Factors associated with difficulty accessing crack cocaine pipes in a Canadian setting
Bibliographic record
Abstract
Background Crack cocaine pipe sharing is associated with various health-related harms, including hepatitis C transmission. Although difficulty accessing crack pipes has been found to predict pipe sharing, little is known about the factors that limit pipe access in settings where pipes are provided at no cost, albeit in limited capacity. Therefore, we investigated crack pipe access among people who use drugs in Vancouver, Canada. Methods Data was collected through two Canadian prospective cohort studies. Generalized estimating equations (GEE) with logit link for binary outcomes was used to identify factors associated with difficulty accessing crack pipes. Results Among 914 participants who reported using crack cocaine, 33% reported difficulty accessing crack pipes. In multivariate analyses, factors independently associated with difficulty accessing crack pipes included: sex work involvement (adjusted odds ratio [AOR] = 1.57; 95% confidence interval [CI]: 1.03 – 2.39), having shared a crack pipe (AOR = 1.69; 95%CI: 1.32 – 2.16), police presence where one buys/uses drugs (AOR = 1.47; 95%CI: 1.10 – 1.95), difficulty accessing services (AOR = 1.74; 95%CI: 1.31 – 2.32), and health problems associated with crack use (AOR = 1.37; 95%CI: 1.04 – 1.79). Reasons given for difficulty accessing pipes included sources being closed (48.2%) and no one around selling pipes (18.1%). Discussion A substantial proportion of people who smoke crack cocaine report difficulty accessing crack pipes in a setting where pipes are available at no cost but in limited quantity. These findings indicate the need for enhanced efforts to distribute crack pipes and address barriers to pipe access.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".