Known fentanyl use among clients of harm reduction sites in British Columbia, Canada
Bibliographic record
Abstract
BACKGROUND: North America is in the midst of an opioid overdose epidemic and it is commonly suggested that exposure to fentanyl is unknown. Using a provincial survey of harm reduction site clients, we aimed to characterize known and unknown fentanyl use and their correlates among people who use drugs in British Columbia, Canada. METHODS: We recruited 486 clients who were >18 years old and 316 agreed to provide a urine sample for substance use testing. Reported known fentanyl use was defined as a three-level categorical variable assessing recent (i.e., in the previous three days) fentanyl exposure: (i) known exposure; (ii) unknown exposure; and (iii) no exposure. We also assessed any exposure to fentanyl (Yes vs. No) confirmed by urinalysis. Survey data were summarized using descriptive statistics. Multinomial logistic regression and modified Poisson regression models were built to examine different correlates of exposure to fentanyl. RESULTS: Median age of the participants was 40 (IQR: 32-49). Out of the 303 eligible participants, 38.7% (117) reported known fentanyl use, 21.7% (66) had unknown fentanyl use, and 39.6% (120) had no recent fentanyl use. In the adjusted multinomial logistic regression model and in comparison with unknown fentanyl use, recent known fentanyl use was significantly associated with self-report of methadone use (aRRR = 3.18), heroin/morphine use (aRRR = 4.40), and crystal meth use (aRRR = 2.95). Moreover, any recent exposure to fentanyl (i.e., positive urine test for fentanyl) was significantly associated with living in urban settings (aPR = 1.49), and self-reporting recent cannabis use (aPR = 0.73), crystal meth (aPR = 1.45), and heroin/morphine use (aPR = 2.48). CONCLUSION: The landscape of illicit opioid use is changing in BC and more people are using fentanyl knowingly. The increasing prevalence of known fentanyl use is concerning and calls for further investments in public awareness and public policy efforts regarding fentanyl exposure and risks.
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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 | 0.000 |
| 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".