Expanding harm reduction to include fentanyl urine testing: results from a pilot in rural British Columbia
Bibliographic record
Abstract
BACKGROUND: Harm reduction has been at the forefront of the response to the opioid overdose public health emergency in British Columbia (BC). The unprecedented number of opioid overdose deaths in the province calls for an expansion of harm reduction services. The purpose of this study was to determine the acceptability of a fentanyl urine drug test among people who use drugs (PWUD) and explore whether testing introduced any changes in participants' attitudes and behaviors towards their drug use. METHODS: A pilot of fentanyl urine testing was implemented in partnership with an outreach harm reduction program in rural BC. Participants were PWUD who had consumed within the last 3 days prior to the test. Participants filled out a semi-structured questionnaire at the time of the test and were invited for a follow-up interview 2 to 4 weeks after the test. Urine samples were tested with BNTX Rapid Response™ fentanyl urine strip test at a detection level of 20 ng/ml norfentanyl. RESULTS: Of the 24 participants who completed the urine test and first interview, 4 had a positive fentanyl urine test. Fifteen clients completed the second questionnaire, 10 of whom reported introducing a behavior change after testing and the remaining 5 indicated being already engaged in harm reduction practices. All four clients who tested positive completed the second questionnaire; all but one indicated adopting behaviors towards overdose prevention. DISCUSSION: Fentanyl urine testing appealed to illicit opioid users and may have contributed to adopting behaviors towards safer drug use. A relationship of trust between tester and client seemed important for clients who expressed concerns with privacy of the urine test results. Post-consumption urine testing could complement the use of pre-consumption drug checking in the context of harm reduction services.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".