Effect of exercise intervention on depression in children and adolescents: a systematic review and network meta-analysis

Objectives To evaluate the effect of different exercise interventions on depressive symptoms in children and adolescents. Methods Randomized controlled trials (RCT) published until May 2023 were screened in four databases. The Cochrane collaboration tool was used to assess the risk of bias for quality evaluation. Stata 16.0 software was used for both a pairwise meta-analysis and a series of frequentist network meta-analyses (NMA). Results A total of 35 RCTs and 5393 participants were included. Aerobic exercise had the most significant effect on depressive symptoms (66.2%), followed by group training (62.5%), resistance exercise (59.0%), and aerobic combined with resistance exercise (57.9%). Furthermore, children and adolescents younger than 15 years showed significant improvement in depressive symptoms (SMD=-0.41, 95% CI (-0.63, -0.19), P < 0.01). The study also found a significant improvement in depression among healthy, obesity, and depressed populations (SMD=-0.25, 95% CI (-0.41, -0.08), P < 0.01); SMD=-0.15, 95% CI (-0.31, -0.00), P < 0.01; SMD=-0.75, 95% CI (-1.32, -0.19), P < 0.01). Additionally, 30 min of exercise had a significant effect (SMD=-0.14, 95% CI (-0,81, -0.01), P < 0.01), and 40–50 min of exercise had the best effect (SMD=-0.17, 95% CI (-0,33, -0.02), P < 0.01). Lastly, exercise frequency of three times per week was significant in children and adolescents (SMD=-0.42, 95% CI (-0,66, -0.18), P < 0.01). Conclusion Exercise significantly improves depressive symptoms in children and adolescents, with aerobic exercise having the most significant effect. A 12-week, three-times-a-week, 40-50-minute exercise intervention was found to be more effective in younger children and adolescents. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-023-16824-z.


Rationale
Describe the rationale for the review in the context of what is already known, including mention of why a network metaanalysis has been conducted.

Objectives
Provide an explicit statement of questions being addressed, with reference to participants, interventions, comparisons, outcomes, and study design (PICOS).

Protocol and registration
Indicate whether a review protocol exists and if and where it can be accessed (e.g., Web address); and, if available, provide registration information, including registration number.Eligibility criteria Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale.Clearly describe eligible treatments included in the treatment network, and note whether any have been clustered or merged into the same node (with justification).

Information sources
Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched.

Search
Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated.

S2
Describe the statistical methods used to evaluate the agreement of direct and indirect evidence in the treatment network(s) studied.Describe efforts taken to address its presence when found.

Risk of bias across studies 15
Specify any assessment of risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting within studies).

Additional analyses 16
Describe methods of additional analyses if done, indicating which were pre-specified.This may include, but not be limited to, the following: For all outcomes considered (benefits or harms), present, for each study: 1) simple summary data for each intervention group, and 2) effect estimates and confidence intervals.
Modified approaches may be needed to deal with information from larger networks.

Synthesis of results 21
Present results of each meta-analysis done, including confidence/credible intervals.In larger networks, authors may focus on comparisons versus a particular comparator (e.g.placebo or standard care), with full findings presented in an appendix.League tables and forest plots may be considered to summarize pairwise comparisons.If additional summary measures were explored (such as treatment rankings), these should also be presented.

S5
Describe results from investigations of inconsistency.This may include such information as measures of model fit to compare consistency and inconsistency models, P values from statistical tests, or summary of inconsistency estimates from different parts of the treatment network.

Risk of bias across studies 22
Present results of any assessment of risk of bias across studies for the evidence base being studied.

Results of additional analyses 23
Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses, meta-regression analyses, alternative network geometries studied, alternative choice of prior distributions for Bayesian analyses, and so forth).

Summary of evidence 24
Summarize the main findings, including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policymakers).Network meta-analysis or mixed treatment comparison: These terms, which are often used interchangeably, refer to situations involving the simultaneous comparison of 3 or more interventions.Any network of treatments consisting of strictly unclosed loops can be thought of as a series of ITCs (Appendix Figure 1, A  and B).In mixed treatment comparisons, both direct and indirect information is available to inform the effect size estimates for at least some of the comparisons; visually, this is shown by closed loops in a network graph (Appendix Figure 1, C). Closed loops are not required to be present for every comparison under study."Network meta-analysis" is an inclusive term that incorporates the scenarios of both indirect and mixed treatment comparisons.

Network geometry evaluation:
The description of characteristics of the network of interventions, which may include use of numerical summary statistics.This does not involve quantitative synthesis to compare treatments.This evaluation describes the current evidence available for the competing interventions to identify gaps and potential bias.Network geometry is described further in Appendix Box 4. Also Study selection State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, describe the use of additional summary measures assessed, such as treatment rankings and surface under the cumulative ranking curve (SUCRA) values, as well as modified approaches used to present summary findings from meta-analyses.Planned methods of analysis 14 Describe the methods of handling data and combining results of studies for each network meta-analysis.This should include, but not be limited to:  Handling of multi-arm trials;  Selection of variance structure;  Selection of prior distributions in Bayesian analyses; and  Assessment of model fit.

Reviews With Networks of Multiple Treatments
Different terms have been used to identify systematic reviews that incorporate a network of multiple treatment comparisons.A brief overview of common terms follows.
Limitations 25Discuss limitations at study and outcome level (e.g., risk of bias), and at review level (e.g., incomplete retrieval of identified research, reporting bias).Comment on the validity of the assumptions, such as transitivity and consistency.Comment