Evidence map›Paper›PMID 41080844›Full record

SynthesisFrontiers in public health2025

Effects of urban green exercise on mental health: a systematic review and meta-analysis.

Guidan Hu, Qingyuan Luo, Peng Zhang, Hao Zeng, Xiujie Ma

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Review
  6. Article
  7. Review
  8. 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.

Guidan HuSchool of Wushu, Chengdu Sport University, Chengdu, China.
Qingyuan LuoSchool of Wushu, Chengdu Sport University, Chengdu, China.
Peng ZhangCollege of Physical Education and Sports, Beijing Normal University, Beijing, China.
Hao ZengSchool of Wushu, Tianjin University of Sport, Tianjin, China.
Xiujie MaSchool of Wushu, Chengdu Sport University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As global urbanization accelerates, concerns regarding the mental health of urban residents have become increasingly prominent. Urban green exercise, a non-pharmacological intervention integrating exposure to nature with physical activity, has gained considerable attention due to its potential mental health benefits. However, systematic evidence synthesizing the specific effects and underlying mechanisms of urban green exercise on mental health remains limited. Following strict adherence to PRISMA guidelines, systematic searches of PubMed, MEDLINE, Embase, the Cochrane Library, and Web Of Science identified 15 RCTs involving urban green spaces, comprising 980 participants aged 18 years and older. Methodological quality was evaluated using the Cochrane RoB 2.0 tool. Meta-analysis using standardized mean difference (SMD) was conducted using Stata 17.0, while subgroup and regression analyses were performed to explore moderating factors, including intervention period, frequency, duration per session, exercise intensity (METs), and gender. A moderate and statistically significant positive impact of urban green exercise on mental health was found (SMD = -0.40; 95% CI = -0.56 to -0.25;

Indexed as

ExerciseMental HealthUrban PopulationAdultFemaleHumansMalegreen spacemental healthmeta-analysispublic healthrandomized controlled trialsystematic reviewurban green exercise

Identifiers

PMID41080844
PMCPMC12507887

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.