Evidence map›Paper›PMID 39183831›Full record

ReviewHeliyon2024

Global research trends in the effects of exercise on depression: A bibliometric study over the past two decades.

Li-Kun Ge, Zheng Huang, Gao-Xia Wei

Abstract readReview
In one paragraph

Review in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

3 authors.

Li-Kun GeCAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China.
Zheng HuangCAS Key Laboratory of Mental Health, Institute of Psychology, Beijing, China.
Gao-Xia WeiCAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: With depression's growing global prevalence and substantial impact, effective prevention and management strategies are imperative. Our study aims to perform a thorough bibliometric analysis of existing research on the impact of exercise on depression. Methods: A comprehensive analysis of Web of Science Core Collection publications from 2000 to 2020 was performed, highlighting trends, themes, and influential authors. The study focused on subject categories, source journals, countries/regions, institutions, and prolific authors. Co-citation and keyword analyses revealed key themes, hotspots and the thematic evolution. Results: The multidisciplinary nature of this research is evident across psychiatry, psychology, neuroscience, and sports science. Specific populations such as women, the elderly, and those with chronic illnesses were targeted. Mind-body exercises like yoga and tai chi gained prominence. Co-citation clusters showcased the evolution from early investigations on exercise's impact to recent dose-response and protocol studies. Conclusions: This bibliometric analysis provides insights into the dynamic field of exercise interventions for depression. It underscores the importance of individual differences, calls for guidelines considering comorbidities, and points towards future directions such as exploring mind-body exercise mechanisms and well-designed clinical trials. This study contributes to a comprehensive understanding of the research landscape and informs future endeavors aimed at refining depression treatment through exercise interventions.

Indexed as

DepressionEmotional healthExerciseKnowledge graphMind-body exercises

Identifiers

PMID39183831
PMCPMC11341242

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.