Applying a multilevel approach to meta-analysis is a strong method for dealing with dependency of effect sizes. However, this method is relatively unknown among researchers and, to date, has not been widely used in meta-analytic research. Therefore, the purpose of this tutorial was to show how a three-level random effects model can be applied to meta-analytic models in R using the rma.mv function of the metafor package. This application is illustrated by taking the reader through a step-by-step guide to the multilevel analyses comprising the steps of (1) organizing a data file; (2) setting up the R environment; (3) calculating an overall effect; (4) examining heterogeneity of within-study variance and between-study variance; (5) performing categorical and continuous moderator analyses; and (6) examining a multiple moderator model. By example, the authors demonstrate how the multilevel approach can be applied to meta-analytically examining the association between mental health disorders of juveniles and juvenile offender recidivism. In our opinion, the rma.mv function of the metafor package provides an easy and flexible way of applying a multi-level structure to meta-analytic models in R. Further, the multilevel meta-analytic models can be easily extended so that the potential moderating influence of variables can be examined.

School absenteeism and dropout are associated with many different life-course problems. To reduce the risk for these problems it is important to gain insight into risk factors for both school absenteeism and permanent school dropout. Until now, no quantitative overview of these risk factors and their effects was available. Therefore, this study was aimed at synthesizing the available evidence on risk factors for school absenteeism and dropout. In total, 75 studies were included that reported on 781 potential risk factors for school absenteeism and 635 potential risk factors for dropout. The risk factors were classified into 44 risk domains for school absenteeism and 42 risk domains for dropout. The results of a series of three-level meta-analyses yielded a significant mean effect for 28 school absenteeism risk domains and 23 dropout risk domains. For school absenteeism, 12 risk domains were found with large effects, including having a negative attitude towards school, substance abuse, externalizing and internalizing problems of the juvenile, and a low parent-school involvement. For dropout, the risk domains having a history of grade retention, having a low IQ or experiencing learning difficulties, and a low academic achievement showed large effects. The findings of the current study contribute to the fundamental knowledge of the etiology of school absenteeism and dropout which in turn contributes to a better understanding of the problematic development of adolescents. Further, more insight into the strength of effects of risk factors on school absenteeism and dropout is important for the development and improvement of both assessment, prevention and intervention strategies.

Knowledge of risk factors and their effects is vital for successfully preventing and reducing child neglect. This study provides a meta-analytic update of research on risk factors for child neglect. A total of 315 effect sizes were extracted from 36 primary studies and classified into 24 risk domains. Effects of 15 risk domains were significant and ranged from small (r = .110) to large (r = .372) in magnitude. Most risks were found at the parental level, such as having a history of antisocial behavior/criminal offending (r = .372); having a history of mental/psychiatric problems (r = . 259); having mental/physical problems (r = .207); and experiences of abuse in own childhood (r = .182). The effect of mother-related risk factors was not significantly different from the effect of father-related risk factors. It is concluded that child neglect is determined by multiple risk domains and that especially parent-related risk factors are important in preventing and reducing child neglect. Implications of the results for clinical practice are discussed.

Multiple risk domains have been identified for life-course persistent (LCP) offending, but a quantitative review of the effect of different risk domains was not yet available. Therefore, we performed a series of multilevel meta-analyses to examine the effect of several risk domains for LCP offending relative to adolescence-limited (AL) offending. We included 55 studies reporting on 1014 effects of risk factors, and classified each factor into one of 14 risk domains. The results revealed a significant effect for 11 domains ranging from d=0.200 to d=0.758. Relatively large effects were found for the criminal history, aggressive behavior, and alcohol/drug abuse domains, whereas relatively small effects were found for the family, neurocognitive, and attitude domains. The physical health, background, and neighborhood domains yielded no effect. Moderator analyses showed that effects of sibling-related risk factors were larger than effects of mother-related risk factors, and that the effect of the relationship domain was largest during childhood. We conclude that most risk domains contribute to the development of LCP offending and that differences between AL and LCP offenders may be quantitative rather than qualitative. Implications of the present results for risk assessment and the prevention/treatment of LCP offending are discussed.

Physical activity interventions are often implemented in the adolescent mental health care practice to prevent or treat psychosocial problems. To date, no systematic review of the effect of these physical activity interventions in adolescents has been conducted. In the current study, four multilevel meta-analyses were performed to assess the overall effect of physical activity interventions on externalizing problems, internalizing problems, self-concept, and academic achievement in adolescents. In addition, possible moderating factors were examined. In total, 57 studies reporting on 216 effect sizes were included, and the results showed significant small-to-moderate effects of physical activity interventions on externalizing problems (d=0.320), internalizing problems (d=0.316), self-concept (d=0.297), and academic achievement (d=0.367). Further, moderator analyses showed that outcome, study, sample, and intervention characteristics influenced the effects of physical activity interventions on psychosocial outcomes. Implications for theory and practice concerning the use of physical activity interventions in adolescent mental health care practice are discussed.

In this meta‐analytic review, we examined the relation between natural mentoring and youth outcomes in four domains: academic and vocational functioning, social‐emotional development, physical health, and psychosocial problems. Natural mentoring relationships are thought to foster positive youth development and buffer against the risks associated with the tumultuous years of adolescence. Two separate meta‐analyses were conducted on the presence of a natural mentor and the quality of the natural mentoring relationship, including thirty studies from 1992 to present. The findings indicated that the presence of a natural mentor was significantly associated with positive youth outcomes (r = .106). A larger effect size was found for the quality of the natural mentoring relationship in terms of relatedness, social support, and autonomy support (r = .208). The largest effect sizes were found for social‐emotional development and academic and vocational functioning. Risk‐status (e.g., teenage mothers, homeless youth, youth in foster care, and youth of alcoholic parents) did not moderate the relation between presence and quality of natural mentoring relationships and youth outcomes, which may indicate that natural mentors are generally beneficial for all youth regardless of risk‐status. Implications for theory and practice concerning the quality of the natural mentoring relationship are discussed.

Rejection sensitivity is a personality disposition characterized by oversensitivity to social rejection. Using a three-level meta-analytic model, 75 studies were reviewed that examined associations between rejection sensitivity and five mental health outcomes: depression, anxiety, loneliness, borderline personality disorder, and body dysmorphic disorder. The results showed significant and moderate associations between rejection sensitivity and depression (pooled r=0.332; p<0.001), anxiety (pooled r=0.407; p<0.001), loneliness (pooled r=0.386; p<0.001), borderline personality disorder (pooled r=0.413; p<0.001), and body dysmorphic disorder (pooled r=0.428; p<0.001). The associations between rejection sensitivity and depression, anxiety, and borderline personality disorder varied by type of sample, but the associations were similar for clinical and non-clinical (i.e., community) samples. The association between rejection sensitivity and anxiety was negatively moderated by percentage of females in samples. The association between rejection sensitivity and depression was negatively moderated by length of follow-up. The longitudinal associations between rejection sensitivity and depression, anxiety, and loneliness were stable over time. Implications of the findings for both risk assessment and prevention and intervention strategies in mental health practice are discussed.

There is a lack of knowledge about specific components that make interventions effective in preventing or reducing child maltreatment. The aim of the present meta-analysis was to increase this knowledge by summarizing findings on effects of interventions for child maltreatment and by examining potential moderators of this effect, such as intervention components and study characteristics. Identifying effective components is essential for developing or improving child maltreatment interventions. A literature search yielded 121 independent studies (N = 39,044) examining the effects of interventions for preventing or reducing child maltreatment. From these studies, 352 effect sizes were extracted. The overall effect size was significant and small in magnitude for both preventive interventions (d = 0.26, p < .001) and curative interventions (d = 0.36, p < .001). Cognitive behavioral therapy, home visitation, parent training, family-based/multisystemic, substance abuse, and combined interventions were effective in preventing and/or reducing child maltreatment. For preventive interventions, larger effect sizes were found for short-term interventions (0–6 months), interventions focusing on increasing self-confidence of parents, and interventions delivered by professionals only. Further, effect sizes of preventive interventions increased as follow-up duration increased, which may indicate a sleeper effect of preventive interventions. For curative interventions, larger effect sizes were found for interventions focusing on improving parenting skills and interventions providing social and/or emotional support. Interventions can be effective in preventing or reducing child maltreatment. Theoretical and practical implications are discussed.