Can We Reverse this Trend? Exploring Health and Risk Behaviours of Grade 12 Cohorts of Ontario Students from 2013–2019
Bibliographic record
Abstract
Adolescents engage in multiple health risk behaviours that put them at risk of future chronic disease. By the time students graduate from secondary school, they may be engaging in behaviours that set them on a particular health trajectory. It is important to monitor the co-occurrence of health risk behaviours of cohorts of grade 12 students over time to highlight important areas for intervention. The purpose of this study was to examine trends in health and risk behaviours over six waves among subsequent cohorts of grade twelve students from Ontario, Canada. A total of 44,740 grade 12 students participated in the COMPASS study across the six waves (2013/14 to 2018/19), and self-reported movement (physical activity, screen time, sleep), dietary (fruit and vegetables, breakfast), and substance use (smoking, vaping, binge drinking, and cannabis use) behaviours. Over 91.0% of students reported engaging in three or more health risk behaviours, with increases in the number of students reporting inadequate sleep, not eating breakfast on every school day, and vaping over time. Although modest, the wave 6 cohort reported slightly more risk behaviours compared with the wave 1 cohort, highlighting the importance of multidimensional health promotion strategies across multiple settings.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.003 | 0.001 |
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".