Cannabis Use Trajectories Among People Living With HIV in the Decade Prior to Recreational Legalization in Ontario, Canada (2008-2017)
Bibliographic record
Abstract
We aimed to describe long-term use trajectories and predictors prior to recreational cannabis legalization in people with HIV in Ontario, Canada. We analysed interview data from the prospective Ontario HIV Treatment Network Cohort Study from 2008 to 2017. We conducted Latent Class Growth Analyses to describe cannabis use trajectories and chi-square tests to identify trajectory group predictors. Most participants (N = 3,299) were male (81%), gay (57%), current/former tobacco smokers (58%), and many had significant symptoms of depression (43%). Four cannabis use trajectory groups were identified (Low/No Use (67%); Increased Use (4%); Decreased use (2%); High Use (26%)). Relative to the Low/No Use group, membership in the High Use group was associated with several predictors such as being older age, completing university, smoking tobacco, and significant depressive symptoms. Future research should explore the relationship between cannabis use and depressive symptoms, outcomes associated with trajectory groups and changes in use trajectories following recreational legalization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".