Client experiences using a new supervised consumption service in Sudbury, Ontario: A qualitative study
Bibliographic record
Abstract
Overdoses are increasing in the province of Ontario, Canada, where northern communities such as Sudbury have witnessed disproportionately elevated rates, with opioid-related deaths double that of the provincial average. To address this issue, governments have implemented supervised consumption services (SCS) where people who use drugs (PWUD) can use their pre-obtained substances onsite under trained supervision. In September 2022, the city of Sudbury opened its first SCS, 'The Spot', but the site's sustainability is contingent on demonstrating benefit to PWUD and the neighboring community. We undertook a qualitative study exploring experiences among clients who used the consumption service inside The Spot. In December 2022, clients of The Spot were invited to participate in a brief survey which collected socio-demographic information and substance use profiles, followed by an in-person semi-structured qualitative interview. Participant survey and interview data were combined with administrative site utilization data provided by site staff of all clients who accessed the consumption service from September 2022 to August 2023 to examine overall service utilization and uptake. Qualitative data were analyzed using iterative thematic analysis techniques, and results were informed by common responses to research questions. The responses were narratively presented. Administrative site utilization data highlighted a relatively stable increase in uptake and utilization of the site since its inception. A total of 20 clients participated in the survey and semi-structured interviews. Participants described the importance of the site in preventing and responding to overdoses, providing a safe and comfortable environment to consume their drugs, and decreasing public drug use, which they suggested may potentially reduce stigmatization in the community. However, clients also suggested challenges, including issues regarding site operational policies that hindered consumption room utilization. Service suggestions made by clients to improve site utilization include the addition of inhalation services, relocating the site to a location in downtown Sudbury where PWUD commonly congregate, and extending operational hours. Positive impacts and recommendations can be drawn on and considered by other northern or rural communities interested in implementing similar 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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".