Risky and rushed public crack cocaine smoking: the potential for supervised inhalation facilities
Bibliographic record
Abstract
BACKGROUND: Despite the multitude of public health and community harms associated with crack cocaine use, little is known about factors associated with smoking crack in public and related risks such as rushed public crack smoking. METHODS: Data were derived from two prospective cohort studies of people who use illicit drugs in Vancouver, Canada between 2010 and 2014. Multivariable generalized estimating equations were used to identify the prevalence and correlates of public crack smoking and rushed public crack smoking. RESULTS: In total, 1085 participants who had smoked crack in the prior six months were eligible for the analysis, of which 379 (34.9 %) reported always or usually smoking crack in public in the previous six months at some point during the study period. Factors positively and independently associated with public crack smoking included public injection drug use (adjusted odds ratio [AOR]: 5.42, 95 % confidence interval [CI]: 3.76-7.82), homelessness (AOR: 3.48, 95 % CI: 2.77-4.36), at least daily crack use (AOR: 2.69, 95 % CI: 2.19-3.31), crack pipe sharing (AOR: 1.98, 95 % CI: 1.60-2.46), drug dealing (AOR: 1.59, 95 % CI: 1.30-1.94), recent incarceration (AOR: 1.47, 95 % CI: 1.09-1.98), noticing police presence when buying or using drugs (AOR: 1.30, 95 % CI: 1.06-1.60), and younger age (AOR: 1.03, 95 % CI: 1.01-1.04). Rushed public crack smoking, which was reported by 216 (28.8 %) of 751 participants who had smoked crack in public at least once during the study period, was positively and independently associated with homelessness (AOR: 2.61, 95 % CI: 1.96-3.49), at least daily crack use (AOR: 1.48, 95 % CI: 1.11-1.98), crack pipe sharing (AOR: 1.44, 95 % CI: 1.10-1.89), drug dealing (AOR: 1.39, 95 % CI: 1.04-1.86), and younger age (AOR: 1.02, 95 % CI: 1.01-1.04). CONCLUSIONS: A high prevalence of public crack smoking and rushed public crack smoking was observed in this setting. These findings point to the need for implementing and evaluating evidence-based public health interventions, such as supervised inhalation facilities, to reduce the risks and harms associated with smoking crack in public.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".