Evidence map›Paper›PMID 42458337›Full record

SynthesisBMC psychiatry2026

Comparative effectiveness and dose-response relationships of exercise for depressive symptoms in children and adolescents: a Bayesian network meta-analysis.

Zilong Zhao, Xuewen Li, Longhui Li, Yang Yi

Abstract readNetwork Meta-AnalysisComparative StudySystematic Review
In one paragraph

Synthesis in BMC psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Zilong ZhaoHebei Sport University, Shijiazhuang, China.
Xuewen LiHebei Sport University, Shijiazhuang, China.
Longhui LiCapital University of Physical Education and Sports, Beijing, 100191, China. m15235524119@163.com.
Yang YiCapital University of Physical Education and Sports, Beijing, 100191, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDepression in children and adolescents is a growing public health concern with lasting effects on mental and physical health. Exercise is a promising strategy for prevention and treatment; however, the comparative effectiveness of different exercise types and their doses response remains unclear. This study aimed to evaluate the effects of different exercise types on depressive symptoms and to explore their dose-response relationships using a network meta-analysis.

methodsSix databases (APA PsycInfo, Cochrane Library, Embase, PubMed, Scopus, and Web of Science) were systematically searched, supplemented by Google Scholar and citation tracking. Randomized controlled trials involving exercise interventions in children and adolescents were included. Risk of bias was assessed using the Revised Cochrane Risk of Bias tool. Bayesian network meta-analyses and dose-response analyses were conducted using random-effects models.

resultsA total of 41 trials with 4,563 participants were included. Mind-body exercise (MBE) was associated with the largest estimated reduction in depressive symptoms (SMD = - 1.46, 95% CrI: -2.00 to - 0.88), followed by resistance training (SMD = - 0.90, 95% CrI: -1.68 to - 0.14), aerobic exercise (AE; SMD = - 0.80, 95% CrI: -1.20 to - 0.43), interval training (SMD = - 0.60, 95% CrI: -1.43 to 0.24), and combined aerobic exercise and resistance training (AE + RT; SMD = - 0.54, 95% CrI: -1.24 to 0.13). Subgroup analyses suggested relatively larger estimated effects for AE in clinical populations and MBE in subclinical and healthy populations. Age-related differences were also observed, with AE showing relatively larger estimated effects in children and MBE in adolescents. A nonlinear U-shaped dose-response relationship was identified, with the greatest estimated effects occurring at 947 MET-min/week. Dose-response patterns varied across types, ranging from 690 MET-min/week for AE + RT to 1,130 MET-min/week for MBE.

conclusionsExercise appears to be associated with reductions in depressive symptoms in children and adolescents, although the magnitude of benefit may vary by exercise type and dose. The primary, subgroup and dose-response findings should be interpreted cautiously because of substantial between-study heterogeneity, residual uncertainty, and the overall low-to-moderate certainty of the evidence. Further high-quality studies are needed to strengthen the evidence base, confirm subgroup and dose-response findings, and assess long-term sustainability. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

DepressionExerciseExercise TherapyAdolescentBayes TheoremChildHumansRandomized Controlled Trials as TopicTreatment Effect HeterogeneityTreatment OutcomeAdolescentChildrenDepressionDose–responseNetwork meta-analysisPhysical exercise

Identifiers

PMID42458337
PMCPMC13505125

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.