Children’s Physical Activity and Depression: A Meta-analysis
Bibliographic record
Abstract
CONTEXT: Research regarding the protective effects of early physical activity on depression has yielded conflicting results. OBJECTIVE: Our objective was to synthesize observational studies examining the association of physical activity in childhood and adolescence with depression. DATA SOURCES: Studies (from 2005 to 2015) were identified by using a comprehensive search strategy. STUDY SELECTION: The included studies measured physical activity in childhood or adolescence and examined its association with depression. DATA EXTRACTION: Data were extracted by 2 independent coders. Estimates were examined by using random-effects meta-analysis. RESULTS: Fifty independent samples (89 894 participants) were included, and the mean effect size was significant (r = –0.14; 95% confidence interval [CI] = –0.19 to –0.10). Moderator analyses revealed stronger effect sizes in studies with cross-sectional versus longitudinal designs (k = 36, r = –0.17; 95% CI = –0.23 to –0.10 vs k = 14, r = –0.07; 95% CI = –0.10 to –0.04); using depression self-report versus interview (k = 46, r = –0.15; 95% CI = –0.20 to –0.10 vs k = 4, r = –0.05; 95% CI = –0.09 to –0.01); using validated versus nonvalidated physical activity measures (k = 29, r = –0.18; 95% CI = –0.26 to –0.09 vs k = 21, r = –0.08; 95% CI = –0.11 to –0.05); and using measures of frequency and intensity of physical activity versus intensity alone (k = 27, r = –0.17; 95% CI = –0.25 to –0.09 vs k = 7, r = –0.05; 95% CI = –0.09 to –0.01). LIMITATIONS: Limitations included a lack of standardized measures of physical activity; use of self-report of depression in majority of studies; and a small number of longitudinal studies. CONCLUSIONS: Physical activity is associated with decreased concurrent depressive symptoms; the association with future depressive symptoms is weak.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.043 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".