Evidence map›Paper›PMID 39926605›Full record

ReviewJournal of exercise science and fitness2025

Use of multicomponent structured exercise to improve depression in older adults: A systematic review and meta-analysis.

Shishi Cheng, Yanping Duan, Min Yang, Xiang Wang

Abstract readReview
In one paragraph

Review in Journal of exercise science and fitness, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shishi ChengDepartment of Sport, Physical Education and Health, Hong Kong Baptist University, Kowloon, Hong Kong, China.
Yanping DuanDepartment of Sport, Physical Education and Health, Hong Kong Baptist University, Kowloon, Hong Kong, China.
Min YangDepartment of Sports Science and Physical Education, The Chinese University of Hong Kong, Sha Tin, Hong Kong, China.
Xiang WangDepartment of Sport, Physical Education and Health, Hong Kong Baptist University, Kowloon, Hong Kong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To summarize the characteristics, estimate the efficacy of multicomponent structured exercise (MSE) intervention on older adults' depression, and investigate its potential moderators. Methods: MEDLINE, PubMed, PsycINFO, SPORTDiscus, Web of Science and Embase databases were searched from January 1, 2000 to June 1, 2024. Randomized controlled trials (RCTs) that included MSE intervention with aerobic, resistance and balance components targeting older adults, and reported depression as an outcome were selected. Random-effects meta-analyses were used to calculate effect sizes from the standardized mean difference (SMD) and 95 % confidence intervals (CIs). Meta-regression was conducted to identify the potential moderators. Results: Data were extracted from 19 studies (22 comparisons) with 1763 older adults. MSE showed a significant intervention effect on buffering older adults' depression (SMD, -0.49; 95 % CI, -0.84 to -0.14) but with considerable heterogeneity (I Conclusion: MSE significantly improved older adults' depression. The findings highlighted the importance of intervention frequency and retention rate in enhancing MSE effectiveness. More high quality RCTs are required to explore and optimize the intervention strategies and dosages of MSE to extend the application in the prevention and treatment of geriatric depression.

Indexed as

Geriatric depressionMulticomponent structured exerciseOlder adults

Identifiers

PMID39926605
PMCPMC11803849

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.