Preferred stimulant safer supply and associations with methamphetamine preference among people who use stimulants in British Columbia: Findings from a 2021 cross-sectional survey
Bibliographic record
Abstract
BACKGROUND: As safer supply programs expand in Canada, stimulant safer supply is often overlooked despite the harms and criminalization faced by people who use stimulants. METHODS: The 2021 Harm Reduction Client Survey was administered at 17 harm reduction sites around British Columbia, Canada. The survey included a question about what specific substance participants would want to receive as stimulant safer supply. We investigated preference of stimulant safer substance by looking at frequency of stated preference and by using multivariable logistic regression to understand factors associated with the most frequently chosen substance. RESULTS: Of 330 participants who reported a stimulant safer supply preference, 58.5% (n = 193) chose crystal methamphetamine, 13% (n = 43) crack cocaine and 12.4% (n = 41) cocaine powder. The options that were available by prescription at the time of data collection were chosen by under 11% of participants (dextroamphetamine n = 21, methylphenidate n = 15). A preference for crystal methamphetamine was associated with being 29 and under compared to 50 and over (AOR: 3.96, 95% CI: 1.42-11.07, p-value: 0.01); self-identifying as a cis man versus a cis woman (AOR: 1.75, 95% CI: 1.03-2.97, p-value: 0.04); and using drugs every day (AOR: 15.43, 95% CI: 3.38-70.51, p-value: < 0.01) or a few times a week (AOR: 8.90, 95% CI: 1.78-44.44, p-value: 0.01) compared to a few times a month. CONCLUSIONS: Preference of stimulant safer supply is associated with age, gender, and substance use characteristics. Safer supply programs that offer limited substances risk being poorly accessed, resulting in a continued reliance on an unregulated supply. Moreover, programs that do not offer a range of substances can contribute to health inequities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".