The impact of an unsanctioned compassion club on non-fatal overdose
Bibliographic record
Abstract
OBJECTIVES: In 2022, the Drug User Liberation Front opened an unsanctioned compassion club in Vancouver where members could purchase illicit drugs that had been rigorously tested to ensure quality and a lack of potentially fatal contaminants. We sought to evaluate the impact of access to this novel safer supply intervention on non-fatal overdose. METHODS: Data were obtained from 47 club members via surveys completed at 3-month intervals between August 2022 and October 2023. We conducted multivariable generalized estimating equations (GEE) analyses to examine the association between club enrolment and the outcomes of: (1) any non-fatal overdose; and (2) any non-fatal overdose involving naloxone administration. RESULTS: The final sample, including 47 study participants, contributed a total of 225 observations and 44.4 person-years of follow-up during the study, and a median follow-up duration of 12.2 months (quartile 1 - 3: 10.4 - 14.7) per participant. In multivariable GEE analyses, enrolment in the compassion club was associated with reduced likelihood of non-fatal overdose (Adjusted Odds Ratio [AOR] = 0.51, 95% Confidence Interval (CI): 0.26 - 0.99) and non-fatal overdose involving naloxone administration (AOR = 0.37, 95% CI: 0.16 - 0.84) after adjusting for potential confounders. DISCUSSION: In this study, enrolment in an unsanctioned compassion club was found to be associated with reductions in any type of non-fatal overdose and non-fatal overdose involving naloxone administration. These findings highlight the need for ongoing research on safer supply interventions, as well as the potential of non-medicalized compassion clubs to complement existing safer supply programming and reduce overdose events.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".