Efficacy of school-based interventions for mental health problems in children and adolescents in low and middle-income countries: A systematic review and meta-analysis

BACKGROUND: Implementation of interventions to treat child and adolescent mental health problems in schools could help fill the mental health care gap in low- and middle-income countries (LMICs). Most of the evidence available come from systematic reviews on mental health prevention and promotion, and there is less evidence on treatment strategies that can be effectively delivered in schools. The aim of this review was to identify what school-based interventions have been tested to treat children and adolescents in LMICs, and how effective they are. METHODS: We conducted a systematic review including seven electronic databases. The search was carried out in October 2022. We included randomised or non-randomised studies that evaluated school-based interventions for children or adolescents aged 6–18 years living in LMICs and who had, or were at risk of developing, one or more mental health problems. RESULTS: We found 39 studies with 43 different pairwise comparisons, treatment for attention-deficit and hyperactivity (ADHD), anxiety, depression, and posttraumatic stress disorder (PTSD), Conduct disorder (CD). Pooled SMD were statistically significant and showed that, overall, interventions were superior to comparators for PTSD (SMD = 0.61; 95% CI = 0.37–0.86), not statistically significant for anxiety (SMD = 0.11; 95% CI = −0.13 to 0.36), ADHD (SMD = 0.36; 95% CI = −0.15 to 0.87), and for depression (SMD = 0.80; 95% CI = −0.47 to 2.07). For CD the sample size was very small, so the results are imprecise. CONCLUSION: A significant effect was found if we add up all interventions compared to control, suggesting that, overall, interventions delivered in the school environment are effective in reducing mental health problems among children and adolescents. SYSTEMATIC REVIEW REGISTRATION: [https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=129376], identifier [CRD42019129376].