Assessing the impact of sports and recreation facility density within school neighbourhoods on Canadian adolescents’ substance use behaviours: quasi-experimental evidence from the COMPASS study, 2015–2018
Bibliographic record
Abstract
OBJECTIVES: There has been relatively little exploration to date of potential protective effects within school neighbourhoods, such as those conferred by facilities that seek to promote health with respect to substance use and related harms. This study examined how the density of sports and recreation facilities in the school neighbourhood is associated with the likelihood of binge drinking, e-cigarette use, cigarette smoking and cannabis use among Canadian secondary school students. DESIGN: Longitudinal data from the COMPASS study on Canadian youth health behaviours from 2015/2016 to 2017/2018 was linked with school neighbourhood data capturing the number of sports and recreation facilities within a 1500 m radius of schools. SETTING: Secondary schools and school neighbourhoods in Alberta, British Columbia, Ontario and Quebec who participated in the COMPASS study. PARTICIPANTS: 16 471 youth who participated in the COMPASS study over three school years (2015/2016-2017/2018). PRIMARY AND SECONDARY OUTCOME MEASURES: Binge drinking, e-cigarette use, cigarette use, cannabis use. RESULTS: Logistic regression models using generalised estimating equations identified that greater density of sports and recreation facilities within the school neighbourhood was significantly associated with lower likelihood of binge drinking and e-cigarette use but was not associated with cigarette smoking or cannabis use. CONCLUSIONS: This research can help to support evidence-informed school community-based efforts to prevent substance-related harms among youth.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".