Peer-assisted injection as a harm reduction measure in a supervised consumption service: a qualitative study of client experiences
Bibliographic record
Abstract
BACKGROUND: Peer assistance is an emerging area of study in injection drug use. When Canada's first supervised consumption site (SCS) opened in 2003 in Vancouver, Canada, clients were prohibited from injecting their peers; only recently has this practise been introduced as a harm reduction measure at these sites. In 2018, Health Canada granted federal exemption to allow peer-assisted injection at certain SCS sites, under the Controlled Drugs and Substances Act. Literature pertaining to peer-assisted injection addresses several topics: interpersonal relationships between the injection provider and recipient; the role of pragmatism; trust and expertise; and gender relations. METHODS: In this qualitative study, participants (n = 16) were recruited to be interviewed about their experiences in a peer-assisted injection program (PAIP) at one SCS regulated by Health Canada. Interview data were transcribed and thematically analyzed. Quantitative administrative data were used to provide context and to describe the study population, comprised of people in the PAIP (n = 248). RESULTS: PAIP clients made up 17.4% of all SCS clients. PAIP clients were more likely to be female and Indigenous. Injection providers expressed being moved by compassion to help others inject. While their desire to assist was pragmatic, they felt a significant burden of responsibility for the outcomes. Other prominent factors related to the injection provider-recipient relationship were social connection, trust, safety, social capital, and reciprocity. Participants also made suggestions for improving the PAIP which included adding more inhalation rooms so that if someone was unable to inject they could smoke in a safe place instead. Additionally, being required by law to divide drugs outside of the SCS, prior to preparing and using in the site, created unsafe conditions for clients. CONCLUSIONS: Regular use of the SCS, and access to its resources, enabled participants to lower their risk through smoking and to practice lower-risk injections. At the federal level, there is considerable room to advocate for allowing clients to divide drugs safely within the SCS, and to increase capacity for safer alternatives such as inhalation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".