Acute effects of outdoor versus indoor exercise: a systematic review and meta-analysis
Bibliographic record
Abstract
Exercise and nature exposure are independently recognised for their positive relationship with health, but their combined effects are not fully understood. The present review summarises the evidence that compares physiological and perceptual differences of a single bout of exercise performed outdoors versus indoors. Nine databases were searched for articles published before March 2021 which utilised controlled designs to assess at least one physiological outcome during or after a single acute bout of outdoor exercise. When appropriate, quantitative analyses were completed. Quality of articles was assessed using the Cochrane Risk of Bias Assessment Tool. The findings of 38 articles (Total N = 1168) were examined. Participants were primarily healthy. Summarised outcomes included objective exercise intensity, perceived exertion, performance, neuroendocrine and metabolic responses, cardiovascular responses, thermoregulation, enjoyment, intention for future exercise, and perceptions of the environment. Outdoor environments increased enjoyment (N = 234, K = 10, g = 1.24, 95% CI = [0.59, 1.89], p < 0.001). Findings for remaining outcomes were non-significant or inconclusive and challenging to interpret due to high risk of bias. Overall, outdoor exercise appears to feel more enjoyable than indoor exercise when matched for intensity, with equivocal physiological benefit.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.021 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".