The Optimal Psychosocial Intervention Strategy for Preventing or Treating the Depressive Symptoms Among Children and Adolescents - A Bayesian Network Meta-Analysis

Background: The existence of depressive symptoms among children or adolescents can trigger a sequence of burden on themselves, their families and even the whole society, which cause both physical and economic impacts. Therefore, the strategy of the primary intervention of their depression is essential, and extremely urgent. So that our Network meta-analysis (NMA) is aimed at comparing them with each other for evaluating the optimal psychosocial therapy to help children and adolescents with depression or at risk to improve their mental health. Methods: Based on several biomedical databases, a system of search strategies was conducted for searching randomized controlled trials (RCTs) which published from their inception on October, 1st 2018 without language restriction. We carried out an expression analysis for comparing the efficacy of various psychosocial therapies by using Bayesian NMA. A battery of analyses and assessments, such as convential meta-analysis and risk of bias, were performed concurrently. Findings: Only 60 of RCTs which enrolled 8914 participants were eventually included in our analyses from the 19176 of initial citation screening. And in term of various valid assessment instrument, computer cognitive-behavioral therapy [standard mean difference (SMD) = -3.00, CI: -4.90, -1.20)], cognitive-behavioral therapy (SMD = -2.70, CI: -3.70, -1.70), interpersonal psychotherapy (SMD = -1.80, CI: -4.20, -0.65), education-based therapy (SMD = -1.40, CI: -2.70, -0.28) had significantly better effects than the named control group. Interpretation: All together, these results suggest that computer cognitive-behavioral therapy might be the best approach to improve the depressive state among children and adolescents. This study may provide an excellent resource for future endeavors to incorporate psychosocial interventions and may serve as a springboard for creative undertakings as yet unknown. Funding: Funding information: This work was supported by the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). Declaration of Interest: The authors have nothing to disclose. Ethical Approval: All analyses were based on previous published studies, and no ethical approval or patient consent was required.