Physical Activity and Mental Health: A Cross-sectional Study of Canadian Youth.
Bibliographic record
Abstract
OBJECTIVE: Our objective was to examine the associations between recreational and non-recreational physical activity with mental health outcomes among Canadian youth aged 12-17. METHODS: Cross-sectional data from the 2015/2016 Canadian Community Health Survey was used for analysis. Physical activity was classified as either recreational or non-recreational. Both types of physical activity were categorized using the Canadian Physical Activity Guidelines. Mental health outcomes included the Patient Health Questionnaire-9 (PHQ-9) scale dichotomized with 5+ and 10+ cut-offs, self-perceived mental health, and self-reported professionally diagnosed mood and anxiety disorders. Descriptive statistics (proportions with 95% confidence intervals), and multivariable logistic regression were used in the analysis. RESULTS: It was found 21.20% of youth were not participating in recreational physical activity and 40.97% were engaging in below guideline recreational physical activity. No activity, or below guideline recreational physical activity was associated with negative mental health. Non-recreational physical activity models were generally non-significant. Additionally, it was determined that associations between recreational physical activity and PHQ-9 score were only evident in males. For the no activity and below guideline activity levels the odds ratios (ORs)=2.57 and 3.19 for males and OR=0.95 and 0.96 for females, respectively. CONCLUSIONS: Recreational physical activity is associated with youth mental health (particularly in males), but non-recreational physical activity is not consistently associated. While the data are cross-sectional and cannot support causal inference, these results highlight the potential importance of accessible recreational physical activity programs. Further, these results may inform guidelines about types of youth physical activity and their apparent mental health benefits.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".