A Preliminary Assessment of Short-Term Social and Substance Use-Related Outcomes Among Clients of Integrated Safer Opioid Supply Pilot Programs in Toronto, Canada
Bibliographic record
Abstract
Canada is experiencing an ongoing overdose crisis, driven by a toxic unregulated drug supply. Integrated safer supply pilot programs offer pharmaceutical alternatives, coupled with comprehensive support services, to individuals using unregulated drug supply who are at high risk of overdose. We collected data from December 2020 to January 2023 on clients receiving safer opioid supply from five frontline service providers in Toronto, Canada, using interviewer-administered questionnaires. We assessed the incidence rate ratio of self-reported overdose comparing pre- and post-enrolment in the programs and examined changes in the prevalence of social and substance use outcomes post-enrolment. Forty-one participants were recruited, of whom 26 were followed up for a median of eight months (interquartile range, 5.0-11.7). The incidence rate ratio of overdose comparing post-enrolment to pre-enrolment was 0.20 (95% confidence interval, 0.09-0.43). Participants reported several positive social and substance use outcomes at follow-up, including a reduction in reliance on the unregulated supply and reduced criminal activity. Future implementation of integrated safer opioid supply pilot programs with larger sample sizes and rigorous epidemiological designs could help further illustrate the potential impacts of these programs in reducing overdose rates in Canada. Supplementary Information: The online version contains supplementary material available at 10.1007/s11469-023-01219-3.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".