Background: It is necessary to develop effective preventive interventions before depression established to alleviate depressive symptoms or delay the onset of depression. In this study, we employed Bayesian network meta-analysis to identify the optimal psychosocial intervention approach for preventing depressive symptoms in children and adolescents.
Methods: We searched publication databases and conference abstracts, from time of their inception through April 2019 without language restriction, for randomized controlled trials that compared the efficacy of various psychosocial intervention approaches. We extracted the mean and standard deviation values between baseline and the last observation, and calculated the change score in depression. We also assessed ranking probability by surface under the cumulative ranking curve using a 95% credible interval.
Results: A total of 27 randomized controlled trials, involving 5,976 participants aged between 7 to 18 years, were included in our analyses. Analysis of various valid assessment instruments indicated that computer cognitive-behavioral therapy [standard mean difference (SMD = -1.82)], cognitive-behavioral therapy (SMD = -1.54) and interpersonal psychotherapy (SMD = -1.29) were statistically superior to wait-list group. Among the approaches, computer cognitive-behavioral therapy had the highest probability of being the best intervention, based on improvement from baseline to the end of the intervention (SUCRA = 90.47%, CrI: 0.55, 1.00).
Limitations: The results herein may not apply to other cultures and ethnic minorities because about half of the studies included in our analysis were conducted in the United States.
Conclusions: Computer cognitive-behavioral therapy was the most recommended intervention to accompany the depression among children and adolescents according to our Bayesian network meta-analysis results.
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