Playing for more than winning: Exploring sports participation, physical activity, and belongingness and their relationship with patterns of adolescent substance use and mental health
Bibliographic record
Abstract
BACKGROUND: Promoting adolescent sports participation and physical activity may be effective low-barrier prevention strategies for co-occurring adolescent substance use (SU) and mental health symptoms (MH). The objectives of this study were to: 1) explore associations between profiles of SU/MH and sports participation; and 2) determine whether physical activity and belongingness account for these associations. METHODS: Data came from a representative sample of 11,994 grade 9-12 Ontarian students (ages ~14-18) previously grouped into five SU/MH profiles based on patterns of use and symptoms. A series of multinomial logistic regressions, adjusted for socio-demographics and school clustering, were used to predict the risks of students belonging to SU/MH profiles based on: 1) school sports participation (>=weekly), 2) sports and physical activity (>=60minutes; 0-7 days), and 3) sports, physical activity, and school belongingness. RESULTS: Greater school sports participation, physical activity, and belongingness were each associated with reduced risks of belonging to most profiles with elevations in SU and/or MH symptoms relative to the low SU/MH profile (Relative Risk Ratios: sports=0.62-0.87, physical activity=0.78-0.98, belonging=0.75-0.83). Frequency of physical activity accounted for ~32-60% of the associations between sports and SU/MH profiles, while school belongingness accounted for the remaining associations. Physical activity and belongingness remained independently associated with SU/MH profiles. CONCLUSIONS: Findings suggest possible indirect associations between school sports participation and SU/MH profiles through physical activity and school belongingness, which may be promising prevention targets that have independent associations over and above sports. School sports participation may be one of a number of ways to achieve these goals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".