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. 2025 May 19;25(1):1845.
doi: 10.1186/s12889-025-22904-z.

Effectiveness of different exercise interventions on depressive symptoms among college students: a network meta-analysis

Yang Xiao #  1   2 , Chaofan Shi #  3 , Xiaotian Zhang  1 , Haitao Liu  4   5
Affiliations

Effectiveness of different exercise interventions on depressive symptoms among college students: a network meta-analysis

Yang Xiao et al. BMC Public Health. .

Abstract

Background: Depression affects approximately 25% of college students globally. Physical exercise shows promise as a low-cost, high-adherence intervention for depression, but research comparing different exercise types is lacking. This study aims to evaluate the efficacy of various exercise interventions in alleviating depressive symptoms among college students through a network meta-analysis, to inform targeted exercise prescriptions.

Methods: We conducted a systematic search of six databases (PubMed, Web of Science, Cochrane Library, EMBASE, SCOPUS, and ScienceDirect) from their inception to July 1, 2024. Interventions were classified into six categories based on exercise type and intensity. Data extraction and systematic analysis were performed using Review Manager 5.4. A network meta-analysis was conducted using Stata 14.0, with heterogeneity assessed via node-splitting models, and results presented as standardized mean differences (SMD) and 95% confidence intervals (CI).

Results: Forty-two randomized controlled trials involving 1,169 participants were included. The network meta-analysis revealed that Special Training Unit (STU), Dynamic Resistance Movement Group (DRMG), and Aerobic Exercise Group (AEG) demonstrated high effectiveness in improving depressive symptoms. STU showed the highest probability of being the most effective intervention (65.1%), followed by DRMG (64.8%), AEG (61.3%), and Strength and Resistance Training Group (SRTG) (60.9%). High-Intensity Training Group (HITG) (26.2%) and Moderate Intensity Group (MIG) (21.7%) showed less impact on improving depressive symptoms. The limited effectiveness of HITG may relate to excessive physiological stress responses, while MIG potentially provided insufficient stimulation to trigger optimal neurobiological adaptations for mood improvement.

Conclusions: Special Training Units (STU) and Dance and Rhythmic Movement Group (DRMG) interventions demonstrate superior efficacy in reducing depressive symptoms among college students. These findings suggest that integrating rhythmic movement with psychological components may offer optimal benefits compared to intensity-focused exercise approaches, providing evidence-based guidance for mental health programs in university settings.

Keywords: College students; Depressive symptoms; Intervention effectiveness; Network meta-analysis; Physical exercise.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: Not applicable, as this study is a systematic review of published literature and does not involve human subjects or animal experiments. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Literature screening flow chart
Fig. 2
Fig. 2
Networks for multiple treatment comparisons Note: (1)Aerobic exercise group - AEG、(2)Dance and rhythmic movement group-DRMG、(3)Moderate intensity exercise group - MIG、(4)Strength and resistance training group - SRTG、(5)High intensity training group - HITG、(6)Special training unit - STU
Fig. 3
Fig. 3
Assessment of the risk of bias for included studies. +, low bias risk; -, high bias risk;? unclear bias risk
Fig. 4
Fig. 4
Distribution of studies across the bias ranking for each type of bias
Fig. 5
Fig. 5
Rank probabilities for efficacy
Fig. 6
Fig. 6
Egger method tests publication bias Note: (1)A - Aerobic exercise group - AEG、(2)B - Dance and rhythmic movement group-DRMG、(3)C - Moderate intensity exercise group - MIG、(4)D - Strength and resistance training group - SRTG、(5)E - High intensity training group - HITG、(6)F - Special training unit - STU
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