Exploring the cross-sectional association between the strength of school vaping policies and student vaping behaviours using data from the 2021–2022 COMPASS Study
Bibliographic record
Abstract
OBJECTIVES: Youth vaping is a concern in Canada. While school-level policies influence student behaviours, few studies have investigated the association between school vaping policies and student vaping. This study reviewed and scored the comprehensiveness of school vaping policies and investigated the association between school vaping policy scores and student vaping. METHODS: Online policy documents from n = 39 schools in Ontario, Alberta, and British Columbia, Canada, participating in the 2021-2022 wave of the COMPASS study were collected, reviewed, and scored for comprehensiveness (/39) using the School Tobacco Policy Index (STPI) rating form. The mean and range of scores for each domain of the STPI were calculated. School policy scores were linked to student vaping data from the COMPASS study. Multilevel logistic regression analyses identified the association between school vaping policy score and student lifetime and current (past 30-day) vaping. RESULTS: The mean total policy score was 10.2/39 (range 0‒24), and 28% of schools scored 0/39. The majority of school policies did not identify enforcement approaches or available preventive or cessation resources. Increasing STPI score was not associated with the odds of student lifetime or current vaping in multilevel logistic regression analyses. CONCLUSION: The STPI quickly identified components of school vaping policies that were missing. The overall score of most school vaping policies in our sample was low and most school vaping policies lacked many important components. Future studies should explore factors associated with adolescent vaping and identify effective prevention measures.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".