Psychological correlates and binge drinking behaviours among Canadian youth: a cross-sectional analysis of the mental health pilot data from the COMPASS study
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to examine associations between depression, anxiety and binge drinking among a large sample of Canadian youth, while testing the moderating effect of flourishing. This research uses data from the Cannabis, Obesity, Mental health, Physical activity, Alcohol, Smoking, Sedentary Behaviour (COMPASS) study (2012-2021) with a large sample size collecting data on youth health behaviours within Canadian secondary schools. DESIGN: Cross-sectional SETTING: 14 secondary schools across Ontario and British Columbia, Canada. PARTICIPANTS: A sample of grade 9-12 students (n=6570) who participated in the Mental Health pilot of the COMPASS study PRIMARY AND SECONDARY OUTCOME MEASURES: Self-reported questionnaires assessed student binge drinking behaviours (5≥drinks), symptoms of depression (Center for Epidemiologic Studies Depression Scale (Revised)-10 scores≥10) and anxiety (Generalised Anxiety Disorder 7-item Scale scores≥10), and flourishing (Diener's Flourishing Scale: 8-40). RESULTS: In our sample of 6570 students, 37.0% of students reported binge drinking in the last year, and 41.4% and 31.7% of students report clinically-relevant symptoms of depression and anxiety, respectively. Anxiety (adjusted OR (AOR): 0.57, (99% CI 0.15 to 2.22)) and depression (AOR: 1.98, (99% CI 0.76 to 5.13)) symptoms were not found to be associated with binge drinking and we did not detect any moderating role of flourishing. Rather, factors that were associated with increased odds of binge drinking included sports team participation (AOR: 1.67, (99% CI 1.37 to 2.03)) and use of other substances (tobacco (AOR: 3.00, (99% CI 2.12 to 4.25)) and cannabis (AOR: 7.76, (99% CI 6.36 to 9.46))). Similar associations were found for frequency of binge drinking. CONCLUSIONS: Consistent with existing literature, binge drinking behaviours were problematic, as well as clinically-relevant symptoms of depression and anxiety. However, mental health problems and well-being may not be responsible for explaining patterns of binge drinking in youth. Targeted intervention efforts towards student athletes and concurrent substance users are necessary for addressing binge drinking in youth populations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".