Mental health and cannabis use among Canadian youth: Integrated findings from cross-sectional and longitudinal analyses
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Using data from two methodologically independent youth research studies in Canada, the Health Behaviour in School-aged Children (HBSC) study and the Cannabis, Obesity, Mental health, Physical activity, Alcohol, Smoking, and Sedentary behaviour (COMPASS) study, the objective of this study was to compare associations between youth's mental health and cannabis use across samples. Using similar indicators in both studies, our goal was to affirm the potential for nationally representative cross-sectional analyses (HBSC) to replicate findings found in a longitudinal non-representative data source (COMPASS), enhancing opportunity for causal inferences. METHODS: Data were collected from grade 9 and 10 Canadian students participating in the 2017/18 HBSC (n=8462) and 2017/18 to 2018/19 waves of COMPASS (n=32,023). Using multivariable Poisson regression models, the strength and statistical significance of the effects of mental health indicators on cannabis use outcomes were estimated within both studies and compared for consistency. Using a 2-year linked sample of students participating in COMPASS, models examining the impact of mental health indicators on cannabis use initiation and maintenance over time were similarly fit using Poisson regression to estimate relative risk. RESULTS: Similar associations between mental health problems and cannabis use were observed in both data sources. The direction, magnitude, and precision of the estimates for restless sleep, loneliness, poor wellbeing, and cannabis use were highly comparable across both studies. Worse mental health was consistently associated with current and lifetime cannabis use among youth. DISCUSSION: Cross-sectional and longitudinal findings from two large methodologically diverse studies in Canada demonstrate a replicable association between indicators of mental health and youth cannabis use. Similarities were identified and two generalizations may be concluded: 1) potentially causal etiological relationships inferred from HBSC data were supported in longitudinal findings based on COMPASS, and 2) longitudinal COMPASS data aligns with nationally representative data from HBSC.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".