Bidirectional associations between cannabis, e-cigarette, and cigarette use among Canadian youth: findings from the COMPASS Study
Bibliographic record
Abstract
Substance use behaviours have been found to cluster in youth, and cannabis use has been previously linked to tobacco and e-cigarette use. The objective of the current study was to examine the bidirectional associations between cannabis, e-cigarette, and cigarette use among a large sample of Canadian secondary school students. A sample of students in grades 9–11 (n = 14,652) from Ontario and Alberta, Canada who participated in two waves of the COMPASS Study (Time 1 (T1): 2015–2016; Time 2 (T2): 2016–2017) was identified. Autoregressive cross-lagged models investigated the stability of product use between T1 and T2, as well as the bidirectional associations between current cannabis, e-cigarette, and cigarette use while controlling for demographic covariates. Significant autoregressive and bidirectional associations between all three substances were observed. Students who reported using cigarettes and e-cigarettes at T1 were more likely to report using cannabis at T2. Similarly, students who reported using cannabis at T1 were more likely to report using cigarettes and e-cigarettes at T2. Given the bidirectional associations identified between cannabis, e-cigarette, and cigarette use in this research, continued monitoring of evolving policies related to cannabis and e-cigarette use in Canada is needed. Additionally, school and community-based prevention efforts targeting youth should consider addressing poly-substance use.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".