Patterns of Cannabis Use among Canadian Youth over Time; Examining Changes in Mode and Frequency Using Latent Transition Analysis
Bibliographic record
Abstract
Background: Historically substance use literature has focused on smoking as the main mode of cannabis consumption, so there are knowledge gaps surrounding current understanding of edibles and vaping. These alternative modes of cannabis use are already common among Canadian youth; however, little is known about how these cannabis use patterns change over time. Methods: This study examined the mode (smoking, eating/drinking, vaping) and frequency of cannabis use among a large sample of Canadian youth who participated in 2017–2018 and 2018–2019 data collection waves of the COMPASS study. Using latent transition analysis, this sample consisting of 18,824 youth in grades 9–12 were categorized into cannabis use classes stratified by sex, and their transition between these classes over the one-year period was examined. Results: Three cannabis use classes were identified (occasional multimode, regular multimode, and smoking) alongside one nonuse class. Among youth who reported cannabis use at baseline, transitioning to a multimode group, and/or increasing frequency of multimode use was likely over the one-year period. Conclusions: These findings may highlight a key leverage point for harm-reduction strategies which aim to prevent cannabis related harms associated with high frequency 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".