Longitudinal study examining the relationship between physical activity and psychiatric hospitalizations in canadian adolescents and young adults utilizing record linkage
Bibliographic record
Abstract
Overwhelming evidence suggests that physical activity among youth can prevent mental illness; however, few studies have explored its effects on mental healthcare utilization. This study aimed to examine the longitudinal associations between physical activity among Canadian adolescents and young adults (AYAs; 12-24 years) and incidence of psychiatric hospitalizations. Physical activity was measured in the 2001-2014 Canadian Community Health Survey (CCHS) and was linked to the Discharge Abstract Database. Negative binomial regression analyses were performed on each CCHS cycle to obtain incidence rate ratios (IRRs) for psychiatric hospitalizations by level of physical activity, which were subsequently meta-analyzed to obtain pooled estimates. In total, 96,100 participants were recruited across eleven cycles. Adolescents were more physically active (52%) compared to young adults (39%). The most common cause of hospitalization was mood or anxiety disorders (38%). Fully adjusted models found that moderately active (IRR = 1.30; 95% CI: 1.02-1.66; p = 0.01) and inactive (IRR = 1.33; 95% CI: 1.06-1.66; p = 0.01) participants had higher rates of psychiatric hospitalizations compared to active participants. Our findings suggest that lower levels of physical activity among AYAs were associated with an increased incidence of psychiatric hospitalizations, providing valuable insights for stakeholders and laying the groundwork for future research.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.015 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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".