A Comprehensive School Health Approach to Student Physical Activity: A Multilevel Analysis Examining the Association between School‐Level Factors and Student Physical Activity Behaviors
Bibliographic record
Abstract
BACKGROUND: The comprehensive school health (CSH) framework has four components: social and physical environment; partnerships and services; teaching and learning; and policy. This study examines associations between CSH and student physical activity (PA). METHODS: Using 2015/2016 COMPASS study survey data of 37,397 students (grades 9-12) from 80 secondary schools in Ontario and Alberta, Canada, associations between school-level factors within CSH and student PA outcomes (weekly moderate-to-vigorous PA [MVPA] minutes and achieving the national PA recommendations of ≥60 min of MVPA daily, vigorous PA ≥3 days/week, strengthening activities ≥3 days/week) were analyzed using multilevel regression models stratified by gender and grade. RESULTS: Factors within all four CSH components were associated with student PA. Four student subgroups were more likely to achieve the recommendations if their school had youth organization partnerships (Range of AORs:1.15-1.33, p <.05) and female students were less likely if their school had low prioritization of PA (AOR = 0.77, 95% CI: [0.65-0.92]). Grade 9 students had higher MVPA when provided non-competitive PA opportunities (β = 100.4, 95%CI: [30.0-170.9]). All student subgroups had better PA outcomes when schools provided access to equipment during non-instructional time. CONCLUSION: There is opportunity to improve student PA through CSH-guided interventions, but different strategies may be more effective for each gender/grade.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".