Is higher physical activity behaviour associated with less subsequent use of any psychotropic medication: Results of a random-effects meta-analysis of prospective cohort studies
Bibliographic record
Abstract
Physical activity is associated with lower risk of incident depression and anxiety disorders. However, there is no meta-analytic evidence on the associations between physical activity levels and the incident use of psychotropic medications. PubMed, Embase, Scopus, Web of Science, PsycINFO, and Cochrane were searched up until March 2024 to identify prospective cohort studies in the general population without age restrictions, with any sample size, and with at least one year of follow-up. Risk of bias was assessed using the Newcastle-Ottawa Scale and a random-effects meta-analysis of adjusted relative risks was performed. Three studies comprising 40,111 participants and 322,521 person-years were included (mean age 53.8, range 18–90 years; 54% women). Relative to people reporting no physical activity, those accumulating any volume of physical activity had 15.0% (95% CI: 0.76, 0.96) lower risk of any subsequent medication use. Heterogeneity was moderate and not significant ( I 2 = 33.6%). The current meta-analysis demonstrated that people with higher physical activity levels are at lower risk of subsequent use of psychotropic medication. However, the evidence is based on a small number of studies (n = 3), highlighting the need for high-quality longitudinal studies. • Physical activity lowers the risk of future psychotropic medication use by 15%. • Results support preventive effects of physical activity on anxiety and depression.
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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 | 0.030 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.086 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".