]
• Reynolds J, Stewart M, Sischo L, McDonald R. Have adolescents become too ambitious? High school seniors' educational and occupational plans, 1976–2000. Soc Probl. 2006; 53 :186–206. [ Google Scholar ]
• Riegle-Crumb C. The path through math: course-taking trajectories and student performance at the intersection of gender and race/ethnicity. Am J Educ. 2006; 113 :101–22. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Rosenbaum J. Beyond College for All: Career Paths for the Forgotten Half. New York: Russell Sage Found; 2001. [ Google Scholar ]
• Rosenfield S, Vertefuille J, McAlpine D. Gender stratification and mental health: an exploration of dimensions of the self. Soc Psychol Q. 2000; 63 :208–23. [ Google Scholar ]
• Rothstein R. Class and Schools: Using Social, Economic, and Educational Reform to Close the Black-White Achievement Gap. New York: Teachers Coll. Press; 2004. [ Google Scholar ]
• Rumberger RW, Palardy GJ. Does segregation still matter? The impact of social composition on academic achievement in high school. Teach Coll Rec. 2005; 107 :1999–2045. [ Google Scholar ]
• Russell ST, Joyner K. Adolescent sexual orientation and suicide risk: evidence from a national study. Am J Public Health. 2001; 91 :1276–81. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Russell ST, Sigler-Andrews N. Adolescent sexuality and positive youth development. In: Perkins D, Borden L, Keith J, Villarruel FA, editors. Positive Youth Development: Beacons, Challenges, and Opportunities. Thousand Oaks, CA: Sage; 2003. pp. 146–61. [ Google Scholar ]
• Schneider B, Stevenson D. The Ambitious Generation: America's Teenagers, Motivated but Directionless. New Haven, CT: Yale Univ. Press; 1999. [ Google Scholar ]
• Schoenhals M, Tienda M, Schneider B. The educational and personal consequences of adolescent employment. Soc Forces. 1998; 77 :723–62. [ Google Scholar ]
• Schoeni RF, Ross KE. Material assistance from families during the transition to adulthood. See Settersten et al. 2005; 2005 :417–53. [ Google Scholar ]
• Schulenberg JE, O'Malley PM, Bachman JG, Johnston LD. Early adult transitions and their relation to well-being and substance use. See Settersten et al. 2005; 2005 :417–53. [ Google Scholar ]
• Seaton EK, Sellers RM, Scottham KM. The status model of racial identity development in African American adolescents: evidence of structure, trajectories, and well-being. Child Dev. 2006; 77 :1416–26. [ PubMed ] [ Google Scholar ]
• Sellers R, Smith M, Shelton J, Rowley S, Chavous T. Multidimensional model of racial identity: a reconceptualization of African American racial identity. Personal Soc Psychol Rev. 1998; 2 :18–39. [ PubMed ] [ Google Scholar ]
• Settersten RA Jr, Furstenberg FF Jr, Rumbaut RG, editors. On the Frontier of Adulthood: Theory, Research and Public Policy. Chicago: Univ. Chicago Press; 2005. [ Google Scholar ]
• Shanahan L, McHale SM, Osgood DW, Crouter AC. Conflict frequency with mothers and fathers from middle childhood to late adolescence: within- and between-families comparisons. Dev Psychol. 2007; 43 :539–50. [ PubMed ] [ Google Scholar ]
• Shulman S, Collins WA, editors. Romantic Relationships in Adolescence: Developmental Perspectives. San Francisco: Jossey-Bass; 1998. [ Google Scholar ]
• Staff J, Mortimer JT. Educational and work strategies from adolescence to early adulthood: consequences for educational attainment. Soc Forces. 2007; 85 :1169–94. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Stättin H, Kerr M. Parental monitoring: a reinterpretation. Child Dev. 2000; 71 :1070–83. [ PubMed ] [ Google Scholar ]
• Stättin H MagnussonD. Pubertal Maturation in Female Development. Hillsdale, NJ: Erlbaum; 1990. [ Google Scholar ]
• Steinberg LD. A social neuroscience perspective on adolescent risk-taking. Dev Rev. 2008; 28 :78–106. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Suarez-Orozco C, Rhodes J, Milburn M. Unraveling the immigrant paradox: academic engagement and disengagement among recently arrived immigrant youth. Youth Soc. 2009; 41 :151–85. [ Google Scholar ]
• Susman EJ. Psychobiology of persistent antisocial behavior: stress, early vulnerabilities and the attenuation hypothesis. Neurosci Biobehav Rev. 2006; 30 :376–89. [ PubMed ] [ Google Scholar ]
• Susman EJ, Dorn LD, Schiefelbein VL. Puberty, sexuality, and health. In: Lerner RM, Easterbrooks MA, Mistry J, editors. Handbook of Psychology: Vol 6 Developmental Psychology. New York: Wiley; 2003. pp. 295–324. [ Google Scholar ]
• Tyson K, Darity W, Castellino DR. It's not a ‘black thing’: understanding the burden of acting white and other dilemmas of high achievement. Am Sociol Rev. 2005; 70 :582–605. [ Google Scholar ]
• Umaña-Taylor AJ, Gonzales-Backen MA, Guimond AB. Latino adolescents' ethnic identity: Is there a developmental progression and does growth in ethnic identity predict growth in self-esteem? Child Dev. 2009; 80 :391–405. [ PubMed ] [ Google Scholar ]
• U.S. Census Bur. Table MS-2 Estimated Median Age at First Marriage, By Sex: 1890 to the Present. Washington, DC: U.S. Census Bur; 2006. http://www.census.gov/population/socdemo/hh-fam/ms2.pdf . [ Google Scholar ]
• Warren JR, LePore PC, Mare RD. Employment during high school: consequences for students' grades in academic courses. Am Educ Res J. 2000; 37 :943–69. [ Google Scholar ]
• Wilson WJ. When Work Disappears. New York: Vintage; 1996. [ Google Scholar ]
• Yau JP, Tasopoulos-Chan M, Smetana JG. Disclosure to parents about everyday activities among American adolescents from Mexican, Chinese, and European backgrounds. Child Dev. 2009; 80 :1481–98. [ PubMed ] [ Google Scholar ]
• Zhou M. Contemporary Chinese American: Immigration, Ethnicity, and Community Transformation. Philadelphia, PA: Temple Univ Press; 2009. [ Google Scholar ]

Reading Lists +

The review +, major adolescent stress reduces connection to future self.

3 April 2024

Research by

• Benjamin Ganschow
• Job van der Schalk
• Hal Hershfield
• Jean-Louis van Gelder
• Behavioral Decision Making

And thinking less about one’s adult life can reduce the pursuit of higher education

Making decisions that aren’t easy in the here and now, which will pay off down the line, is a tension many struggle with. It is central to the challenges of making healthier lifestyle choices today or committing to socking away money for retirement, rather than spending it pronto.

Past research by UCLA Anderson’s Hal Hershfield has advanced an understanding of a key mechanism for this behavioral challenge: We typically don’t have a tight relationship with our future self, which makes it harder to act in that stranger’s best interests. (In his book, Your Future S elf , Hershfield shares his and others’ research on how we can form a better link between today us, and tomorrow us.)

In research publish ed in the Journal of Early Adolescence, University of Leiden’s Benjamin Ganschow, Cardiff University’s Job van der Schalk, Vrije Universiteit Amsterdam’s Sven Zebel and University of Leiden’s Jean-Louis van Gelder, together with Hershfield, explore the extent to which one’s past experiences might impact one’s level of connectedness to future self.

Opt In to the Review Monthly Email Update.

The Past Is Prologue?

Leveraging data from an ongoing longitudinal study, they find that teens who experienced severe stress — death of a parent, divorce, placement in foster care, hospitalization — indeed had a lower sense of connectedness to their future self. Moreover, they found an increased likelihood those teens would not pursue an educational path that leads to college. 

The Zurich Project on the Social Development from Childhood into Adulthood started recording life experiences and perceptions of nearly 1,700 first graders in 2004 and continues to periodically check in with them. The researchers focused on data when participants were ages 12, 15, 17 and 20.

The Zurich Project asked participants if they have experienced any of nearly two dozen stressful events, including death of a close relationship, mental or physical illness, divorce of parents, failing a grade, being a victim of violence and sexual violence. The project also has participants convey their sense of connectedness to their future self 10 years out, using a visual prompt developed in previous research Hershfield collaborated on.

They found a significant negative correlation between the prevalence of stressful life events and the participant’s stated level of connectedness to their future self when asked at age 20. Interestingly, they found that when that stress occurred in adolescence — early/late/throughout — didn’t seem to change the level of connectedness. 

The researchers found that parents being involved ( helping with homework, say) was correlated with stronger future-self connectedness, but positive parenting ( praise for doing a good job) wasn’t a factor. Nor was the prevalence of corporal punishment or erratic discipline. 

Ganschow, van der Schalk, Zebel, Hershfield and van Gelder also measured two related aspects of future-self identification, but neither vividness (how well we can describe our future self), or valence (whether we see our future self as positive or negative) showed any meaningful correlation with stressful experiences as an adolescent. 

Small Intervention, Big Payoff

The researchers analyzed stress/connectiveness data in relation to two consequential paths measured at age 20: “delinquent” behaviors (driving without a license, purchase of illegal drugs, possession of a weapon, petty theft, and car theft) in the past few years and pursuit of an educational track that leads to university education. (In Switzerland, teens must choose a track for high school that focuses on either vocational training, or one that leads to university study.) 

The analysis showed no meaningful impact of stress/lower connectedness on acts of delinquency. There was a stronger correlation between higher stress/lower educational attainment and lower stress/higher educational attainment. 

The research team notes that a growing body of research offers up simple interventions that might help more stressed adolescents forge a better connection with their future self. Seeing a doctored photo of their older self, or writing letters to and from their future self or role-playing as their future self might help move the needle, which could improve educational outcomes.

Featured Faculty

Professor of Marketing and Behavioral Decision Making

About the Research

Ganschow, B., Zebel, S., Van der Schalk, J., Hershfield, H. E., & Van Gelder, J. L. (2023). Adolescent Stressful Life Events Predict Future Self-Connectedness in Adulthood. Journal of Early Adolescence , 02724316231216380.

Suggested Articles

Was Research — on Physicians and Noncompete Agreements — Before Its Time?

Unearthing the Negative Consequences of Managing to Quarterly Earnings

Is Amazon’s Fake Review Response 94 Days Too Late?

Related articles.

Another Political Trick? Inducing Forgetting By Mentioning Irrelevant Information

Positive views on, say, a social policy are more easily suppressed than negative ones

The Trade-Off Between Fairness and Accuracy in Algorithm Design

What happens when data is excluded?

Advancing the Study of Using Future-Self Images to Alter Behavior

Successful projects suggest a more thorough cataloging of how “vividness” nudges can help us delay gratification

How People Gather Information — or Don’t — to Make Decisions

Personal beliefs, especially among the less educated, often outweigh actual data

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• BOOK REVIEW
• 29 March 2024

The great rewiring: is social media really behind an epidemic of teenage mental illness?

• Candice L. Odgers 0

Candice L. Odgers is the associate dean for research and a professor of psychological science and informatics at the University of California, Irvine. She also co-leads international networks on child development for both the Canadian Institute for Advanced Research in Toronto and the Jacobs Foundation based in Zurich, Switzerland.

You can also search for this author in PubMed   Google Scholar

You have full access to this article via your institution.

Social-media platforms aren’t always social. Credit: Getty

The Anxious Generation: How the Great Rewiring of Childhood is Causing an Epidemic of Mental Illness Jonathan Haidt Allen Lane (2024)

Two things need to be said after reading The Anxious Generation . First, this book is going to sell a lot of copies, because Jonathan Haidt is telling a scary story about children’s development that many parents are primed to believe. Second, the book’s repeated suggestion that digital technologies are rewiring our children’s brains and causing an epidemic of mental illness is not supported by science. Worse, the bold proposal that social media is to blame might distract us from effectively responding to the real causes of the current mental-health crisis in young people.

Haidt asserts that the great rewiring of children’s brains has taken place by “designing a firehose of addictive content that entered through kids’ eyes and ears”. And that “by displacing physical play and in-person socializing, these companies have rewired childhood and changed human development on an almost unimaginable scale”. Such serious claims require serious evidence.

Collection: Promoting youth mental health

Haidt supplies graphs throughout the book showing that digital-technology use and adolescent mental-health problems are rising together. On the first day of the graduate statistics class I teach, I draw similar lines on a board that seem to connect two disparate phenomena, and ask the students what they think is happening. Within minutes, the students usually begin telling elaborate stories about how the two phenomena are related, even describing how one could cause the other. The plots presented throughout this book will be useful in teaching my students the fundamentals of causal inference, and how to avoid making up stories by simply looking at trend lines.

Hundreds of researchers, myself included, have searched for the kind of large effects suggested by Haidt. Our efforts have produced a mix of no, small and mixed associations. Most data are correlative. When associations over time are found, they suggest not that social-media use predicts or causes depression, but that young people who already have mental-health problems use such platforms more often or in different ways from their healthy peers 1 .

These are not just our data or my opinion. Several meta-analyses and systematic reviews converge on the same message 2 – 5 . An analysis done in 72 countries shows no consistent or measurable associations between well-being and the roll-out of social media globally 6 . Moreover, findings from the Adolescent Brain Cognitive Development study, the largest long-term study of adolescent brain development in the United States, has found no evidence of drastic changes associated with digital-technology use 7 . Haidt, a social psychologist at New York University, is a gifted storyteller, but his tale is currently one searching for evidence.

Of course, our current understanding is incomplete, and more research is always needed. As a psychologist who has studied children’s and adolescents’ mental health for the past 20 years and tracked their well-being and digital-technology use, I appreciate the frustration and desire for simple answers. As a parent of adolescents, I would also like to identify a simple source for the sadness and pain that this generation is reporting.

A complex problem

There are, unfortunately, no simple answers. The onset and development of mental disorders, such as anxiety and depression, are driven by a complex set of genetic and environmental factors. Suicide rates among people in most age groups have been increasing steadily for the past 20 years in the United States. Researchers cite access to guns, exposure to violence, structural discrimination and racism, sexism and sexual abuse, the opioid epidemic, economic hardship and social isolation as leading contributors 8 .

How social media affects teen mental health: a missing link

The current generation of adolescents was raised in the aftermath of the great recession of 2008. Haidt suggests that the resulting deprivation cannot be a factor, because unemployment has gone down. But analyses of the differential impacts of economic shocks have shown that families in the bottom 20% of the income distribution continue to experience harm 9 . In the United States, close to one in six children live below the poverty line while also growing up at the time of an opioid crisis, school shootings and increasing unrest because of racial and sexual discrimination and violence.

The good news is that more young people are talking openly about their symptoms and mental-health struggles than ever before. The bad news is that insufficient services are available to address their needs. In the United States, there is, on average, one school psychologist for every 1,119 students 10 .

Haidt’s work on emotion, culture and morality has been influential; and, in fairness, he admits that he is no specialist in clinical psychology, child development or media studies. In previous books, he has used the analogy of an elephant and its rider to argue how our gut reactions (the elephant) can drag along our rational minds (the rider). Subsequent research has shown how easy it is to pick out evidence to support our initial gut reactions to an issue. That we should question assumptions that we think are true carefully is a lesson from Haidt’s own work. Everyone used to ‘know’ that the world was flat. The falsification of previous assumptions by testing them against data can prevent us from being the rider dragged along by the elephant.

A generation in crisis

Two things can be independently true about social media. First, that there is no evidence that using these platforms is rewiring children’s brains or driving an epidemic of mental illness. Second, that considerable reforms to these platforms are required, given how much time young people spend on them. Many of Haidt’s solutions for parents, adolescents, educators and big technology firms are reasonable, including stricter content-moderation policies and requiring companies to take user age into account when designing platforms and algorithms. Others, such as age-based restrictions and bans on mobile devices, are unlikely to be effective in practice — or worse, could backfire given what we know about adolescent behaviour.

A third truth is that we have a generation in crisis and in desperate need of the best of what science and evidence-based solutions can offer. Unfortunately, our time is being spent telling stories that are unsupported by research and that do little to support young people who need, and deserve, more.

Nature 628 , 29-30 (2024)

doi: https://doi.org/10.1038/d41586-024-00902-2

Heffer, T., Good, M., Daly, O., MacDonell, E. & Willoughby, T. Clin. Psychol. Sci. 7 , 462–470 (2019).

Article   Google Scholar  

Hancock, J., Liu, S. X., Luo, M. & Mieczkowski, H. Preprint at SSRN https://doi.org/10.2139/ssrn.4053961 (2022).

Odgers, C. L. & Jensen, M. R. J. Child Psychol. Psychiatry 61 , 336–348 (2020).

Article   PubMed   Google Scholar  

Orben, A. Soc . Psychiatry Psychiatr. Epidemiol. 55 , 407–414 (2020).

Valkenburg, P. M., Meier, A. & Beyens, I. Curr. Opin. Psychol. 44 , 58–68 (2022).

Vuorre, M. & Przybylski, A. K. R. Sci. Open Sci. 10 , 221451 (2023).

Miller, J., Mills, K. L., Vuorre, M., Orben, A. & Przybylski, A. K. Cortex 169 , 290–308 (2023).

Martínez-Alés, G., Jiang, T., Keyes, K. M. & Gradus, J. L. Annu. Rev. Publ. Health 43 , 99–116 (2022).

Danziger, S. Ann. Am. Acad. Pol. Soc. Sci. 650 , 6–24 (2013).

US Department of Education. State Nonfiscal Public Elementary/Secondary Education Survey 2022–2023 (National Center for Education Statistics, 2024).

Google Scholar  

Download references

Competing Interests

The author declares no competing interests.

Related Articles

• Public health

Use fines from EU social-media act to fund research on adolescent mental health

Correspondence 09 APR 24

AI-fuelled election campaigns are here — where are the rules?

World View 09 APR 24

Why loneliness is bad for your health

News Feature 03 APR 24

Circulating myeloid-derived MMP8 in stress susceptibility and depression

Article 07 FEB 24

Only 0.5% of neuroscience studies look at women’s health. Here’s how to change that

World View 21 NOV 23

Bird flu outbreak in US cows: why scientists are concerned

News Explainer 08 APR 24

Adopt universal standards for study adaptation to boost health, education and social-science research

Correspondence 02 APR 24

Abortion-pill challenge provokes doubt from US Supreme Court

News 26 MAR 24

Junior Group Leader Position at IMBA - Institute of Molecular Biotechnology

The Institute of Molecular Biotechnology (IMBA) is one of Europe’s leading institutes for basic research in the life sciences. IMBA is located on t...

Austria (AT)

IMBA - Institute of Molecular Biotechnology

Husbandry Technician I

Memphis, Tennessee

St. Jude Children's Research Hospital (St. Jude)

Lead Researcher – Department of Bone Marrow Transplantation & Cellular Therapy

Researcher in the center for in vivo imaging and therapy, scientist or lead researcher (protein engineering, hematology, shengdar q. tsai lab).

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Adolescence in India pp 1–5 Cite as

Introduction to Adolescence in India: Issues, Challenges, and Possibilities

• Swati Patra 2  
• First Online: 09 March 2022

310 Accesses

The term ‘adolescence’ generates varied emotions, perception, and cognition within us. The fluidity of the adolescence phase of life highlights the role of socio-political-economic-cultural determinants influencing the developmental trajectories of adolescents. This affects significantly their development, health, and well-being. Given the huge demographic dividend of adolescents and young people in India and across the world, the key is to harness this potential resource to contribute actively towards their own development and progress as well as that of the society and nation. This requires that we not only discuss the issues, concerns, and challenges of adolescents but also the ways and possibilities for them to fulfil their potential, perform optimally, and thrive.

This is a preview of subscription content, log in via an institution .

Buying options

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info
• Durable hardcover edition

Tax calculation will be finalised at checkout

Purchases are for personal use only

Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design . Harvard University Press.

Google Scholar  

Ciccarelli, S. K., & White, J. N. (2018b). Psychology . (p. 342), Adapted by Girishwar Misra. Pearson.

Ciccarelli, S. K., & White, J. N. (2018a). Psychology . (p. 510), Adapted by Girishwar Misra. Pearson.

Devi, S. & Patra, S. (2019). Exploring mental health of adolescents in relation to their strengths, weaknesses and wishes . Unpublished manuscript.

Erikson, E. H. (1959). Growth and crises of the healthy personality. Psychological Issues, 1 , 50–100.

Hall, G. S. (1904). Adolescence: Its psychology and its relation to physiology, anthropology, sociology, sex, crime, religion and education (Vol. 1 and 2). Prentice-Hall.

http://mospi.nic.in/sites/default/files/publication_reports/Youth_in_India-2017.pdf

https://www.unicef.org/india/what-we-do/adolescent-development-participation

National Research Council and Institute of Medicine. (2002). Community programs to promote youth development. The National Academics Press. https://doi.org/10.17226/10022 . https://www.nap.edu/read/10022/chapter/6

Nussbam, M. C. (2003). Capabilities as fundamental entitlements: Sen and social justice. Feminist Economics, 9 , 33–59.

Article   Google Scholar  

Rogers, C. R. (1961). On becoming a person: A therapist’s view of psychotherapy . Houghton Mifflin Co.

Sen, A. (1992). Inequality reexamined . Oxford University Press.

Sen, A. (1997). From income inequality to economic inequality. Southern Economic Journal, 64 (2), 384–401.

Snyder, C. R., Lopez, S. J., & Pedrotti, J. T. (2011). Positive psychology: The scientific and practical explorations of human strengths (2nd ed, p. 4). Sage South Asia edition.

Strategy Handbook. (2014). Rashtriya Kishor Swasthya Karyakram. Adolescent Health Division, Ministry of Health and Family Welfare Government of India. January 2014.

Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes . Harvard University Press.

Download references

Author information

Authors and affiliations.

Faculty of Psychology, School of Social Sciences, Indira Gandhi National Open University (IGNOU), New Delhi, India

Swati Patra

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Swati Patra .

Editor information

Editors and affiliations, rights and permissions.

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Cite this chapter.

Patra, S. (2022). Introduction to Adolescence in India: Issues, Challenges, and Possibilities. In: Patra, S. (eds) Adolescence in India. Springer, Singapore. https://doi.org/10.1007/978-981-16-9881-1_1

Download citation

DOI : https://doi.org/10.1007/978-981-16-9881-1_1

Published : 09 March 2022

Publisher Name : Springer, Singapore

Print ISBN : 978-981-16-9880-4

Online ISBN : 978-981-16-9881-1

eBook Packages : Behavioral Science and Psychology Behavioral Science and Psychology (R0)

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

• Skip to main content
• Skip to FDA Search
• Skip to in this section menu
• Skip to footer links

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

U.S. Food and Drug Administration

•   Search
•   Menu
• Science & Research
• Science and Research Special Topics
• Advancing Regulatory Science

Adapting a Measure of Heart Failure to an Adolescent Population

CERSI Collaborators: Stanford University: Christopher Almond, MD, MPH; Chiu-Yu Chen, MD, PhD; Korey Hood, PhD; Molly Tanenbaum, PhD

FDA Collaborators: Center for Devices and Radiological Health: Fraser Bocell, PhD; Vasum Peiris, MD, MPH; Anindita Saha; Brittany Caldwell, PhD; Michelle Tarver, MD, PhD

CERSI Subcontractors: Mayo Clinic: Jonathan Johnson, MD; Jennifer Ridgeway, PhD; Emma Behnken

CERSI In-Kind Collaborators: OptumLabs - William Crown, PhD; University of San Francisco - Sanket Dhruva, MD

Non-Federal Entity Collaborators: Johnson and Johnson- Karla Childers, MSJ, Paul Coplan, ScD, MBA, Stephen Johnston, MSc

Project Start Date: December 2018

Regulatory Science Challenge

The evaluation and approval of medical devices in pediatric populations lags far behind adult populations. Many devices, including life-saving devices, are adapted and used in children without the benefit of first going through a well-controlled study to evaluate their safety and effectiveness. One way to encourage studies of devices in pediatric populations is to provide additional measures to facilitate efficient evidence generation, such as Patient-Reported Outcomes Measures (PROMs). PROMs are questionnaires about health status that are answered by the patient. PROMs have become an important method to include the patient voice in clinical studies and can help provide evidence of the safety and effectiveness of a device and evaluate the impact a treatment on a patient’s life. However, PROMs must be developed to fit the clinical research in which they will be used, and companies within the medical device industry do not always have the resources necessary to develop new PROMs for new areas of research. Thus, this project was conceived to provide an example of how to efficiently and cost-effectively adapt an existing PROM, making changes to the questions, to fit a new population; in this case, pediatric heart failure patients.

The adaptation of a PROM for appropriate use in this population will provide an additional method for collecting evidence to support the use of devices in pediatric heart failure. Additionally, it provides an example of methods other stakeholders can use to adapt other PROMs for use in device studies.

Project Description and Goals

The aim of this project is to understand how adolescents perceive the symptoms and impact of their heart failure, while adapting existing adult PROMs to capture and quantify this perception for use in clinical care and regulatory decision making. The development of a PROM is a multi-step undertaking where each subsequent step is informed by the prior. The major steps include a literature review of existing publications and evidence, a short survey to capture clinician input, focus groups and interviews to confirm the question selection and inform adaptation, the completion of the adapted PROM, and a study to evaluate the PROM’s properties in a larger sample. The final PROM will be available for further testing and potential use in pediatric cardiology device submissions.

Research Outcomes/Results

An analysis of interview transcripts found common and consistent themes from patient interviews, which included:

• Symptoms of fatigue, shortness of breath, and chest discomfort.
• Limitations in ability to perform ordinary tasks, participate in extracurricular activities, and keep up with peers.
• Social and emotional impacts from being treated differently by others.
• Burden of medical care.

Caregivers reported similar symptoms and impacts on patient function, and further described social exclusion by peers and caregiver anxiety about illness burden in the future such as college and career limitations, ability to have children, etc.

Research Impacts

Incorporating patient preference information into decisions that FDA makes about regulating devices is one of the major goals of FDA’s Center for Devices and Radiological Health (CDRH). Study findings show that patients prefer specific outcomes related to prostate ablation therapies like HIFU. The study results may help inform the design and regulation of current and future prostate tissue ablation devices by providing information about outcomes that patients most desire.

Publications

• PMID: 34677594; Citation: Wallach JD, Deng Y, McCoy RG, Dhruva SS, Herrin J, Berkowitz A, Polley EC, Quinto K, Gandotra C, Crown W, Noseworthy P, Yao X, Shah ND, Ross JS, Lyon TD. Real-world Cardiovascular Outcomes Associated With Degarelix vs Leuprolide for Prostate Cancer Treatment.  JAMA Netw Open. 2021;4(10):e2130587. doi:10.1001/jamanetworkopen.2021.30587 .
• PMID: 36191949; Citation: Deng Y, Polley EC, Wallach JD, Dhruva SS, Herrin J, Quinto K, Gandotra C, Crown W, Noseworthy P, Yao X, Lyon TD, Shah ND, Ross JS, McCoy RG. Emulating the GRADE trial using real world data: retrospective comparative effectiveness study. BMJ . 2022 Oct 3;379:e070717. doi: 10.1136/bmj-2022-070717 .

This paper is in the following e-collection/theme issue:

Published on 10.4.2024 in Vol 26 (2024)

Effectiveness of a Web-Based Individual Coping and Alcohol Intervention Program for Children of Parents With Alcohol Use Problems: Randomized Controlled Trial

Authors of this article:

Original Paper

• Håkan Wall 1 , PhD   ; 
• Helena Hansson 2 , PhD   ; 
• Ulla Zetterlind 3 , PhD   ; 
• Pia Kvillemo 1 , PhD   ; 
• Tobias H Elgán 1 , PhD  

1 Stockholm Prevents Alcohol and Drug Problems, Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Stockholm, Sweden

2 School of Social Work, Faculty of Social Sciences, Lund University, Lund, Sweden

3 Clinical Health Promotion Centre, Department of Health Sciences, Lund University, Lund, Sweden

Corresponding Author:

Tobias H Elgán, PhD

Stockholm Prevents Alcohol and Drug Problems, Centre for Psychiatry Research

Department of Clinical Neuroscience

Karolinska Institutet, & Stockholm Health Care Services

Norra Stationsgatan 69

Stockholm, 11364

Phone: 46 700011003

Email: [email protected]

Background: Children whose parents have alcohol use problems are at an increased risk of several negative consequences, such as poor school performance, an earlier onset of substance use, and poor mental health. Many would benefit from support programs, but the figures reveal that only a small proportion is reached by existing support. Digital interventions can provide readily accessible support and potentially reach a large number of children. Research on digital interventions aimed at this target group is scarce. We have developed a novel digital therapist-assisted self-management intervention targeting adolescents whose parents had alcohol use problems. This program aims to strengthen coping behaviors, improve mental health, and decrease alcohol consumption in adolescents.

Objective: This study aims to examine the effectiveness of a novel web-based therapist-assisted self-management intervention for adolescents whose parents have alcohol use problems.

Methods: Participants were recruited on the internet from social media and websites containing health-related information about adolescents. Possible participants were screened using the short version of the Children of Alcoholics Screening Test-6. Eligible participants were randomly allocated to either the intervention group (n=101) or the waitlist control group (n=103), and they were unblinded to the condition. The assessments, all self-assessed, consisted of a baseline and 2 follow-ups after 2 and 6 months. The primary outcome was the Coping With Parents Abuse Questionnaire (CPAQ), and secondary outcomes were the Center for Epidemiological Studies Depression Scale, Alcohol Use Disorders Identification Test (AUDIT-C), and Ladder of Life (LoL).

Results: For the primary outcome, CPAQ, a small but inconclusive treatment effect was observed (Cohen d =–0.05 at both follow-up time points). The intervention group scored 38% and 46% lower than the control group on the continuous part of the AUDIT-C at the 2- and 6-month follow-up, respectively. All other between-group comparisons were inconclusive at either follow-up time point. Adherence was low, as only 24% (24/101) of the participants in the intervention group completed the intervention.

Conclusions: The findings were inconclusive for the primary outcome but demonstrate that a digital therapist-assisted self-management intervention may contribute to a reduction in alcohol consumption. These results highlight the potential for digital interventions to reach a vulnerable, hard-to-reach group of adolescents but underscore the need to develop more engaging support interventions to increase adherence.

Trial Registration: ISRCTN Registry ISRCTN41545712; https://www.isrctn.com/ISRCTN41545712?q=ISRCTN41545712

International Registered Report Identifier (IRRID): RR2-10.1186/1471-2458-12-35

Introduction

Children who grow up with parents who have substance use problems or disorders face extraordinary challenges. Approximately 20% of all children have parents with alcohol problems [ 1 - 5 ], while approximately 5% have parents with alcohol use disorders [ 4 , 6 , 7 ]. Children growing up with parental substance abuse are at an increased risk of several negative outcomes, such as psychiatric morbidity [ 8 - 12 ]; poor intellectual, cognitive, and academic achievement [ 13 - 15 ]; domestic physical abuse [ 16 ]; and early drinking onset and the development of substance use problems [ 9 , 17 , 18 ]. Thus, children exposed to parental substance abuse comprise a target group for selective interventions and prevention strategies [ 19 - 22 ].

In Sweden, municipalities account for most of the support offered to these children. An annual survey by the junior association of the Swedish branch of Movendi International (ie, an international temperance movement) reported that 97% of all municipalities provided support resources [ 23 ]. However, estimates from the same survey showed that approximately 2% of the children in the target group received support. Hence, an overwhelming majority never receives support, mainly because of difficulties in identifying and attracting them to intervention programs [ 22 , 24 ].

The internet has become an appealing way to reach and support a large number of people [ 25 , 26 ]. Web-based interventions seem particularly attractive to adolescents, as they generally use digital technology and social media. Furthermore, research has shown that adolescents regard the internet as inviting because it is a readily accessible, anonymous way of seeking help [ 27 ]. Web-based interventions can reduce the stigma associated with face-to-face consultations in health care settings [ 28 ], and young people appreciate the flexibility of completing web-based sessions to fit their own schedules [ 29 ]. The positive effects of web-based interventions have been detected across a broad range of conditions. A recent review by Hedman-Lagerlöf et al [ 30 ] concluded that therapist-supported internet-based cognitive behavioral therapy for adults yielded similar effects as face-to-face therapy. To date, most web-based interventions have been designed for adults. Although the number of web-based interventions targeting children or adolescents is increasing [ 25 , 31 - 33 ], the number of digital interventions aimed at children of substance-abusing parents is still scarce [ 22 , 34 - 38 ]. Those described in the literature, however, all have in common that they are quite extensive, with a duration over several weeks, and a brief digital intervention could complement these more extended interventions. For instance, our research group initiated a study on a web-based group chat for 15- to 25-year-old individuals who have parents with mental illness or substance use problems [ 35 ]. The duration of the program is 8 weeks, and it is a translated version of a program from the Netherlands [ 34 ], which has been shown to have inconclusive treatment effects [ 39 ]. In Sweden, 2 other programs with inconclusive treatment effects have been tested that target significant others and their children [ 37 , 38 ]. Finally, a digital intervention developed in Australia for 18- to 25-year-old individuals with parents with mental illness or substance use disorder [ 36 ] was tested in a pilot study demonstrating positive findings [ 40 ].

To meet the need for a brief, web-based intervention that targets adolescents having parents with alcohol problems and build on the evidence base of digital interventions targeting this vulnerable group, we developed a novel internet-delivered therapist-assisted self-management intervention called “Alcohol and Coping.” Our program originated from a manual-based face-to-face intervention called the “Individual Coping and Alcohol Intervention Program” (ICAIP) [ 41 , 42 ]. Previous studies on both the ICAIP, which aimed at college students having parents with alcohol problems, and a coping skills intervention program, which aimed at spouses of partners with alcohol dependency [ 43 ], have demonstrated positive effects regarding decreased alcohol consumption and improved mental health and coping behaviors [ 41 - 44 ]. Furthermore, the results from these studies underscore the importance of improving coping skills [ 42 , 44 ]. Among college students, those who received a combination of coping skills and an alcohol intervention program had better long-term outcomes [ 42 ].

The aim of this study was to test the effectiveness of Alcohol and Coping among a sample of adolescents aged 15-19 years with at least 1 parent with alcohol use problems. We hypothesized that the intervention group would be superior to the control group in improving coping skills. Secondary research questions concerned the participants’ improvement in (1) depression, (2) alcohol consumption, and (3) quality of life.

This study was a parallel-group randomized controlled trial in which participants were randomized to either the intervention or waitlist control group in a 1:1 allocation ratio. The trial design is illustrated in Figure 1 .

Recruitment and Screening

The participants were recruited from August 2012 to December 2013 through advertisements on social media (Facebook). The advertisements targeted individuals aged 15-19 years with Facebook accounts. Participants were recruited on the internet through advertisements on websites containing health-related information about adolescents. The advertisements included the text, “Do your parents drink too much? Participate in a study.” The advertisement contained an invitation to perform a web-based, self-assessed screening procedure. In addition to questions about age and sex, participants were screened for having parents with alcohol problems using the short version of the Children of Alcoholics Screening Test-6 (CAST-6), developed from a 30-item original version [ 45 ]. The CAST-6 is a 6-item true-false measure designed to assess whether participants perceive their parents’ alcohol consumption to be problematic. The CAST-6 has demonstrated high internal consistency ( r =0.92-0.94), test-retest reliability ( r =0.94), and high validity as compared to the 30-item version ( r =0.93) using the recommended threshold score of 3 or higher [ 45 , 46 ]. We previously translated the CAST-6 into Swedish and validated the translated version among 1450 adolescents, showing good internal consistency (α=.88), excellent test-retest reliability (intraclass correlation coefficient=0.93), and loading into 1 latent factor [ 47 ]. Additional inclusion criteria included having access to a computer and the internet and being sufficiently fluent in Swedish. Participants were excluded from the study and were referred to appropriate care if there were indications of either suicidal or self-inflicted harmful behaviors. Individuals eligible for inclusion received further information about the study and were asked to provide consent to participate by providing an email address.

Data Collection and Measures

All assessments were administered through email invitations containing a hyperlink to the web-based self-reported assessments. Up to 3 reminders were sent through email at 5, 10, and 15 days after the first invitation. A baseline assessment (t 0 ) was collected before randomization, and follow-up assessments were conducted at 2 and 6 months (t 1 and t 2 , respectively) after the initial assessment.

Participants were asked for age, sex, whether they lived with a parent (mother and father, mother or father, mother or father and stepparent, or alternate between mother and father), where their parents were born (Sweden or a Nordic country excluding Sweden or outside of the Nordic countries), parental status (employed, student, on parental leave, or unemployed), and any previous or present participation in support activities for children having parents with alcohol use problems. The primary outcome was coping, measured using the Coping With Parents Abuse Questionnaire (CPAQ) based on the Coping Behavior Scale developed by Orford et al [ 48 ]. Secondary outcomes were the Center for Epidemiological Studies Depression Scale (CES-DC) [ 49 ], the 3-question Alcohol Use Disorders Identification Test (AUDIT-C) [ 50 ], and the Ladder of Life (LoL), which measures the overall quality of life by asking about the participants’ past, present, and future ratings of their overall life satisfaction [ 50 ]. CPAQ has been shown to be reliable [ 41 , 42 ]. For this study, this scale was factor-analyzed to reduce the number of questions from 37 to 20. The resulting scale measures 6 coping typologies (discord, emotion, control, relationship, avoidance, and taking specific action) using a 4-point Likert scale, with a threshold score above 50 points (out of 80) indicating dysfunctional coping behavior. The CES-DC measures depressive symptoms during the past week using a 4-point Likert scale, where a higher total score indicates more depressive symptoms [ 49 ]. A cutoff score of ≥16 indicates symptoms of moderate depression, while a score of ≥30 indicates symptoms of severe depression [ 51 , 52 ]. The scale measures 4 dimensions of depression: depressed mood, tiredness, inability to concentrate, and feelings of being outside and lonely, and has positively stated items [ 52 ]. Additionally, this scale is a general measure of childhood psychopathology [ 53 ] and has been demonstrated to be reliable and valid among Swedish adolescents [ 52 ]. Alcohol consumption was measured using a modified AUDIT-C, which assesses the frequency of drinking, quantity consumed on a typical occasion, and frequency of heavy episodic drinking (ie, binge drinking) [ 50 ] using a 30-day perspective (as opposed to the original 12-month perspective). These questions have previously been translated into Swedish [ 54 ], and a score of ≥4 and ≥5 points for women and men, respectively, was used as a cutoff for risky drinking. This scale has been demonstrated to be reliable and valid for Swedish adolescents [ 55 ]. Furthermore, 2 questions were added concerning whether the participants had ever consumed alcohol to the point of intoxication and their age at the onset of drinking and intoxication. The original version of the LoL was designed for adults and asked the respondents to reflect on their, present, and future life status from a 5-year perspective on a 10-point Visual Analogue Scale representing life status from “worst” to “best” possible life imaginable [ 56 ]. A modified version for children, using a time frame of 1 year, has been used previously in Sweden [ 57 ] and was used in this study.

Randomization

After completing the baseline assessment, each participant was allocated to either the intervention or the control group. An external researcher generated an unrestricted random allocation sequence using random allocation software [ 58 ]. Neither the participants nor the researchers involved in the study were blinded to group allocation.

Based on the order in which participants were included in the study, they were allocated to 1 of the 2 study groups and informed of their allocation by email. Additionally, those who were randomized to the intervention group received a hyperlink to the Alcohol and Coping program, whereas the control group participants received information that they would gain access to Alcohol and Coping after the last follow-up assessment (ie, the waitlist control group). All participants were informed about other information and support available through web pages, notably drugsmart [ 59 ], which contains general information and facts about alcohol and drugs, in addition to more specific information about having substance-abusing parents. Telephone numbers and contact information for other organizations and primary health care facilities were also provided.

The Intervention

As noted previously, Alcohol and Coping is derived from the aforementioned manual-based face-to-face ICAIP intervention program [ 41 , 42 ]. The ICAIP consists of a combination of an alcohol intervention program, which is based on the short version of the Brief Alcohol Screening and Intervention for College Students program [ 60 ], and a coping intervention program developed for the purpose of the ICAIP [ 41 , 42 ]. Like the original ICAIP intervention, Alcohol and Coping builds on psychoeducational principles and includes components such as film-based lectures, various exercises, and both automated and therapist-assisted feedback. Briefly, once the participants logged into the Alcohol and Coping platform, they were introduced to the program, which followed the pattern of a board game ( Figure 2 ). Following the introduction, participants took part in 3 film-based lectures (between 8 and 15 minutes each, Figure 3 ) concerning alcohol problems within the family. The respective lectures included information about (1) dependency in general as well as the genetic and environmental risks for developing dependency, (2) family patterns and how the family adapts to the one having alcohol problems, and (3) attitudes toward alcohol and how they influence drinking and the physiological effects of alcohol. After completing the lectures, the participants were asked to answer 2 questions about their own alcohol consumption (ie, how often they drink and how often they drink to intoxication), followed by an automatic feedback message that depended on their answers. It was then suggested that the participants log out of the intervention for a 1- to 2-day break. The reason for this break was to give the participants a chance to digest all information and impressions. When they logged back into the intervention, they were asked to answer 20 questions about their coping strategies, which were also followed by automatic feedback. This feedback comprised a library covering all the prewritten feedback messages, each of which was tailored to the participants’ specific answers. The participants then participated in a 5-minute–long film-based lecture on emotion and problem-focused coping in relation to family alcohol problems ( Figure 3 ). This was followed by 4 exercises where the participants read through vignette-like stories from 4 fictional persons describing their everyday lives related to coping and alcohol problems in the family. The stories are presented by film-based introductions that are each 1-2 minutes long. Participants were then requested to respond to each story by describing how the fictive person could have coped with their situation. As a final exercise, participants were asked to reflect on their own family situation and how they cope with situations. The participants then had to take a break for a few days.

During the break, a therapist composed individual feedback that covered reflections and confirmation of the participant’s exercises and answers to questions and included suggestions on well-suited coping strategies. Additionally, the therapist encouraged the participants to talk to others in their surroundings, such as friends, teachers, or coaches, and seek further support elsewhere, such as from municipal social services, youth health care centers, or other organizations. Finally, the therapist reflected on the participants’ alcohol consumption patterns and reminded them of increased genetic and environmental risks. Those who revealed patterns of risky alcohol use were encouraged to look at 2 additional film-based lectures with more information about alcohol and intoxication (4 minutes) and alcohol use and dependency (5 minutes). Participants received this feedback once they logged back into the program, but they also had the opportunity to receive feedback through email. The total estimated effective time for completing the program was about 1 hour, but as described above, there was 1 required break when the individualized feedback was written. To keep track of the dose each participant received, each of the 15 components in the program ( Figure 1 ) is equal to completing 6.7% (1/15) of the program in total.

Sample Size

The trial was designed to detect a medium or large effect size corresponding to a standardized mean difference (Cohen d >0.5) [ 61 ]. An a priori calculation of the estimated sample size, using the software G*Power (G*Power Team) [ 62 ], revealed that a total of 128 participants (64 in each group) were required to enroll in the trial (power=0.80; α=.05; 2-tailed). However, to account for an estimated attrition rate of approximately 30% [ 34 ], it was necessary to enroll a minimum of 128/(1 – 0.3) = 183 participants in the trial. After a total of 204 individuals had been recruited and randomized into 2 study arms, recruitment was ended.

Statistical Analysis

Data were analyzed according to the intention-to-treat (ITT) principle, and all randomized participants were included, irrespective of whether they participated in the trial. The 4 research variables were depression (CES-DC), coping (CPAQ), alcohol use (AUDIT-C), and life status (LoL).

Data analysis consisted of comparing outcome measurements at t 1 and t 2 . The baseline measurement t 0 value was added as an adjustment variable in all models. The resulting data from CPAQ, CES-DC, and LoL were normally distributed and analyzed using linear mixed models. The resulting AUDIT-C scores were nonnormally distributed, with an excess of 0 values, and were analyzed using a 2-part model for longitudinal data. This model is sufficiently flexible to account for numerous 0 reports. This was achieved by combining a logistic generalized linear mixed model (GLMM) for the 0 parts and a skewed continuous GLMM for the non-0 alcohol consumption parts. R-package brms (Bayesian regression models using Stan; R Foundation for Statistical Computing) [ 63 ], a higher-level interface for the probabilistic programming language Stan [ 64 ], and a custom brms family for a marginalized 2-part lognormal distribution were used to fit the model [ 65 ]. The logistic part of the model represents the subject-specific effects on the odds of reporting no drinking. The continuous part was modeled using a gamma GLMM with a log link. The exponentiated treatment effect represents the subject-specific ratio of the total AUDIT-C scores between the treatment and waitlist control groups for those who reported drinking during the specific follow-up period.

Handling of Missing Data

GLMMs include all available data and provide unbiased ITT estimates under the assumption that data are missing at random, meaning that the missing data can be explained by existing data. However, it is impossible to determine whether the data are missing at random or whether the missing data are due to unobserved factors [ 66 ]. Therefore, we also assumed that data were not missing at random, and subsequent sensitivity analyses were performed [ 66 ]. We used the pattern mixture method, which assumes not missing at random, to compare those who completed the follow-up at 6 months (t 2 ) with those who did not (but completed the 2-month follow-up). The overall effect of this model is a combination of the effects of each subgroup. We also tested the robustness of the results by performing ANCOVAs at the 2-month follow-up, both using complete cases and with missing values imputed using multilevel multiple imputation.

The effect of the program was estimated using Cohen d , where a value of approximately 0.2 indicates a small effect size and values of approximately 0.5 and 0.8 indicate medium and large effect sizes, respectively [ 61 ].

Ethical Considerations

All procedures were performed in accordance with the ethical standards of the institutional or national research committees, the 1964 Helsinki Declaration and its later amendments, and comparable ethical standards. Informed consent was obtained from all the participants included in the study. This study was approved by the Swedish Ethical Review Authority (formerly the Regional Ethical Review Board in Stockholm, No. 2011/1648-31/5).

To enhance the response rates, participants received a cinema gift certificate corresponding to approximately EUR 11 (US $12) as compensation for completing each assessment. If a participant completed all assessments, an additional gift certificate was provided. The participants could subsequently receive 4 cinema gift certificates totaling EUR 44 (US $48).

The trial profile is depicted in Figure 1 and reveals that 2722 individuals who were aged between 15 and 19 years performed the screening procedure. A total of 1448 individuals did not fulfill the inclusion criteria and were excluded, leaving 1274 eligible participants. Another 1070 individuals were excluded because they did not provide informed consent or complete the baseline assessment, leaving 204 participants who were allocated to 1 of the 2 study groups. A total of 140 (69%) and 131 (64%) participants completed t 1 and t 2 assessments, respectively. Of the participants in the intervention group (n=101), 63% (n=64) registered an account on the Alcohol and Coping website, 35% (n=35) completed the alcohol intervention section, and 24% (n=24) completed both the alcohol and coping intervention sections.

Sample Characteristics

The mean age of the sample was 17.0 (SD 1.23) years, and the vast majority were female, with both parents born in Sweden and currently working ( Table 1 ). Approximately one-third of the participants reported living with both parents. The mean score on the CAST-6 was 5.33 (SD 0.87) out of a total of 6, and the majority of the sample (147/204, 72.1%) perceived their father to have alcohol problems. Approximately 12% (25/204) had never consumed alcohol, whereas approximately 70% (144/204) had consumed alcohol at a level of intoxication. The mean age at onset was 13.7 (SD 2.07) years and the age at first intoxication was 14.8 (SD 1.56) years. The proportion of participants with symptoms of at least moderate depression was 77.5% (158/204), of whom 55.1% (87/158) had symptoms of severe depression and 42.6% (87/204) had symptoms of dysfunctional coping behaviors. The percentage of participants who consumed alcohol at a risky level was 39.7% (81/204). Table 1 provides complete information regarding the study sample.

a Significance levels calculated by Pearson chi-square statistics for categorical variables and 2-tailed t tests for continuous variables.

Treatment Effects

For the primary outcome, coping behavior (CPAQ), we found a small but inconclusive treatment effect in favor of treatment at both 2 (t 1 ) and 6 (t 2 ) months (Cohen d =–0.05 at both t 1 and t 2 ). For the secondary outcome, alcohol use (AUDIT-C), we found a treatment effect in that the intervention group scored 38% less than the control group on the continuous part (ie, drinking when it occurred) at t 1 and 46% less at t 2 . Regarding depression (CES-DC) and life status (LoL), all between-group comparisons of treatment effects were inconclusive at both follow-up time points ( Table 2 ).

a CPAQ: Coping With Parents Abuse Questionnaire.

b CES-DC: Center for Epidemiological Studies Depression Scale.

c LoL: Ladder of Life.

d AUDIT-C: Alcohol Use Disorders Identification Test.

e N/A: not applicable.

Missing Data

In contrast to the ITT analyses, the sensitivity analyses showed that the treatment group, averaged over the levels of dropout, scored higher (ie, a negative effect) on the main outcome, coping behavior (CPAQ), at t 1 (2.44; P =.20). However, the results remain inconclusive.

Dose-Response Effects

We did not find any evidence for greater involvement in the program being linked to improved outcomes with regard to coping behavior.

We did not find any support for the primary hypothesis: the intervention was not superior to the control condition with regard to coping behavior. Inconclusive results with small effect sizes were observed at both follow-up time points. However, for the secondary outcomes, we found that those in the intervention group who drank alcohol drank approximately 40%-50% less than those in the control group at both follow-ups. These results corroborate previous findings on the precursor face-to-face ICAIP intervention program, demonstrating that participants who received a combined alcohol and coping intervention reported superior outcomes with regard to alcohol-related outcomes compared to participants in the other 2 study arms, who received only a coping or alcohol intervention [ 41 , 42 ]. In contrast to this study, Hansson et al [ 42 ] found that all groups improved their coping skills, although the between-group comparisons were inconclusive and the improvements were maintained over time. These differences could be explained by the different settings in which the precursor program was provided (ie, face-to-face to young adults in a university setting), whereas this study targeted young people (15-19 years of age) through a web-based digital intervention. Additionally, the poor adherence in this study may explain the absence of primary results favoring the intervention group. In a recent study, parents without alcohol problems were recruited to participate in a randomized trial evaluating the web-based SPARE (Supportive Parenting and Reinforcement) program to improve children’s mental health and reduce coparents’ alcohol use. In line with our study, the authors did not find the primary outcome of the SPARE program to be superior to that of the active control group (which received written psychoeducation); however, both groups reported decreased coparental alcohol consumption [ 38 ].

Considering that approximately 3600 children in 2022 participated in various forms of support provided by Swedish municipalities [ 23 ], our recruitment activities reached a large number of eligible individuals, pointing to the potential of finding these children on these platforms. There were unexpectedly high levels of depression among the participants in this study. Although the intervention did not target depressive symptoms per se , there was a trend for the intervention group to have decreased depression levels compared to the control group. A large proportion of participants had symptoms of severe depression, which may have aggravated their capacity for improvement at follow-up [ 28 , 67 ]. Targeting dysfunctional coping patterns could affect an individual’s perceived mental health, and studies have shown that healthy coping strategies positively affect depression and anxiety in a positive way [ 68 ]. Using dysfunctional coping strategies, such as negative self-talk and alcohol consumption, can lead to depressive symptoms [ 69 ]. Targeting these symptoms in the context of healthy and unhealthy coping strategies may be a viable route to fostering appropriate coping strategies that work in the long run. Given that the young people who were reached by the intervention in this study displayed high levels of depression, future interventions for this group should include programs targeting depressive symptoms.

Almost 37% (37/101) of the intervention group did not log into the intervention at all, and only 24% (24/101) of the intervention group participants completed all parts of the program. The fact that a high proportion of the participants had symptoms of severe depression could explain the low adherence. Another reason could be that the initial film-based lectures were too long to maintain the participants’ attention, as the lectures ranged from 8-15 minutes. Yet a final reason could be that we had a 1- to 2-day break built into the intervention, and for unknown reasons, some participants did not log back into the intervention. However, we did not find a dose-response relationship indicating favorable outcomes for those who completed more of the program content. High levels of attrition are not uncommon in self-directed programs such as the one in this study; for example, in a study on a smoking cessation intervention, 37% of the participants never logged into the platform [ 70 ], and in a self-directed intervention for problem gamblers, a majority dropped out after 1 week and none completed the entire program [ 71 ]. Increased intervention adherence is a priority when developing new digital interventions, particularly for young people. One method is to use more persuasive technologies, such as primary tasks, dialogue, and social support [ 72 ]. Considering children whose parents have mental disorders, Grové and Reupert [ 73 ] suggested that digital interventions should include components such as providing information about parental mental illness, access to health care, genetic risk, and suggestions for how children might initiate conversations with parents who have the illness. These suggestions should be considered in future studies on interventions for youths whose parents have substance use problems. Representatives of the target group and other relevant stakeholders should also be involved in coproducing new interventions to increase the probability of developing more engaging programs [ 74 ]. Moreover, one cannot expect study participants to return to the program more than once, and for the sake of adherence, briefer interventions should not encourage participants to log-out for a break. To keep adherence at an acceptable level, similar future interventions for this target group should also consider having symptoms of severe depression as an exclusion criterion [ 28 , 67 ]. Further, to improve adherence, strategies of coproduction could be used where all stakeholders, including the target group, are involved in intervention development [ 75 ]. Other important factors identified to improve adherence to digital interventions are to make the content relatable, useful, and even more interactive [ 76 ]. Those participants who have symptoms of severe depression should be referred to other appropriate health care. Finally, it is probably beneficial to develop shorter psychoeducative film-based lectures than ours, lasting up to 15 minutes. Future self-directed digital interventions targeting this population should, therefore, focus on a very brief and focused intervention, which, based on theory, has the potential to foster healthy coping behaviors that can lead to an increased quality of life and improved mental health for this group of young people.

Another concern for future projects would be to use a data-driven approach during the program development phase, where A/B testing can be used to test different setups of the program to highlight which setup works best. Another aspect that must be considered is the fast-changing world of technology, where young people are exposed to an infinite number of different apps that grab their attention, which also calls for interventions to be short and to the point. Furthermore, if the program is to spread and become generally available, one must consider that keeping the program alive for a longer period will require funding and staffing for both product management and technical support.

Strengths and Limitations

This study had several strengths. First, Alcohol and Coping is a web-based intervention program, and it appears as if the internet is a particularly promising way to provide support to adolescents growing up with parents with alcohol problems because it offers an anonymous means of communicating and makes intervention programs readily accessible [ 25 ]. Our recruitment strategies reached a considerable number of interested and eligible individuals, demonstrating the potential for recruiting through social media and other web platforms. Additionally, this program is one of the first brief web-based interventions aimed at adolescents with parents with alcohol-related problems. We used the CAST-6, which has been validated among Swedish adolescents [ 47 ], to screen eligible participants. Another strength is that the intervention program involved personalized, tailored feedback in the form of prewritten automatic messages and therapist-written personalized feedback, both of which have proven to be important components of web-based interventions aimed at adolescents [ 77 , 78 ]. Finally, this study evaluated the effectiveness of the Alcohol and Coping program using a randomized controlled trial design, which is considered the strongest experimental design with regard to allocation bias.

This study had some limitations. First, the design with a passive waitlist control group and an active intervention group, both unblinded to study allocation, may have resulted in biased estimates of treatment effects. Intervention adherence was low, and most of the study participants had symptoms of depression, where 55% (87/158) had symptoms of severe depression. This may have contributed to the small and overall inconclusive effects on the primary outcomes of this study. Many digital interventions have problems with low adherence, and in a review by Välimäki et al [ 79 ], some studies reported adherence rates as low as 10%. A vast proportion of the study participants were women, making the findings difficult to generalize to men. However, another limitation concerns selection bias and external validity. We recruited study participants through social media and other relevant websites containing health-related information, including information about parents with alcohol-related problems. It is, therefore, possible that the study population can be classified as “information-seeking” adolescents, who may have different personality traits relative to other adolescents in the same home situation. Additionally, as an inclusion criterion was having ready access to computers and the internet, it is possible that participants belonging to a lower socioeconomic class were underrepresented in the study. It should also be noted that the data presented here were collected approximately 10 years ago. However, we believe our findings make an important contribution to the field since, like our intervention, many recent web-based interventions use strategies of psychoeducation, films, exercises, questions, and feedback. Further, the number of web-based interventions for this target group remains scarce in the literature, which underscores the need for future research. Finally, the study was powered to detect a medium effect size. However, given the small effect sizes detected in this study, it is plausible that too few participants were recruited to detect differences between the groups.

Implications for Practice

Although growing up with parents who have alcohol problems per se is not sufficient for developing psychosocial disorders, many children need support to manage their situation. Therefore, it is difficult to recruit children to support these groups. In Sweden, not even 2% of all children growing up with parental alcohol problems attend face-to-face support groups provided by municipalities.

Offering support through web-based intervention programs seems particularly attractive to adolescents whose parents have alcohol-related problems. To date, evidence for such programs is scarce, and there is an urgent need to develop and evaluate digital interventions targeting this group of adolescents. This study makes important contributions to this novel field of research. The results provide insight into effective strategies for delivering intervention programs to children of parents with substance abuse issues, highlighting the potential for digital interventions to reach a vulnerable, hard-to-reach group of adolescents. Our findings underscore the need to develop more engaging interventions in coproduction with the target group.

Conclusions

We found that a digital therapist-assisted self-management intervention for adolescents whose parents have alcohol use problems contributed to a reduction in the adolescents’ own alcohol consumption. This result highlights the potential for digital interventions to reach a large, vulnerable, and hard-to-reach group of adolescents with support efforts. Findings were inconclusive for all other outcomes, which may be attributable to low adherence. This points to the need for future research on developing more engaging digital interventions to increase adherence among adolescents.

Acknowledgments

This work was undertaken on behalf of the Swedish Council for Information on Alcohol and Other Drugs (CAN) and was supported by grants from the Swedish National Institute of Public Health and the Swedish Council for Working Life and Social Research.

Conflicts of Interest

HH and UZ developed the study interventions. However, the parties did not derive direct financial income from these interventions. HW, PK, and THE declare no conflicts of interest.

CONSORT-eHEALTH checklist (V 1.6.1).

• Haugland SH, Elgán TH. Prevalence of parental alcohol problems among a general population sample of 28,047 Norwegian adults: evidence for a socioeconomic gradient. Int J Environ Res Public Health. 2021;18(10):5412. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Elgán TH, Leifman H. Prevalence of adolescents who perceive their parents to have alcohol problems: a Swedish national survey using a web panel. Scand J Public Health. 2013;41(7):680-683. [ CrossRef ] [ Medline ]
• Laslett AM, Ferris J, Dietze P, Room R. Social demography of alcohol-related harm to children in Australia. Addiction. 2012;107(6):1082-1089. [ CrossRef ] [ Medline ]
• Manning V, Best DW, Faulkner N, Titherington E. New estimates of the number of children living with substance misusing parents: results from UK national household surveys. BMC Public Health. 2009;9:377. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Grant BF. Estimates of US children exposed to alcohol abuse and dependence in the family. Am J Public Health. 2000;90(1):112-115. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Raninen J, Elgán TH, Sundin E, Ramstedt M. Prevalence of children whose parents have a substance use disorder: findings from a Swedish general population survey. Scand J Public Health. 2016;44(1):14-17. [ CrossRef ] [ Medline ]
• Christoffersen MN, Soothill K. The long-term consequences of parental alcohol abuse: a cohort study of children in Denmark. J Subst Abuse Treat. 2003;25(2):107-116. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Martikainen PN, Korhonen K, Moustgaard H, Aaltonen M, Remes H. Substance abuse in parents and subsequent risk of offspring psychiatric morbidity in late adolescence and early adulthood: a longitudinal analysis of siblings and their parents. Soc Sci Med. 2018;217:106-111. [ CrossRef ] [ Medline ]
• Jääskeläinen M, Holmila M, Notkola IL, Raitasalo K. Mental disorders and harmful substance use in children of substance abusing parents: a longitudinal register-based study on a complete birth cohort born in 1991. Drug Alcohol Rev. 2016;35(6):728-740. [ CrossRef ] [ Medline ]
• Velleman R, Templeton LJ. Impact of parents' substance misuse on children: an update. BJPsych Adv. Apr 11, 2018;22(2):108-117. [ FREE Full text ] [ CrossRef ]
• Ohannessian CM, Hesselbrock VM, Kramer J, Bucholz KK, Schuckit MA, Kuperman S, et al. Parental substance use consequences and adolescent psychopathology. J Stud Alcohol. 2004;65(6):725-730. [ CrossRef ] [ Medline ]
• Johnson JL, Leff M. Children of substance abusers: overview of research findings. Pediatrics. 1999;103(5 Pt 2):1085-1099. [ CrossRef ] [ Medline ]
• Berg L, Bäck K, Vinnerljung B, Hjern A. Parental alcohol-related disorders and school performance in 16-year-olds-a Swedish national cohort study. Addiction. 2016;111(10):1795-1803. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Casas-Gil MJ, Navarro-Guzman JI. School characteristics among children of alcoholic parents. Psychol Rep. 2002;90(1):341-348. [ CrossRef ] [ Medline ]
• McGrath CE, Watson AL, Chassin L. Academic achievement in adolescent children of alcoholics. J Stud Alcohol. 1999;60(1):18-26. [ CrossRef ] [ Medline ]
• Velleman R, Templeton L, Reuber D, Klein M, Moesgen D. Domestic abuse experienced by young people living in families with alcohol problems: results from a cross‐european study. Child Abuse Rev. Nov 24, 2008;17(6):387-409. [ CrossRef ]
• Rothman EF, Edwards EM, Heeren T, Hingson RW. Adverse childhood experiences predict earlier age of drinking onset: results from a representative US sample of current or former drinkers. Pediatrics. 2008;122(2):e298-e304. [ CrossRef ] [ Medline ]
• Anda RF, Whitfield CL, Felitti VJ, Chapman D, Edwards VJ, Dube SR, et al. Adverse childhood experiences, alcoholic parents, and later risk of alcoholism and depression. Psychiatr Serv. 2002;53(8):1001-1009. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Straussner SLA, Fewell CH. A review of recent literature on the impact of parental substance use disorders on children and the provision of effective services. Curr Opin Psychiatry. 2018;31(4):363-367. [ CrossRef ] [ Medline ]
• Calhoun S, Conner E, Miller M, Messina N. Improving the outcomes of children affected by parental substance abuse: a review of randomized controlled trials. Subst Abuse Rehabil. 2015;6:15-24. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Emshoff JG, Price AW. Prevention and intervention strategies with children of alcoholics. Pediatrics. 1999;103(5 Pt 2):1112-1121. [ CrossRef ] [ Medline ]
• Cuijpers P. Prevention programmes for children of problem drinkers: a review. Drugs Educ Prev Policy. 2009;12(6):465-475. [ CrossRef ]
• Wannberg H. Plats för barnen—Om kommunernas stöd till barn som växer upp med missbrukande föräldrar [Make room for the children—municipalities and their support for children who grow up with parents with substance abuse]. Stockholm, Sweden. Junis, IOGT-NTO's ungdomsförbund; 2023.
• Elgán TH, Leifman H. Children of substance abusing parents: a national survey on policy and practice in Swedish schools. Health Policy. 2011;101(1):29-36. [ CrossRef ] [ Medline ]
• de Sousa D, Fogel A, Azevedo J, Padrão P. The effectiveness of web-based interventions to promote health behaviour change in adolescents: a systematic review. Nutrients. 2022;14(6):1258. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Andersson G. Internet-delivered psychological treatments. Annu Rev Clin Psychol. 2016;12:157-179. [ FREE Full text ] [ CrossRef ] [ Medline ]
• King R, Bambling M, Lloyd C, Gomurra R, Smith S, Reid W, et al. Online counselling: the motives and experiences of young people who choose the internet instead of face to face or telephone counselling. Couns Psychother Res. 2007;6(3):169-174. [ CrossRef ]
• Borghouts J, Eikey E, Mark G, De Leon C, Schueller SM, Schneider M, et al. Barriers to and facilitators of user engagement with digital mental health interventions: systematic review. J Med Internet Res. 2021;23(3):e24387. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Boggs JM, Beck A, Felder JN, Dimidjian S, Metcalf CA, Segal ZV. Web-based intervention in mindfulness meditation for reducing residual depressive symptoms and relapse prophylaxis: a qualitative study. J Med Internet Res. 2014;16(3):e87. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Hedman-Lagerlöf E, Carlbring P, Svärdman F, Riper H, Cuijpers P, Andersson G. Therapist-supported internet-based cognitive behaviour therapy yields similar effects as face-to-face therapy for psychiatric and somatic disorders: an updated systematic review and meta-analysis. World Psychiatry. 2023;22(2):305-314. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Lehtimaki S, Martic J, Wahl B, Foster KT, Schwalbe N. Evidence on digital mental health interventions for adolescents and young people: systematic overview. JMIR Ment Health. 2021;8(4):e25847. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Li J, Theng YL, Foo S. Game-based digital interventions for depression therapy: a systematic review and meta-analysis. Cyberpsychol Behav Soc Netw. 2014;17(8):519-527. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Pennant ME, Loucas CE, Whittington C, Creswell C, Fonagy P, Fuggle P, et al. Computerised therapies for anxiety and depression in children and young people: a systematic review and meta-analysis. Behav Res Ther. 2015;67:1-18. [ CrossRef ] [ Medline ]
• Woolderink M, Smit F, van der Zanden R, Beecham J, Knapp M, Paulus A, et al. Design of an internet-based health economic evaluation of a preventive group-intervention for children of parents with mental illness or substance use disorders. BMC Public Health. 2010;10:470. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Elgán TH, Kartengren N, Strandberg AK, Ingemarson M, Hansson H, Zetterlind U, et al. A web-based group course intervention for 15-25-year-olds whose parents have substance use problems or mental illness: study protocol for a randomized controlled trial. BMC Public Health. 2016;16(1):1011. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Maybery D, Reupert A, Bartholomew C, Cuff R, Duncan Z, Foster K, et al. A web-based intervention for young adults whose parents have a mental illness or substance use concern: protocol for a randomized controlled trial. JMIR Res Protoc. 2020;9(6):e15626. [ FREE Full text ] [ CrossRef ] [ Medline ]
• EÉk N, Romberg K, Siljeholm O, Johansson M, Andreasson S, Lundgren T, et al. Efficacy of an internet-based community reinforcement and family training program to increase treatment engagement for AUD and to improve psychiatric health for CSOs: a randomized controlled trial. Alcohol Alcohol. 2020;55(2):187-195. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Siljeholm O, Lindner P, Johansson M, Hammarberg A. An online self-directed program combining Community Reinforcement Approach and Family Training and parenting training for concerned significant others sharing a child with a person with problematic alcohol consumption: a randomized controlled trial. Addict Sci Clin Pract. 2022;17(1):49. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Woolderink M. Mind the gap: evaluation of an online preventive programme for adolescents with mentally ill or addicted parents. Maastricht University. 2016. URL: https://cris.maastrichtuniversity.nl/ws/portalfiles/portal/7281149/c5531.pdf [accessed 2024-03-14]
• Maybery D, Reupert A, Bartholomew C, Cuff R, Duncan Z, McAuliffe C, et al. An online intervention for 18-25-year-old youth whose parents have a mental illness and/or substance use disorder: a pilot randomized controlled trial. Early Interv Psychiatry. 2022;16(11):1249-1258. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Hansson H, Rundberg J, Zetterlind U, Johnsson KO, Berglund M. An intervention program for university students who have parents with alcohol problems: a randomized controlled trial. Alcohol Alcohol. 2006;41(6):655-663. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Hansson H, Rundberg J, Zetterlind U, Johnsson KO, Berglund M. Two-year outcome of an intervention program for university students who have parents with alcohol problems: a randomized controlled trial. Alcohol Clin Exp Res. 2007;31(11):1927-1933. [ CrossRef ] [ Medline ]
• Zetterlind U, Hansson H, Aberg-Orbeck K, Berglund M. Effects of coping skills training, group support, and information for spouses of alcoholics: a controlled randomized study. Nord J Psychiatry. 2001;55(4):257-262. [ CrossRef ] [ Medline ]
• Hansson H, Zetterlind U, Aberg-Orbeck K, Berglund M. Two-year outcome of coping skills training, group support and information for spouses of alcoholics: a randomized controlled trial. Alcohol Alcohol. 2004;39(2):135-140. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Hodgins DC, Maticka-Tyndale E, El-Guebaly N, West M. The CAST-6: development of a short-form of the Children of Alcoholics Screening Test. Addict Behav. 1993;18(3):337-345. [ CrossRef ] [ Medline ]
• Hodgins DC, Shimp L. Identifying adult children of alcoholics: methodological review and a comparison of the CAST-6 with other methods. Addiction. 1995;90(2):255-267. [ Medline ]
• Elgán TH, Berman AH, Jayaram-Lindström N, Hammarberg A, Jalling C, Källmén H. Psychometric properties of the short version of the children of alcoholics screening test (CAST-6) among Swedish adolescents. Nord J Psychiatry. 2021;75(2):155-158. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Orford J, Guthrie S, Nicholls P, Oppenheimer E, Egert S, Hensman C. Self-reported coping behavior of wives of alcoholics and its association with drinking outcome. J Stud Alcohol. 1975;36(9):1254-1267. [ CrossRef ] [ Medline ]
• Schoenbach VJ, Kaplan BH, Grimson RC, Wagner EH. Use of a symptom scale to study the prevalence of a depressive syndrome in young adolescents. Am J Epidemiol. 1982;116(5):791-800. [ CrossRef ] [ Medline ]
• Bush K, Kivlahan DR, McDonell MB, Fihn SD, Bradley KA. The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test. Arch Intern Med. 1998;158(16):1789-1795. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Myers JK, Weissman MM. Use of a self-report symptom scale to detect depression in a community sample. Am J Psychiatry. 1980;137(9):1081-1084. [ CrossRef ] [ Medline ]
• Olsson G, von Knorring AL. Depression among Swedish adolescents measured by the self-rating scale Center for Epidemiology Studies-Depression Child (CES-DC). Eur Child Adolesc Psychiatry. 1997;6(2):81-87. [ CrossRef ] [ Medline ]
• Fendrich M, Weissman MM, Warner V. Screening for depressive disorder in children and adolescents: validating the Center for Epidemiologic Studies Depression Scale for Children. Am J Epidemiol. 1990;131(3):538-551. [ CrossRef ] [ Medline ]
• Bergman H, Källmen H, Rydberg U, Sandahl C. Tio frågor om alkohol identifierar beroendeproblem. Psykometrisk prövning på psykiatrisk akutmottagning [Ten questions about alcohol as identifier of addiction problems. Psychometric tests at an emergency psychiatric department]. Läkartidningen. 1998;95(43):4731-4735. [ FREE Full text ]
• Källmén H, Berman AH, Jayaram-Lindström N, Hammarberg A, Elgán TH. Psychometric properties of the AUDIT, AUDIT-C, CRAFFT and ASSIST-Y among Swedish adolescents. Eur Addict Res. 2019;25(2):68-77. [ CrossRef ] [ Medline ]
• Andrews FM, Withey SB. Developing measures of perceived life quality: results from several national surveys. Soc Indic Res. 1974;1(1):1-26. [ CrossRef ]
• Nagy E. Barns känsla av sammanhang—En valideringsstudie av BarnKASAM i årskurserna 1-6 (ålder 7-12 år) [Children's sense of coherence—a study validating SOC for children in grades 1-6 (7-12 years old)]. Lunds Universitet [Lund University]. 2004. URL: https://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=1358959&fileOId=1358960 [accessed 2024-03-14]
• Saghaei M. Random allocation software for parallel group randomized trials. BMC Med Res Methodol. 2004;4:26. [ FREE Full text ] [ CrossRef ] [ Medline ]
• drugsmart. URL: https://www.drugsmart.se/ [accessed 2024-03-19]
• Dimeff LA, Baer JS, Kivlahan DR, Marlatt GA. Brief Alcohol Screening and Intervention for College Students: A Harm Reduction Approach. New York. The Guilford Press; 1999.
• Cohen J. A power primer. Psychol Bull. 1992;112(1):155-159. [ CrossRef ] [ Medline ]
• Faul F, Erdfelder E, Lang A, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2):175-191. [ CrossRef ] [ Medline ]
• Bürkner PC. brms: an R package for bayesian multilevel models using stan. J Stat Soft. 2017;80(1):1-28. [ FREE Full text ] [ CrossRef ]
• Carpenter B, Gelman A, Hoffman MD, Lee D, Goodrich B, Betancourt M, et al. Stan: a probabilistic programming language. J Stat Softw. 2017;76(1):1-32. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Magnusson K, Nilsson A, Carlbring P. Modeling longitudinal gambling data: challenges and opportunities. PsyArxiv. Preprint posted online on September 12, 2019. [ FREE Full text ] [ CrossRef ]
• Coertjens L, Donche V, De Maeyer S, Vanthournout G, Van Petegem P. To what degree does the missing-data technique influence the estimated growth in learning strategies over time? A tutorial example of sensitivity analysis for longitudinal data. PLoS One. 2017;12(9):e0182615. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Kunas SL, Lautenbacher LM, Lueken PU, Hilbert K. Psychological predictors of cognitive-behavioral therapy outcomes for anxiety and depressive disorders in children and adolescents: a systematic review and meta-analysis. J Affect Disord. 2021;278:614-626. [ CrossRef ] [ Medline ]
• Stallman HM, Lipson SK, Zhou S, Eisenberg D. How do university students cope? An exploration of the health theory of coping in a US sample. J Am Coll Health. 2022;70(4):1179-1185. [ CrossRef ] [ Medline ]
• Stallman HM, Beaudequin D, Hermens DF, Eisenberg D. Modelling the relationship between healthy and unhealthy coping strategies to understand overwhelming distress: a Bayesian network approach. J Affect Disord Rep. 2021;3:100054. [ FREE Full text ] [ CrossRef ]
• McClure JB, Shortreed SM, Bogart A, Derry H, Riggs K, St John J, et al. The effect of program design on engagement with an internet-based smoking intervention: randomized factorial trial. J Med Internet Res. 2013;15(3):e69. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Humphrey G, Bullen C. Smartphone-based problem gambling evaluation and technology testing initiative ('SPGeTTI'): final report reference 354913/00 for the Ministry of Health. National Institute for Health Innovation (NIHI), Auckland UniServices Ltd, The Univerisy of Auckland. 2019. URL: https:/​/www.​health.govt.nz/​system/​files/​documents/​publications/​20190424-spgetti-354913-00-final-report.​pdf [accessed 2024-03-14]
• Kelders SM, Kok RN, Ossebaard HC, Van Gemert-Pijnen JEWC. Persuasive system design does matter: a systematic review of adherence to web-based interventions. J Med Internet Res. 2012;14(6):e152. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Grové C, Reupert A. Moving the field forward: developing online interventions for children of parents with a mental illness. Child Youth Serv Rev. 2017;82:354-358. [ CrossRef ]
• Moffat BM, Haines-Saah RJ, Johnson JL. From didactic to dialogue: assessing the use of an innovative classroom resource to support decision-making about cannabis use. Drugs Educ Prev Policy. 2016;24(1):85-95. [ FREE Full text ] [ CrossRef ]
• Bevan Jones R, Stallard P, Agha SS, Rice S, Werner-Seidler A, Stasiak K, et al. Practitioner review: co-design of digital mental health technologies with children and young people. J Child Psychol Psychiatry. 2020;61(8):928-940. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Garrido S, Millington C, Cheers D, Boydell K, Schubert E, Meade T, et al. What works and what doesn't work? A systematic review of digital mental health interventions for depression and anxiety in young people. Front Psychiatry. 2019;10:759. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Crutzen R, de Nooijer J, Brouwer W, Oenema A, Brug J, de Vries NK. Strategies to facilitate exposure to internet-delivered health behavior change interventions aimed at adolescents or young adults: a systematic review. Health Educ Behav. 2011;38(1):49-62. [ CrossRef ] [ Medline ]
• Milward J, Drummond C, Fincham-Campbell S, Deluca P. What makes online substance-use interventions engaging? A systematic review and narrative synthesis. Digit Health. 2018;4:2055207617743354. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Välimäki M, Anttila K, Anttila M, Lahti M. Web-based interventions supporting adolescents and young people with depressive symptoms: systematic review and meta-analysis. JMIR Mhealth Uhealth. 2017;5(12):e180. [ FREE Full text ] [ CrossRef ] [ Medline ]

Abbreviations

Edited by YH Lin; submitted 24.08.23; peer-reviewed by X Zhang, C Asuzu, D Liu; comments to author 28.01.24; revised version received 08.02.24; accepted 27.02.24; published 10.04.24.

©Håkan Wall, Helena Hansson, Ulla Zetterlind, Pia Kvillemo, Tobias H Elgán. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 10.04.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

• Share full article

Advertisement

Supported by

Youth Gender Medications Limited in England, Part of Big Shift in Europe

Five European countries have recently restricted hormone treatments for adolescents with gender distress. They have not banned the care, unlike many U.S. states.

By Azeen Ghorayshi

Azeen Ghorayshi reports on transgender health and visited the world’s first youth gender clinic in Amsterdam this fall.

The National Health Service in England started restricting gender treatments for children this month, making it the fifth European country to limit the medications because of a lack of evidence of their benefits and concern about long-term harms.

England’s change resulted from a four-year review released Tuesday evening by Dr. Hilary Cass, an independent pediatrician. “For most young people, a medical pathway will not be the best way to manage their gender-related distress,” the report concluded. In a related editorial published in a medical journal, Dr. Cass said the evidence that youth gender treatments were beneficial was “built on shaky foundations.”

The N.H.S. will no longer offer drugs that block puberty , except for patients enrolled in clinical research. And the report recommended that hormones like testosterone and estrogen, which spur permanent physical changes, be prescribed to minors with “extreme caution.” (The guidelines do not apply to doctors in private practice, who serve a small fraction of the population.)

England’s move is part of a broader shift in northern Europe, where health officials have been concerned by soaring demand for adolescent gender treatments in recent years. Many patients also have mental health conditions that make it difficult to pinpoint the root cause of their distress, known as dysphoria.

In 2020, Finland’s health agency restricted the care by recommending psychotherapy as the primary treatment for adolescents with gender dysphoria. Two years later, Sweden restricted hormone treatments to “exceptional cases.”

In December, regional health authorities in Norway designated youth gender medicine as a “treatment under trial,” meaning hormones will be prescribed only to adolescents in clinical trials. And in Denmark, new guidelines being finalized this year will limit hormone treatments to transgender adolescents who have experienced dysphoria since early childhood.

Several transgender advocacy groups in Europe have condemned the changes , saying that they infringe on civil rights and exacerbate the problems of overstretched health systems. In England, around 5,800 children were on the waiting list for gender services at the end of 2023, according to the N.H.S.

“The waiting list is known to be hell,” said N., a 17-year-old transgender boy in southern England who requested to withhold his full name for privacy. He has been on the waiting list for five years, during which time he was diagnosed with autism and depression. “On top of the trans panic our own government is pushing, we feel forgotten and left behind,” he said.

In the United States, Republican politicians have cited the pullback in Europe to justify laws against youth gender medicine. But the European policies are notably different from the outright bans for adolescents passed in 22 U.S. states, some of which threaten doctors with prison time or investigate parents for child abuse. The European countries will still allow gender treatments for certain adolescents and are requiring new clinical trials to study and better understand their effects.

“We haven’t banned the treatment,” said Dr. Mette Ewers Haahr, a psychiatrist who leads Denmark’s sole youth gender clinic, in Copenhagen. Effective treatments must consider human rights and patient safety, she said. “You have to weigh both.”

In February, the European Academy of Paediatrics acknowledged the concerns about youth gender medicine. “The fundamental question of whether biomedical treatments (including hormone therapy) for gender dysphoria are effective remains contested,” the group wrote. In contrast, the American Academy of Pediatrics last summer reaffirmed its endorsement of the care, stating that hormonal treatments are essential and should be covered by health insurers, while also commissioning a systematic review of evidence.

Europeans pioneered the use of gender treatments for young people. In the 1990s, a clinic in Amsterdam began giving puberty-suppressing drugs to adolescents who had felt they were a different gender since early childhood.

The Dutch doctors reasoned that puberty blockers could give young patients with gender dysphoria time to explore their identity and decide whether to proceed with hormones to ultimately transition. For patients facing male puberty, the drugs would stave off the physical changes — such as a deeper voice and facial hair — that could make it more difficult for them to live as women in adulthood. The Dutch team’s research, which was first published in 2011 and tracked a carefully selected group of 70 adolescents, found that puberty blockers, in conjunction with therapy, improved psychological functioning.

That study was hugely influential, inspiring clinics around the world to follow the Dutch protocol. Referrals to these clinics began to surge around 2014, though the numbers remain small. At Sweden’s clinic, for example, referrals grew to 350 adolescents in 2022 from around 50 in 2014. In England, those numbers grew to 3,600 referrals in 2022 from 470 in 2014.

Clinics worldwide reported that the increase was largely driven by patients raised as girls. And unlike the participants in the original Dutch study, many of the new patients did not experience gender distress until puberty and had other mental health conditions, including depression and autism.

Given these changes, some clinicians are questioning the relevance of the original Dutch findings for today’s patients.

“The whole world is giving the treatment, to thousands, tens of thousands of young people, based on one study,” said Dr. Riittakerttu Kaltiala, a psychiatrist who has led the youth gender program in Finland since 2011 and has become a vocal critic of the care.

Dr. Kaltiala’s own research found that about 80 percent of patients at the Finnish clinic were born female and began experiencing gender distress later in adolescence. Many patients also had psychological issues and were not helped by hormonal treatments, she found. In 2020, Finland severely limited use of the drugs.

Around the same time, the Swedish government commissioned a rigorous research review that found “insufficient” evidence for hormone therapies for youth. In 2022, Sweden recommended hormones only for “exceptional cases,” citing in part the uncertainty around how many young people may choose to stop or reverse their medical transitions down the line, known as detransitioning.

Even the original Dutch clinic is facing pressure to limit patients receiving the care. In December, a public documentary series in the Netherlands questioned the basis of the treatments. And in February, months after a far-right political party swept an election in a country long known as socially liberal , the Dutch Parliament passed a resolution to conduct research comparing the current Dutch approach with that of other European countries.

“I would have liked that the Netherlands was an island,” said Dr. Annelou de Vries, a psychiatrist who led the original Dutch research and still heads the Amsterdam clinic. “But of course, we are not — we are also part of the global world. So in a way, if everybody is starting to be concerned, of course, these concerns come also to our country.”

In England, brewing concerns about the surge of new patients reached a boiling point in 2018, when 10 clinicians at the N.H.S.’s sole youth gender clinic, known as the Tavistock Gender Identity Development Service, formally complained that they felt pressure to quickly approve children, including those with serious mental health problems, for puberty blockers.

In 2021, Tavistock clinicians published a study of 44 children who took puberty blockers that showed a different result from the Dutch: The patients given the drugs, on average, saw no impact on psychological function.

Although the drugs did not lessen thoughts of self-harm or the severity of dysphoria, the adolescents were “resoundingly thrilled to be on the blocker,” Dr. Polly Carmichael, the head of the clinic, said at a 2016 conference . And 43 of the 44 study participants later chose to start testosterone or estrogen, raising questions about whether the drug was serving its intended purpose of giving adolescents time to consider whether a medical transition was right for them.

In 2020, the N.H.S. commissioned Dr. Cass to carry out an independent review of the treatments. She commissioned scientific reviews and considered international guidelines of the care. She also met with young people and their families, trans adults, people who had detransitioned, advocacy groups and clinicians.

The review concluded that the N.H.S.’s standard of care was inadequate, with long waiting lists for access to drug treatments and few routes to address the mental health concerns that may be contributing to gender distress. The N.H.S. shuttered the Tavistock center last month and opened two new youth gender clinics, which Dr. Cass said should have a “holistic” approach, with more support for those with autism, depression and eating disorders, as well as psychotherapy to help adolescents explore their identities.

“Children and young people have just been really poorly served,” Dr. Cass said in an interview with the editor of The British Medical Journal, released Tuesday. She added, “I can’t think of another area of pediatric care where we give young people potentially irreversible treatments and have no idea what happens to them in adulthood.”

The changes enacted by the N.H.S. this month are “an acknowledgment that our concerns were, in fact, valid,” said Anna Hutchinson, a clinical psychologist in London who was one of the Tavistock staff members who raised concerns in 2018. “It’s reassuring that we’re going to return to a more robust, evidence-based pathway for decisions relating to these children.”

Some critics said that Europe, like the United States, had also been influenced by a growing backlash against transgender people.

In Britain, for example, a yearslong fight over a proposed law that would have made it easier for transgender people to change the gender on their identification documents galvanized a political movement to try to exclude transgender women from women’s sports, prisons and domestic violence shelters.

“The intention with the Cass review is to be neutral, but I think that neutral has maybe moved,” said Laurence Webb, a representative from Mermaids, a trans youth advocacy organization in Britain. “Extremist views have become much more normalized.”

Other countries have seen more overt attacks on transgender rights and health care. In 2020, Hungary’s Parliament passed a law banning gender identity changes on legal documents. Last year, Russia banned legal gender changes as well as gender-related medical care, with one lawmaker describing gender surgeries as the “path to the degeneration of the nation.”

In France this year, a group of conservative legislators introduced a bill to ban doctors from prescribing puberty blockers and hormones, with punishments of two years’ imprisonment and a fine of 30,000 euros, or about $32,600. And on Monday, the Vatican condemned gender transitions as threats to human dignity.

Azeen Ghorayshi covers the intersection of sex, gender and science for The Times. More about Azeen Ghorayshi

• Study Protocol
• Open access
• Published: 10 April 2024

Alerta Cannabis: A Tailored-Computer Web-Based Program for the Prevention of Cannabis Use in Adolescents: A Cluster-Randomized Controlled Trial Protocol

• Marta Lima-Serrano 1 ,
• Carmen Barrera-Villalba 2 , 1 ,
• Isotta Mac-Fadden 3 ,
• Ilse Mesters 4 &
• Hein de Vries 5  

BMC Nursing volume  23 , Article number:  239 ( 2024 ) Cite this article

33 Accesses

Metrics details

The growing use of cannabis in adolescence is a public health problem that must be addressed through prevention. In Spain, the average age of initiation of cannabis use in the adolescent population is 14.8 years. At 14 years, the lifetime prevalence of cannabis use is 11.7%, which increases to 51.,5% at the age of 18; the prevalence of cannabis use in the population aged 14 to 18 years is 28.6%, a figure that must be tried to reduce, that is why this school prevention program is proposed: Alerta Cannabis.

The Alerta Cannabis research project consists of design, implementation, and evaluation. In the first phase, a computer-tailored eHealth program (Alerta Cannabis) is developed based on the I-Change Model, an integrated model based on three main behavioral change processes: awareness, motivation, and action. This program consists of four 30-minute sessions that will provide culturally adapted and personalized advice to motivate students not to use cannabis through text feedback, animations, and gamification techniques. This phase will also include usability testing. In the implementation phase, secondary school students from Western Andalusia, Spain (Seville, Cádiz, Huelva, and Córdoba) and Eastern Andalusia (Jaén, Málaga, and Granada) will be randomized to an experimental condition (EC) or a control condition (CC) for a cluster randomized clinical trial (CRCT). Each condition will have 35 classes within 8 schools. GI will receive the online intervention Alerta Cannabis. EC and CC will have to fill out a questionnaire at baseline, six months, and twelve months of follow-up. In the last phase, the effect of Alerta Cannabis is evaluated. The primary outcomes are the lifetime prevalence of cannabis use and its use in the last 30 days and at 6 months. At 12 months of follow-up, the prevalence in the last 12 months will also be assessed. The secondary outcome is the intention to use cannabis.

The study tests the effect of the innovative program specifically aimed to reduce the use of cannabis in the adolescent population through eHealth in Spain. The findings aim to develop and implement evidence-based cannabis prevention interventions, which could support school prevention, for instance, the assistance of school nurses. If the program proves to be effective, it could be useful to prevent cannabis use on a national and international scale.

Trial registration

NCT05849636. Date of registration: March 16, 2023.

Peer Review reports

Introduction

Cannabis is the most widely consumed illegal drug in the world and with the general populations and adolescent populations in Europe, Spain, and Andalusia. According to the World Drug Report of the United Nations Office on Drugs and Crime [ 1 ], 209 million people used cannabis in the previous year. Furthermore, cannabis consumption is increasing; globally, the number of cannabis users has increased by 23% in the last decade. Cannabis use is more common among 15 to 16-year-olds (5.8%) than in the general population (4.1%). In Spain [ 2 , 3 , 4 ], the average age of initiation of cannabis use in the adolescent population is 14.8 years. At 14 years of age, the lifetime prevalence of cannabis use is 11.7%, which quintuples to 51.5% at 18 years old; the prevalence of cannabis use in the population aged 14 to 18 years is 28.6%. Among those under 18 years of age, cannabis is consolidated as the substance that generates the highest treatment admissions (95.1%).In Andalusia [ 3 , 5 ], the lifetime prevalence of cannabis use in the population aged 14 to 18 is 21.4%, and cannabis use is the leading cause of treatment admissions for substance use in the adolescent population (86%). Recent scientific literature concludes that there is insufficient evidence regarding the association between cannabis use and all-cause mortality [ 6 , 7 ]. However, some adverse health outcomes may be elevated among heavy cannabis users, such us fatal motor vehicle accidents, and possibly respiratory and brain cancers [ 6 ]. Furthermore, cannabis use disorder is a common comorbidity and risk marker for self-harm, mortality, and death by unintentional overdose and homicide among youth with mood disorders [ 8 ]. In fact, cannabis use is the drug associated with the highest number of disorders related to mental health [ 9 ].

A meta-analytic review [ 10 ] by Porath-Waller and Cols (2010) concluded that school-based programs have a positive impact on reducing adolescents‘ (aged 12–19) cannabis use compared to control conditions. Their results also suggested that targeting high school students is more effective than targeting middle school students. In Spain, the Ministry of Health has a system of health promotion and prevention that includes school-based health education in schools [ 11 ]. This is linked to the Strategy for Health Promotion and Prevention of the National System of Health. This includes a website for healthy lifestyles, a map of resources for health and the Information System of Health Promotion and Education (SIPES), where it is possible to publish actions that are carried out by different organizations at regional and national levels. Furthermore, a portal to include Good Practices for the reduction of demands for substance use and other addictions [ 12 ], with the objective of promoting the quality of interventions in Spain, that is to identify, select, transfer, and disseminate good practices in addictions. However, a review of school programs for substance abuse prevention in Spain indicated promising results although a lack of more rigorous evaluation is detected [ 13 ]. Moreover, a recent review concludes that most of the programs include in Spanish best practices portals did not evaluate their efficacy, while there are programs that having had their results evaluated are not indexed in said portals. Although Spain goes in the right direction, an evidence-based prevention model coexists with a pseudo-preventive model. Therefore, it is necessary to continue to promote a culture of evidence-based prevention and having efficacy evaluation protocols in prevention programs [ 14 ]. This review recommends the programs due to their strong evidence the Project EX and the Unplugged program. The last is a comprehensive program for substance use prevention based on the social influence approach and showed a reduction in the prevalence of cannabis. However, the data were not disaggregated by countries (the study was carried out in Seven European countries: Austria, Belgium, Germany, Greece, Italy, Spain, and Sweden) [ 15 ]. Moreover, in northern Spain, a universal program on drug use in general [ 16 ], ‘Be yourself’, showed a positive impact on the reduction of cannabis use in middle schools (aged 12–14) exposed to the intervention. The latter is based on models of social influence and social competence.

Research indicates that cannabis prevention programs can be effective if they use social cognitive models to convince adolescents of their disadvantages, how to deal with social influences that promote their use, and to increase self-efficacy and refusal skill [ 10 , 17 , 18 , 19 ]. They also concluded that programs that incorporated elements of several prevention models were significantly more effective than those based solely on a social influence model [ 18 , 19 ]. In addition, eHealth methods are also effective for cannabis treatment and have even better results for prevention [ 17 ]. In this line and view of the results of other investigations, the cultural compatibility of the prevention interventions must also be considered [ 20 , 21 , 22 , 23 ].

Based on this scientific evidence the school-based program Alerta Cannabis will be developed. It will use as theoretical model the Integrated Change Model [ 24 ], which has also turned out to be an explanatory model for the factors associated with the use of cannabis among Andalusian adolescents [ 25 ]. This model integrates existing social cognitive models and can be used as a basis in computer-tailored information and communication technology.

The starting hypothesis is that the application of this program, Alerta Cannabis, to minors between the ages of 14 and 18 in the school context, will be effective in reducing the prevalence of cannabis use. The objective of this study is to evaluate the effect of the Alerta Cannabis program, for which we will consider, as primary outcomes, different patterns of cannabis use such as cannabis use sometimes in life, in the last 30 days and the last 12 months, and, as a secondary outcome, the intention to use cannabis.

The integrated change model

The I-Change model is a behavior change model that tries to generate motivational and behavioral change in individuals based on their intentions and abilities [ 24 ]. The I-Change model integrates various theoretical models such as the Attitude Model- Social Influence-Self efficacy (or ASE-model) [ 26 ], the Theory of Planned Behavior by Ajzen [ 27 , 28 ], Bandura’s Social Cognitive Theory [ 29 ], Transtheoretical Model of Change [ 30 ], Belief Model on Health and Goal Setting [ 31 ]. Behavior change is generated through three stages: pre-motivational, motivational, and post-motivational, with the motivational stage serving as the foundation [ 25 ]. Pre-motivational factors influence behaviors and consist of predisposing factors (behavioral, psychological, biological, social, and cultural), awareness factors (knowledge, cues to action, and risk perception), and information factors (message, channels, and source), which. Motivational factors, facilitate or condition action. They include attitude (advantages and disadvantages), social influence (social norm, social pressure, social model, support), and self-efficacy (barriers, emotions, and abilities), while post-motivational factors are related to skills (implementation plans, development skills, and actions objectives) (Fig.  1 ), which are key to convert intentions into actions [ 32 , 33 ].

I-change model (De Vries, 2017)

Computer tailoring technology

Computer-tailoring technology can be defined as the process of adjusting intervention materials to the specific characteristics of an individual through a digitized process [ 34 ]. Unlike more static online communication, these interventions provide people with only the information that is relevant to them, as it is often personalized and tailored to the demographic characteristics and specific situations of the participants. As a result, this information is more likely to be considered relevant by the individual and, consequently, to be read [ 35 ]. This methodology provides individuals with personalized feedback on risk behaviors through messages adapted to their specific needs of the user while protecting their anonymity [ 34 ].

Web-based computer-tailored interventions (WBCT) are cost-effective for a variety of health-related behaviors in the adult and adolescent populations [ 36 , 37 , 38 ]. These interventions also have the potential to reach a large proportion of the adolescent population, since in Spain 99,7% of young people are Internet users, with hardly any differences by gender and/or social status [ 39 ]. WBTCT interventions improve young people’s accessibility, as they do not have space-time constraints, they generate personalized messages based on the motivational characteristics of participants; can attract the attention of individuals, and improve the processing of transmitted information through multiple senses [ 40 , 41 ].

As a theoretical and methodological framework, the I-Change model has been applied in other drug use prevention web-based computer tailoring programs in adolescents, with promising results. For example, a randomized controlled trial to prevent alcohol consumption in adolescents, with a theoretical and methodological design similar to that proposed in this article. The intervention successfully reduced binge drinking among 15 and 16-year-olds [ 40 ]. In Spain, the cross-cultural adaptation of the intervention designed by Jander et al. has also been carried out with efficacy data for the reduction of alcohol consumption reported [ 38 , 42 ].

The study design

The objective of this article is to describe the protocol for the design, the implementation, and the evaluation of a computer-tailored web-based intervention (Alerta Cannabis) aimed to prevent cannabis use among Andalusian adolescents.

Materials and methods

This project is based on a cluster-randomized controlled trial in which the new program Alerta Cannabis is tested. This section will be divided into three phasesas described in the following figure (Fig.  2 ). It has been estimated that to carry out this project 36 months are needed.

Schedule for the design, implementation, and evaluation of the Alerta cannabis program

Intervention development

Design of the intervention.

The intervention will be based on previous studies carried out by the research team [ 40 , 42 , 43 , 44 ], specifically, it will be based on the Alerta Alcohol program [ 41 ]. The development of the content of the intervention will be also based on in-depth interviews with young people in rehabilitation treatment for cannabis use and focus groups with adolescents who are not habitual users of cannabis [ 45 ]. A review of the literature will also be carried out to determine the success factors of programs with similar characteristics in cannabis prevention. In addition to being based on scientific evidence, the content of the intervention will be culturally adapted through focus groups with students of similar ages to the target population to learn about the circumstances surrounding cannabis use and the factors associated with cannabis use in Spain (using the I-Change model as a reference). For this qualitative phase, the team follows the COREQ criteria (Consolidated Criteria for Reporting Qualitative research) [ 46 ]. Finally, once the content of the intervention is developed, a focus group will be held with experts in prevention to validate it. An advisory and research team will also be consulted in the development of an online intervention for web content development. To finish this stage, a pilot study of the web intervention will be carried out with different class groups to confirm its feasibility and acceptance by the students (feasibility test) [ 47 ].

Intervention characteristics

This program will be implemented during the academic year during school hours. It is intended for adolescents between the ages of 14 and 18. It consists of four half-hour sessions given once a week or every two weeks by the professors, except for the first, where, in addition to the professors, a member of the research team will be present face-to-face or online, to explain what the course consists of program and how to use the application. Teachers will previously receive all the information about the program through the school counselor, they will even be able to register and use the platform if they want to explore it beforehand. The program is designed to be self-administered, individualized, and personalized, and is very intuitive. The Alerta Cannabis intervention will consist of preventive messages and personalized information on the benefits of not using cannabis, based on the I-Change model. In the first intervention session, the knowledge and risk of cannabis use will be addressed (level of danger, susceptibility, and severity), as well as the pros of cannabis use. In the second session, the cons of cannabis use (emphasizing the negative aspects of its consumption to foster an attitude of rejection of it) and the social model will be worked on (helping adolescents to choose the models they consider most appropriate and encouraging them to seek the support of friends and family who do not use cannabis). In the third session, social norms (helping adolescents to deal with the perceived approval of cannabis use in their environment as well as to choose real relationships that can help them avoid their use) and social pressure (avoiding the influence of people who consume cannabis in their environment) will be worked on. The fourth session is a reinforcement session in which all the aforementioned concepts are worked on and, in addition, the challenge of not consuming cannabis will be proposed to the participants. To evaluate the challenge, the participants who accept it will receive an e-mail asking them to answer whether or not they have been able to overcome the challenge. In all sessions, skills (self-efficacy and action plans) will also be worked on to reject cannabis.

Before starting the first session of the intervention, participants will have to complete an initial questionnaire (pre-test) and two follow-up questionnaires (post-test at six months and twelve months).

Implementation phase

Study design.

A two-arm cluster-randomized controlled trial (CRCT) will be designed, with an experimental condition (EC) and a control condition (CC) condition will be randomized at the school level. An initial assessment (pretest) and two assessments (post-test) will be performed at six and twelve months. The allocation ratio will be 1:1 using an online randomization system [ 48 ] (Fig.  3 ). Randomization will be performed by a member of the research team. Randomization will be carried out in batches, since after previous studies we have verified that not all schools confirm their participation in the program within the stipulated period, delaying the start of the rest of the schools in the program. Two school recruitment periods will be stipulated to reach the desired sample size within the same academic year. Participants will be blinded, only knowing that they will be participating in a cannabis prevention project.

The flow diagram of the intervention describes the steps followed to carry out the intervention, as well as the two study conditions. Sessions for each condition will be also described. The sessions are held at the school and a teacher is present

Participants

The target population will be students between the ages of 14 and 18 enrolled in the third and fourth years of Compulsory Secondary Education (CSE), the first year of high school or intermediate training cycles of publicly affiliated Secondary Education Institutes (SEI) in Andalusia, equivalent to grades 9, 10, 11 and 12, respectively, in the United States. The inclusion criteria in the study for schools are: 1) Secondary School in Andalusia; 2) having access to the Internet; and 3) allowing the use of computers, mobile phones, or tablets to carry out the activity. The exclusion criteria for the students are: 1) having previously participated in a specific program for the prevention of cannabis use 2), having difficulties in the language of the program (Spanish) 3), not wanting to participate or not having parental consent to participate.

Sample size

The GRANMO online calculator [ 49 ] was used to determine the sample size. It is estimated that after the intervention, the prevalence of cannabis use in the last 30 days will be reduced by 10% [ 42 ]. It is estimated that 875 subjects are needed in EC and 875 in CC to find a statistically significant difference between the two proportions of cannabis use. We assumed an intracluster correlation of ρ = 0.2, a minimum of 25 patients for each practice, and a worst-case control rate of 50%. Under these assumptions, we anticipated a power of 87% to detect a difference of 15% in rates between the two groups with α = 0.05 with 60 practices for each intervention group for monitoring accumulating data to protect patients in the trial and future patients.

Selection and collection of samples

Contact will be made with all Andalusia schools that have students between the aged of 14 and 18 in their classrooms. According to the data provided by the Education Webpage of the Junta de Andalucía [ 50 ] (using the filters secondary education, intermediate vocational training, basic vocational education, and baccalaureate) 119 provincial capital schools can be approached. A member of the investigative team will call all schools. All information provided by telephone will also be mailed to schools interested in participating (program manual, manual summary, application management document, resolution of the Ethics Committee, active consent for parent’s form). This parent-consent form must be signed by parents through iPasen [ 51 ], which is the mobile application of the Department of Education and Sports of the Junta de Andalucía that allows communication between different members of the educational community (legal guardians, students, management positions and teachers). Some school nurses also assisted in recruiting schools, during the second batch of recruitment.

Weekly, members of the team will call the counselors of these centers to obtain their definitive participation. The randomization process will be carried out using the Research Randomizer computer software (Version 4.0) [ 48 ]. Over the phone, agreements will be made on the dates for the sessions. During the first session, a member of the research team will be present face-to-face or online, so that the teacher who will be present with the students in the next session knows how the platform works (although previously the teacher has been able to use the platform to find out how does it work).

Experimental condition (Alerta Cannabis Program)

Participants will complete the Alerta Cannabis intervention (described in Sect.Intervention characteristics).

Control condition

Participants in the control condition only will complete one initial questionnaire (pre-test) and two follow-ups (post-test) at six and twelve months.

Measurements

Sociodemographic variables.

They will include gender (female/male), age (in years), parental educational level (none, primary, secondary, university, not knowing), student’s academic year, religion (Catholic, Protestant/Evangelical, Muslim/Islamic, other religion, and no religion) and nationality (Spanish, other). To assess socioeconomic status, the Family Affluence Scale [ 52 ] will be used, which consists of six different questions (Does your family own a car, van, or truck? Do you have a bedroom? How many times did your family travel outside of Spain last year on vacation? How many computers (including laptops and tablets, excluding game consoles and smartphones) does your family have? Does your family have a dishwasher at home? How many bathrooms (rooms with a bath/shower or both) are in your house [ 53 , 54 , 55 , 56 ]. The family Apgar test will be chosen to measure the self-perception of the family’s functional status. It will consist of five questions answered using a three-point Likert-type scale, assessing adaptability or mobilization of resources (Are you satisfied with the help you receive from your family when you have problems? ), participation or cooperation (Do you talk at home about the problems?, What do you have? ), development or growth (Are important family decisions discussed together at home? ), resolve or ability to spend time with a family member (Are you satisfied with the time you spend with your family?) [ 41 ].

Primary and secondary results: cannabis use and intention to cannabis use

We will measure the frequency and intention of cannabis use. The frequency of cannabis use will be measured with the questions used by the ESTUDES survey [ 57 ], which include the days the adolescent has consumed cannabis (hashish/marijuana) in their life, in the last 12 months, and in the last 30 days. In addition, the number of joint consumptions per day will be measured in the last 30 days. We will ask two questions to measure cannabis use intention: Do you intend to use cannabis in the future? Do you intend to use cannabis next year?

Motivation factors

To study the motivational factors associated with cannabis use, we based ourselves on previous studies by the team [ 25 ].

The advantages and disadvantages of cannabis use will be explored through nine items scored on a five-point Likert scale (1 = strongly agree, 5 = strongly disagree). For example, marijuana use produces family problems (advantage), or cannabis use relaxes me (disadvantage).

Regarding social influences, social modeling will be assessed by asking participants how often people in their environment (i.e., parents, brothers/sisters, friends) use cannabis (1 = never; 5 = always). The social norm will be assessed by asking participants what people around them (that is, parents, brothers/sisters, friends) think about whether the adolescent should use cannabis (1 = definitively should not use cannabis; 5 = definitively should use cannabis). Social pressure will be assessed by asking participants if they have felt pressured to use cannabis by people around them (that is, parents, brothers/sisters, friends) about whether or not they should use cannabis (1 = never; 5 = always). For example, I have felt pressured to use cannabis for my sister.

Self-efficacy will be measured with ten items. Each item assesses whether participants feel confident about not using cannabis in a certain difficult situation (situations that would normally trigger cannabis use, for example, “How difficult or easy is it for you not to use cannabis, if you are at a party and your friend offers you a joint”?). We use a five-point scale (1 = very difficult; 5 = very easy).

Ethics procedure and approval

The voluntary nature and confidentiality of the data provided by the participants are guaranteed, based on Royal Decree-Law 5/2018, of 27 July on the Protection of Personal Data and the European Data Protection Regulation [ 58 ]. Informed consent will be requested both from parents and from the adolescent to participate in the project. This study has been designed in accordance with the Declaration of Helsinki and has the approval of the Andalusian Bioethics Committee (Code 2162- N -20) and the approval of the data management protocol for Alerta Cannabis by the University of Seville.

Evaluation phase

Effectiveness and process evaluation.

General descriptive statistics will be used to describe the baseline characteristics of the participants. Since the students will be nested within a class in the study and classes will be nested within schools, to examine the predictors of dropout versus non-dropout, a multilevel logistic regression analysis will be conducted. In addition, a multilevel approach will be used to assess the effects of the intervention on the behavior of cannabis use. The first level will be repeated measures within the participants (baseline and two follow-up measurements), the second level will be the student, the third level is the class, and the fourth level is the school.

Baseline cannabis will use behavior and the demographic variables described above will be included as covariates. To select significant predictors and interactions, a backward deletion procedure (a = 0.05) will be used, with the restriction that predictors will not be removed from the model if they were involved as terms.

To study the predictors of adherence, we will also analyze the associations between the potential characteristics (i.e., gender, age, academic course, religion, nationality, family wealth score, Apgar score, and cannabis use at baseline) on the one hand, and participation in the intervention (i.e., adherent or not) through the number of sessions attended by participants at schools on the other.

Finally, for the process evaluation, a descriptive analysis will be performed using chi-square tests to examine differences between males and females and between cannabis users and non-users. We use SPSS Statistics for Windows, version 26.0 (IBM Corp.), for these analyses.

This study is the first to be conducted to design and evaluate an online cannabis use prevention program exclusively in Spain. Cannabis use in adolescents is a public health problem [ 1 ] that needs to be addressed through school-based prevention. Several factors are related to its use; a comprehensive socioecological model is needed to understand the various determinants and how best to target preventive activities for adolescents. In the current project, the I-Change Model [ 24 ] will be therefore used to develop an interactive and personalized eHealth program for the prevention of cannabis use: Alerta Cannabis, which used principles from earlier similar models targeting smoking prevention [ 42 ] and alcohol prevention [ 41 , 44 ]. To optimize use and implementation, the program will be developed using principles of co-creation, including opinions of experts in prevention, experts in computer engineering, school personnel, as well as adolescents and (former) cannabis users. In Spain, there is a legislative regulation to promote drug prevention in the classroom [ 59 ]. Law 4/1997 on Prevention and Assistance in the field of drugs gives special relevance to prevention and frames it within a broad and intersectoral context, including both problem and the causes that determine it. Therefore, schools are obliged to offer these types of activities, which require the collaboration of their teaching staff, implying an extra effort on their part. To help in these training activities, in Andalusia, there are school nurses who perform tasks focused on caring for the health of students and the rest of the school community. To this end, they carry out training activities in the field of health, both for students and for parents, teachers, and other school workers.

A possible limitation of this study could be related to the exclusion criteria related to the prior participation in a specific program aimed at preventing cannabis use, which was assessed among the participant schools during the selection process. However, this criterion does not account for the potential influence of other health promotion or prevention programs within the school environment. As stated in the introduction, In Spain, the school prevention system encompasses various programs, that although not directly linked to cannabis prevention, have demonstrated evidence of impacting cannabis use. Therefore, it is challenging to control for their influence. Furthermore, comparing selected schools based on the number, type, and extent of their prevention programs poses a challenge due to the high variability between regions and within schools. In addition, although there are other possible factors that could influence cannabis use, such as the use of other substances, mental health issues, or other life stressful events, we made the decision to focus solely on general sociodemographic factors to avoid overwhelming adolescents during the completion of the questionnaire. However, we recognize that these factors could act as confounders, and their consideration would be valuable in understanding and explaining why some adolescents may respond more positively to the tested intervention.

In conclusion, it is imperative to continue promoting a culture of evidence-based prevention and to develop efficacy evaluation protocols for prevention programs. By addressing these challenges and conducting further research, we can advance our understanding of effective strategies for substance abuse prevention in school settings. The findings will contribute to the development of future interventions to prevent cannabis use in adolescents. Providing an analysis of the effect and process of a specific program to prevent cannabis use, since the prevention programs of the service portfolio of the Andalusian health system to date have not been evaluated in terms of effect. This program could be a helpful tool for school nurses [ 60 ] in charge of implementing prevention programs in the Andalusian context. If the program proves to be effective, the ultimate goal would be national and eventually international implementation.

Data availability

This paper is a study protocol so there are not direct data generated. Nonetheless, information on project development can be addressed through correspondence author ([email protected]).

Abbreviations

Experimental condition

Cluster randomized clinical trial

Web-based computer-tailored interventions

Compulsory Secondary Education

Secondary Education Institutes

United Nations Office on Drugs and Crime (UNODC). Booklet 2 - Global overview of drug demand and drug supply. United Nations: Office on Drugs and Crime. [cited 2023 Mar 30]. Available from: https://www.unodc.org/unodc/en/data-and-analysis/wdr-2022_booklet-2.html .

European Monitoring Center for Drugs and Drug Addiction (EMCDDA). European report on Drugs: Trends and developments 2022. European Monitoring Centre for Drugs and Drug Addiction. [cited 2023 Mar 30]. Available from: https://www.emcdda.europa.eu/system/files/publications/14644/20222419_TDAT22001ESN_PDF.pdf .

Spanish Observatory of Drugs and Addictions. Report 2021. Alcohol, tobacco, and illegal drugs in Spain. [cited 2023 Mar 30]. Available from: https://pnsd.sanidad.gob.es/profesionales/sistemasInformacion/sistemaInformacion/pdf/ESTUDES_2021_Informe_de_Resultados.pdf .

Spanish Observatory of Drugs and Addictions. Report 2022. Alcohol, tobacco, and illegal drugs in Spain. [cited 2023 Mar 30]. Available from: https://pnsd.sanidad.gob.es/profesionales/sistemasInformacion/sistemaInformacion/pdf/2022_Informe_Indi_admisiones.pdf .

Social Services Agency and Dependency of the Junta de Andalucia. Annual report of the Treatment Admissions Indicator 2021. [cited 2023 Mar 30]. Available from: e https://www.juntadeandalucia.es/sites/default/files/2022-05/280222-Informe_tratamiento_2021%20%281%29.pdf .

Calabria B, Degenhardt L, Hall W, Lynskey M. Does cannabis use increase the risk of death? Systematic review of epidemiological evidence on adverse effects of cannabis use. Drug Alcohol Rev. 2010;29(3):318–30.

Article   PubMed   Google Scholar  

Borges G, Bagge CL, Orozco R. A literature review and meta-analyses of cannabis use and suicidality. J Affect Disord. 2016;195:63–74.

Fontanella CA, Steelesmith DL, Brock G, Bridge JA, Campo JV, Fristad MA. Association of Cannabis Use with Self-harm and mortality risk among youths with Mood disorders. JAMA Pediatr 1 de Abril De. 2021;175(4):377–84.

Article   Google Scholar  

United Nations Office on Drugs and Crime (UNODC). Booklet 1 - Executive summary / Policy implications [Internet]. United Nations: Office on Drugs and Crime. [cited 2023 Mar 30]. Available from: https://www.unodc.org/unodc/en/data-and-analysis/wdr-2022_booklet-1.html .

Porath-Waller AJ, Beasley E, Beirness DJ. A meta-analytic review of school-based prevention for cannabis use. Health Educ Behav. 2010;37(5):709–23.

(Ministry of Health., (March. 2024). Health Promotion and Prevention. https://www.sanidad.gob.es/areas/promocionPrevencion/home.htm

Good Practices Portal. In Reducing the Demand for ugs and Others Addictions. (March, 2024). http://www.buenaspracticasadicciones.es/ .

Espada JP, Gonzálvez MT, Orgilés M, Lloret D, Guillén-Riquelme A. Meta-analysis of the effectiveness of school substance abuse prevention programs in Spain. Psicothema. 2015;27(1):5–12.

PubMed   Google Scholar  

Medina-Martínez J, Villanueva-Blasco VJ. Prevention versus pseudoprevention: a systematic review of drug prevention in schools and its indexation in best practices portals. Int J Ment Health Addict. 2023. https://doi.org/10.1007/s11469-023-01122-x .

Kreeft PVD, Wiborg G, Galanti RM, Siliquini R, Bohrn K, Catigna M, Lindahl AM, Melero JC, Vassara M, Faggiano F, The Eu-Dap Study Group. Unplugged’: a new European school programme against substance abuse. Drugs: Educ Prev Policy. 2009;16(2):167–81. https://doi.org/10.1080/09687630701731189 .

Villanueva VJ, Puig-Perez S, Becoña E. Efficacy of the Sé tú Mismo (be yourself) program in Prevention of Cannabis Use in adolescents. Int J Ment Health Addict. 2021;19(4):1214–26.

Boumparis N, Loheide-Niesmann L, Blankers M, Ebert DD, Korf D, Schaub MP, et al. Short- and long-term effects of digital prevention and treatment interventions for cannabis use reduction: a systematic review and meta-analysis. Drug Alcohol Depend. 2019;200:82–94.

Lize SE, Iachini AL, Tang W, Tucker J, Seay KD, Clone S, et al. A Meta-analysis of the effectiveness of Interactive Middle School Cannabis Prevention Programs. Prev Sci. 2017;18(1):50–60.

Article   PubMed   PubMed Central   Google Scholar  

Norberg MM, Kezelman S, Lim-Howe N. Primary prevention of cannabis use: a systematic review of randomized controlled trials. PLoS ONE. 2013;8(1):e53187.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Marsiglia FF, Booth JM. Cultural Adaptation of interventions in Real Practice settings. Res Soc Work Pract. 2015;25(4):423–32.

Sidani S, Ibrahim S, Lok J, Fan L, Fox M, Guruge S. An Integrated Strategy for the Cultural Adaptation of evidence-based interventions. Health. 2017;9(4):738–55.

Burlew AK, Copeland VC, Ahuama-Jonas C, Calsyn DA. Does Cultural Adaptation have a role in substance abuse treatment? Soc Work Public Health. 2013;28(0):440–60.

Kulis SS, Marsiglia FF, Medina-Mora ME, Nuño-Gutiérrez BL, Corona MD, Ayers SL. Keepin’ it REAL-Mantente REAL in Mexico: a Cluster Randomized Controlled Trial of a culturally adapted Substance Use Prevention Curriculum for early adolescents. Prev Sci. 2021;22(5):645–57.

De Vries H. An Integrated Approach for Understanding Health Behavior; The I-Change Model as an Example. PBSIJ. March 9, 2017 [updated 2017; cited 2023 Mar 30];2(2). Available from: https://juniperpublishers.com/pbsij/PBSIJ.MS.ID.555585.php .

Torrejón-Guirado MC, Lima-Serrano M, Mercken L, de Vries H. Which factors are associated with cannabis use among adolescents in Andalusia? An application of the I-Change model. Journal of Nursing Scholarship. [citado 5 de abril de 2023];n/a(n/a). Available from: https://onlinelibrary.wiley.com/doi/abs/ https://doi.org/10.1111/jnu.12806 .

De Vries H, Mudde AN. Predicting stage transitions for smoking cessation applying the attitude-social influence-efficacy model. Psychol Health. 1998;13(2):369–85.

Azjen I. Theory of planned behavior. Organ Behav Hum Decis Process. 1991;50(2):179–211.

Ajzen I. From intentions to actions: a theory of Planned Behavior. Action Control: Cognition Behav. 1985. https://doi.org/10.1007/978-3-642-69746-3_2 .

Bandura A, Rivière-Gómez Á. Social Learning theory. Espasa Calpe Spain; 1982 [cited 2023 Mar 30]. Available from: https://dialnet.unirioja.es/servlet/libro?codigo=184893 .

Prochaska JO, Velicer WF. The Transtheoretical Model of Health Behavior Change. Am J Health Promot. 1997;12(1):38–48.

Article   CAS   PubMed   Google Scholar  

Janz NK, Becker MH. The Health Belief Model: a Decade later. Health Educ Q. 1984;11(1):1–47.

Gastelurrutia MA, Amezúa MJ, Gil M, Noain MA, Castrillón CC. The integration of different strategies to boost the adoption of the pharmacotherapy follow-up service in Spanish community pharmacies. Pharm Care Spain. 2009;1:11:52–62.

More KR, Phillips LA. The utility of the integrated behavior change model as an extension of the theory of planned behavior. Frontiers in Psychology. 2022 [updated 2022; cited 2023 April 5];13. Available from: https://www.frontiersin.org/articles/ https://doi.org/10.3389/fpsyg.2022.940777 .

De Vries H, Brug J. Computer-tailored interventions motivating people to adopt health promoting behaviors: introduction to a new approach. Patient Educ Couns. 1999;36(2):99–105.

Smit ES, Linn AJ, van Weert JCM. Taking online computer-tailoring forward: the potential of tailoring the message frame and delivery mode of online health behaviour change interventions. Eur Health Psychol. 2015;17(1):25–31.

Google Scholar  

Altendorf MB, van Weert JCM, Hoving C, Smit ES. An economic evaluation of an online computer-tailored smoking cessation intervention that includes message frame-tailoring: a randomized controlled trial. PLOS Digit Health. 2022;1(9):e0000094.

Krebs P, Prochaska JO, Rossi JS. A meta-analysis of computer-tailored interventions for health behavior change. Prev Med. 2010;51(3):214–21.

Vargas-Martínez AM, Lima-Serrano M, Trapero-Bertran M. Cost-effectiveness and cost-utility analyses of a web-based computer-tailored intervention for prevention of binge drinking among Spanish adolescents. Alcohol Clin Exp Res. 2023;47(2):319–35.

Population that uses the Internet (in the last three months). Type of activities carried out on the Internet. Statistics National Institute. [cited 2023 April 5]. Available in: https://www.ine.es/ss/Satellite?L=es_ES&c=INESeccion_C&cid=1259925528782&p=1254735110672&pagename=ProductosYServicios%2FPYSLayoutm1=PYSDetallem3=1259924822888

Jander A, Crutzen R, Mercken L, Candel M, de Vries H. Effects of a web-based computer-tailored game to reduce binge drinking among Dutch adolescents: a Cluster Randomized Controlled Trial. J Med Internet. 2016;18(2):e29.

Lima-Serrano M, Martínez-Montilla JM, Lima-Rodríguez JS, Mercken L, de Vries H. Design, implementation and evaluation of a web-based computer-tailored intervention to prevent binge drinking in adolescents: study protocol. BMC Public Health. 2018;18(1):449.

Martinez-Montilla JM, Mercken L, de Vries H, Candel M, Lima-Rodríguez JS, Lima-Serrano MA, Web-Based. Computer-tailored intervention to reduce alcohol consumption and binge drinking among Spanish adolescents: Cluster Randomized Controlled Trial. J Med Internet Res. 2020;22(1):e15438.

Cremers HP, Mercken L, Oenema A, de Vries H. A web-based computer-tailored smoking prevention programme for primary school children: intervention design and study protocol. BMC Public Health. 2012;12(1):277.

Lima-Serrano M, Fernández-León P, Mercken L, Martínez-Montilla JM, de Vries H. An animation- Versus text-based computer-tailored game intervention to prevent alcohol consumption and binge drinking in adolescents: study protocol. Int J Environ Res Public Health. 2021;18(19):9978.

González-Cano-Caballero M, Torrejón-Guirado C, Cano-Caballero MD, Mac-Fadden I, Barrera-Villalba C, Lima-Serrano M. Adolescents and youths’ opinions about the factors associated with cannabis use: a qualitative study based on the I-Change model. BMC Nurs. 2023;22(114). https://doi.org/10.1186/s12912-023-01283-z .

Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. 2007;19(6):349–57.

Dupont HB, Lemmens P, Adriana G, van de Mheen D, de Vries NK. Developing the Moti-4 intervention, assessing its feasibility and pilot testing its effectiveness. BMC Public Health. 2015;15(1):500.

Research Randomizer. [Cited 2023 Apr 10]. Available from: https://www.randomizer.org/ .

Calculator. [Cited 2023 Apr 10]. Available from: https://www.imim.cat/ofertadeserveis/software-public/granmo/ .

Ministry of Education. Culture, and Sport. Junta de Andalucía. [cited 2023 May 3]. Available from: https://www.juntadeandalucia.es/educacion/vscripts/centros/index.asp .

Ministry of Educational Development. and Vocational Training. [cited 2023 May 3]. Available from: https://www.juntadeandalucia.es/educacion/portals/web/ipasen .

Hartley JEK, Levin K, Currie C. A new version of the HBSC Family affluence scale - FAS III: Scottish qualitative findings from the international FAS development study. Child Ind Res. 2016;9:233–45. https://doi.org/10.1007/s12187-015-9325-3 .

Currie C, Molcho M, Boyce W, Holstein B, Torsheim T, Richter M. Researching health inequalities in adolescents: the development of the Health Behaviour in School-aged children (HBSC) family affluence scale. Soc Sci Med. 2008;66(6):1429–36.

Currie C, Inchley J, Molchi M, Lenzi M, Veselska Z, Wild F. Health Beha aviou rr in. School-aged children (HBSC) study protocol: background, methodology and mandatory items for the 2013/14 survey. St Andrews: Child and Adolescent Health Research Unit (CAHRU); 2014.

Inchley J, Molcho M, Lenzi M, Veselska Z, Wild F. Health Behavior Study Protocol in School-Age Children (HBSC): Background, Methodology, and Required Items for the 2013/14 Survey. Child and Adolescent Health Research Unit: St. Andrews; Available from: https://drive.google.com/file/d/1FZ8c2Xa_FcZ5Yx5gPXkPtlbV545NKhnx/view .

Moreno C, Ramos P, Rivera F et al. Technical report on the results obtained from the Health Behavior in School-aged Children Study (HBSC) 2018 in Spain. Ministry of Health, 2020.

Portal National Plan on Drugs. - Surveys and studies. [cited 2023 April 5]. Available from: https://pnsd.sanidad.gob.es/profesionales/sistemasInformacion/sistemaInformacion/encuestas_ESTUDES.htm

Head of state. Royal Decree-Law 5/2018, of July 27, on urgent measures for the adaptation of Spanish Law to the European Union regulations on data protection. Section 1, Royal Decree-Law 5/2018 Jul 30, 2018 p. 76249-57. Available from: https://www.boe.es/eli/es/rdl/2018/07/27/5 .

Autonomous Community of Andalusia. Law 4/1997, of July 9, on Drug Prevention and Assistance. Section 1, Law 4/1997 Aug 14, 1997 p. 24916-25. Available from: https://www.boe.es/eli/es-an/l/1997/07/09/4 .

Andalusian Health Service. Functions and competencies of the Reference Nurses of Educational Centers in Andalusia. Andalusian Health Service. [cited 2023 May 17]. Available from: https://www.sspa.juntadeandalucia.es/servicioandaluzdesalud/publicaciones/funciones-y-competencias-de-las-enfermeras-referentes-de-centros-educativos-erc-en-andalucia .

Download references

Grant PID2019-107229RA-I00 funded by MCIN/AEI/10.13039/501100011033; MCIN/AEI/10.13039/501100011033.

Author information

Authors and affiliations.

Instituto de Biomedicina de Sevilla, IBiS. Department of Nursing, School of Nursing, Physiotherapy and Podiatry, University of Seville, Seville, Spain

Marta Lima-Serrano & Carmen Barrera-Villalba

Department of Health Promotion, Care and Public Health Research Institute CAPHRI, Maastricht University, Maastricht, The Netherlands

Carmen Barrera-Villalba

Department of Sociology, University of Salamanca, Salamanca, Spain

Isotta Mac-Fadden

Department of Epidemiology, Care and Public Health Research Institute CAPHRI, Maastricht University, Maastricht, The Netherlands

Ilse Mesters

Hein de Vries

You can also search for this author in PubMed   Google Scholar

Contributions

Conceptualization, Lima-Serrano, M., De Vries, H., Barrera-Villalba, C.; funding acquisition, Lima-Serrano, M.; Led the write up of this manuscript, Barrera-Villalba, C. Draft and substantial revisions of the manuscript, Lima-Serrano, M., De Vries, H., Mesters, I., Mac-Fadden, I., Barrera-Villalba, C. All authors approved the submission of the final manuscript.

Corresponding author

Correspondence to Carmen Barrera-Villalba .

Ethics declarations

Ethics approval and consent to participate.

The Alerta Cannabis project has been designed in accordance with the Declaration of Helsinki and has received full approval by Andalusian Bioethics Committee, Spain, under code 2162- N -20. Regarding personal data legislation, anonymity of participants is warrantied, provided that no personal data will be used in the project development. Informed consent will be requested both from parents and from the adolescent to participate in the project.

Consent for publication

Not applicable.

Registration

ClinicalTrials.gov ID: NCT05849636. Date of registration: March 16, 2023.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Lima-Serrano, M., Barrera-Villalba, C., Mac-Fadden, I. et al. Alerta Cannabis: A Tailored-Computer Web-Based Program for the Prevention of Cannabis Use in Adolescents: A Cluster-Randomized Controlled Trial Protocol. BMC Nurs 23 , 239 (2024). https://doi.org/10.1186/s12912-024-01889-x

Download citation

Received : 10 September 2023

Accepted : 21 March 2024

Published : 10 April 2024

DOI : https://doi.org/10.1186/s12912-024-01889-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Cannabis use
• Cluster randomized controlled trial
• Adolescents
• Web-based interventions
• Computer-tailoring

BMC Nursing

ISSN: 1472-6955

• General enquiries: [email protected]

Read our research on: Gun Policy | International Conflict | Election 2024

Regions & Countries

About half of americans say public k-12 education is going in the wrong direction.

About half of U.S. adults (51%) say the country’s public K-12 education system is generally going in the wrong direction. A far smaller share (16%) say it’s going in the right direction, and about a third (32%) are not sure, according to a Pew Research Center survey conducted in November 2023.

Pew Research Center conducted this analysis to understand how Americans view the K-12 public education system. We surveyed 5,029 U.S. adults from Nov. 9 to Nov. 16, 2023.

The survey was conducted by Ipsos for Pew Research Center on the Ipsos KnowledgePanel Omnibus. The KnowledgePanel is a probability-based web panel recruited primarily through national, random sampling of residential addresses. The survey is weighted by gender, age, race, ethnicity, education, income and other categories.

Here are the questions used for this analysis , along with responses, and the survey methodology .

A majority of those who say it’s headed in the wrong direction say a major reason is that schools are not spending enough time on core academic subjects.

These findings come amid debates about what is taught in schools , as well as concerns about school budget cuts and students falling behind academically.

Related: Race and LGBTQ Issues in K-12 Schools

Republicans are more likely than Democrats to say the public K-12 education system is going in the wrong direction. About two-thirds of Republicans and Republican-leaning independents (65%) say this, compared with 40% of Democrats and Democratic leaners. In turn, 23% of Democrats and 10% of Republicans say it’s headed in the right direction.

Among Republicans, conservatives are the most likely to say public education is headed in the wrong direction: 75% say this, compared with 52% of moderate or liberal Republicans. There are no significant differences among Democrats by ideology.

Similar shares of K-12 parents and adults who don’t have a child in K-12 schools say the system is going in the wrong direction.

A separate Center survey of public K-12 teachers found that 82% think the overall state of public K-12 education has gotten worse in the past five years. And many teachers are pessimistic about the future.

Related: What’s It Like To Be A Teacher in America Today?

Why do Americans think public K-12 education is going in the wrong direction?

We asked adults who say the public education system is going in the wrong direction why that might be. About half or more say the following are major reasons:

• Schools not spending enough time on core academic subjects, like reading, math, science and social studies (69%)
• Teachers bringing their personal political and social views into the classroom (54%)
• Schools not having the funding and resources they need (52%)

About a quarter (26%) say a major reason is that parents have too much influence in decisions about what schools are teaching.

How views vary by party

Americans in each party point to different reasons why public education is headed in the wrong direction.

Republicans are more likely than Democrats to say major reasons are:

• A lack of focus on core academic subjects (79% vs. 55%)
• Teachers bringing their personal views into the classroom (76% vs. 23%)

In turn, Democrats are more likely than Republicans to point to:

• Insufficient school funding and resources (78% vs. 33%)
• Parents having too much say in what schools are teaching (46% vs. 13%)

Views also vary within each party by ideology.

Among Republicans, conservatives are particularly likely to cite a lack of focus on core academic subjects and teachers bringing their personal views into the classroom.

Among Democrats, liberals are especially likely to cite schools lacking resources and parents having too much say in the curriculum.

Note: Here are the questions used for this analysis , along with responses, and the survey methodology .

Sign up for our weekly newsletter

Fresh data delivered Saturday mornings

‘Back to school’ means anytime from late July to after Labor Day, depending on where in the U.S. you live

Among many u.s. children, reading for fun has become less common, federal data shows, most european students learn english in school, for u.s. teens today, summer means more schooling and less leisure time than in the past, about one-in-six u.s. teachers work second jobs – and not just in the summer, most popular.

About Pew Research Center Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of The Pew Charitable Trusts .