No health without mental health.

In prevention science and related fields, large meta-analyses are common, and these analyses often involve dependent effect size estimates. Robust variance estimation (RVE) methods provide a way to include all dependent effect sizes in a single meta-regression model, even when the exact form of the dependence is unknown. RVE uses a working model of the dependence structure, but the two currently available working models are limited to each describing a single type of dependence. Drawing on flexible tools from multilevel and multivariate meta-analysis, this paper describes an expanded range of working models, along with accompanying estimation methods, which offer potential benefits in terms of better capturing the types of data structures that occur in practice and, under some circumstances, improving the efficiency of meta-regression estimates. We describe how the methods can be implemented using existing software (the “metafor” and “clubSandwich” packages for R), illustrate the proposed approach in a meta-analysis of randomized trials on the effects of brief alcohol interventions for adolescents and young adults, and report findings from a simulation study evaluating the performance of the new methods.

/pdf/meta-analysis-with-robust-variance-estimation-expanding-the-3c4ungxf8s.pdf

Meta-analysis with Robust Variance Estimation: Expanding the Range of Working Models

Importance Bullying is a prevalent and modifiable risk factor for mental health disorders. Although previous studies have supported the effectiveness of anti-bullying programs; their population impact and the association of specific moderators with outcomes are still unclear. Objective To assess the effectiveness of school anti-bullying interventions, their population impact, and the association between moderator variables and outcomes. Data sources A search of Ovid MEDLINE, ERIC, and PsycInfo databases was conducted using 3 sets of search terms to identify randomized clinical trials (RCTs) assessing anti-bullying interventions published from database inception through February 2020. A manual search of reference lists of articles included in previous systematic reviews and meta-analyses was also performed. Study selection The initial literature search yielded 34 798 studies. Included in the study were articles that (1) assessed bullying at school; (2) assessed the effectiveness of an anti-bullying program; (3) had an RCT design; (4) reported results; and (5) were published in English. Of 16 707 studies identified, 371 met the criteria for review of full-text articles; 77 RCTs were identified that reported data allowing calculation of effect sizes (ESs). Of these, 69 independent trials were included in the final meta-analysis database. Data extraction and synthesis Random-effects and meta-regression models were used to derive Cohen d values with pooled 95% CIs as estimates of ES and to test associations between moderator variables and ES estimates. Population impact number (PIN), defined as the number of children in the total population for whom 1 event may be prevented by an intervention, was used as an estimate of the population impact of universal interventions targeting all students, regardless of individual risk. Main outcomes and measures The main outcomes are the effectiveness (measured by ES) and the population impact (measured by the PIN) of anti-bullying interventions on the following 8 variable categories: overall bullying, bullying perpetration, bullying exposure, cyberbullying, attitudes that discourage bullying, attitudes that encourage bullying, mental health problems (eg, anxiety and depression), and school climate as well as the assessment of potential assocations between trial or intervention characteristics and outcomes. Results This study included 77 samples from 69 RCTs (111 659 participants [56 511 in the intervention group and 55 148 in the control group]). The weighted mean (range) age of participants in the intervention group was 11.1 (4-17) years and 10.8 (4-17) years in the control group. The weighted mean (range) proportion of female participants in the intervention group was 49.9% (0%-100%) and 50.5% (0%-100%) in the control group. Anti-bullying interventions were efficacious in reducing bullying (ES, -0.150; 95% CI, -0.191 to -0.109) and improving mental health problems (ES, -0.205; 95% CI, -0.277 to -0.133) at study end point, with PINs for universal interventions that target the total student population of 147 (95% CI, 113-213) and 107 (95% CI, 73-173), respectively. Duration of intervention was not statistically significantly associated with intervention effectiveness (mean [range] duration of interventions, 29.4 [1 to 144] weeks). The effectiveness of anti-bullying programs did not diminish over time during follow-up (mean [range] follow-up, 30.9 [2-104] weeks). Conclusions and relevance Despite the small ESs and some regional differences in effectiveness, the population impact of school anti-bullying interventions appeared to be substantial. Better designed trials that assess optimal intervention timing and duration are warranted.

Assessment of School Anti-Bullying Interventions: A Meta-analysis of Randomized Clinical Trials.

Introduction As adolescents transition from childhood to adulthood, they experience major physical, social and psychological changes, and are at heightened risk for developing mental health conditions and engaging in health-related risk behaviours. For adolescents living with HIV (ALHIV), these risks may be even more pronounced. Research shows that this population may face additional mental health challenges related to the biological impact of the disease and its treatment, the psychosocial burdens of living with HIV and HIV-related social and environmental stressors. Discussion Psychosocial interventions delivered to adolescents can promote positive mental health, prevent mental health problems and strengthen young people's capacity to navigate challenges and protect themselves from risk. It is likely that these interventions can also benefit at-risk populations, such as ALHIV, yet there is little research on this. There is an urgent need for more research evaluating the effects of interventions designed to improve the mental health of ALHIV. We highlight four priorities moving forward. These include: generating more evidence about preventive mental health interventions for ALHIV; including mental health outcomes in research on psychosocial interventions for ALHIV; conducting intervention research that is sensitive to differences among ALHIV populations and involving adolescents in intervention design and testing. Conclusions More robust research on promotive and preventive mental health interventions is needed for ALHIV. Programmes should be informed by adolescent priorities and preferences and responsive to the specific needs of these groups.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/jia2.25556

Preventing mental health conditions in adolescents living with HIV: an urgent need for evidence.

Integrating youth mental health into cash transfer programmes in response to the COVID-19 crisis in low-income and middle-income countries.

CONTEXT: Although adolescent mental health interventions are widely implemented, little consensus exists about elements comprising successful models. OBJECTIVE: We aimed to identify effective program components of interventions to promote mental health and prevent mental disorders and risk behaviors during adolescence and to match these components across these key health outcomes to inform future multicomponent intervention development. DATA SOURCES: A total of 14 600 records were identified, and 158 studies were included. STUDY SELECTION: Studies included universally delivered psychosocial interventions administered to adolescents ages 10 to 19. We included studies published between 2000 and 2018, using PubMed, Medline, PsycINFO, Scopus, Embase, and Applied Social Sciences Index Abstracts databases. We included randomized controlled, cluster randomized controlled, factorial, and crossover trials. Outcomes included positive mental health, depressive and anxious symptomatology, violence perpetration and bullying, and alcohol and other substance use. DATA EXTRACTION: Data were extracted by 3 researchers who identified core components and relevant outcomes. Interventions were separated by modality; data were analyzed by using a robust variance estimation meta-analysis model, and we estimated a series of single-predictor meta-regression models using random effects. RESULTS: Universally delivered interventions can improve adolescent mental health and reduce risk behavior. Of 7 components with consistent signals of effectiveness, 3 had significant effects over multiple outcomes (interpersonal skills, emotional regulation, and alcohol and drug education). LIMITATIONS: Most included studies were from high-income settings, limiting the applicability of these findings to low- and middle-income countries. Our sample included only trials. CONCLUSIONS: Three program components emerged as consistently effective across different outcomes, providing a basis for developing future multioutcome intervention programs.

https://pediatrics.aappublications.org/content/pediatrics/144/2/e20183488.full.pdf

Cristina Eriksson de Carvalho

Papers

Adolescent Mental Health Program Components and Behavior Risk Reduction: A Meta-analysis