Evidence map›Paper›PMID 41583780›Full record

ArticleFrontiers in psychology2025

Green exercise, nature connectedness, and academic burnout: a psychological study based on Chinese university students.

Tong Liu, Bo Peng, Weisong Chen, Yawei Ren, Hang Hu

Abstract read
In one paragraph

Article in Frontiers in psychology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  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

5 authors.

Tong LiuSchool of Sports Training, Chengdu Sport University, Chengdu, Sichuan, China.
Bo PengSchool of Sports Training, Chengdu Sport University, Chengdu, Sichuan, China.
Weisong ChenSchool of Sports Training, Chengdu Sport University, Chengdu, Sichuan, China.
Yawei RenSchool of Sports Training, Chengdu Sport University, Chengdu, Sichuan, China.
Hang HuSchool of Sports Training, Chengdu Sport University, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study investigated the associations between green exercise, nature connectedness, and academic burnout among university students, with a focus on whether nature connectedness mediates the relationship between green exercise and burnout. Methods: A cross-sectional survey was conducted with Chinese university students. Green exercise, nature connectedness, and three dimensions of academic burnout-emotional exhaustion (EE), cynicism (CY), and reduced personal accomplishment (RPA)-were assessed using validated self-report measures. Data were analyzed with confirmatory factor analysis (CFA), correlation analysis, and structural equation modeling (SEM). Mediation effects were tested using bias-corrected bootstrapping with 5,000 resamples. Results: Green exercise was positively correlated with nature connectedness ( Conclusion: The findings indicate that green exercise is a robust protective factor against academic burnout, operating both directly and indirectly through enhanced nature connectedness. Framed within Conservation of Resources theory and stress coping perspectives, these results suggest that outdoor physical activity and a strong sense of connection to nature function as interrelated resources that reduce strain, support resilience, and promote student well-being in higher education contexts.

Indexed as

academic burnoutgreen exercisemediationnature connectednessstructural equation modelinguniversity students

Identifiers

PMID41583780
PMCPMC12823991

What OpenQuestion holds

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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.