Impact of safe consumption facilities on individual and community outcomes: A scoping review of the past decade of research
Bibliographic record
Abstract
Globally, the rate of injection drug use has increased, leading to a rise in injection-related injuries, infections, disease transmission, and death. Safe consumption facilities (SCFs) were developed with the aim of reducing injection-related disease transmission and death. There is a rapidly growing body of literature related the individual and community level outcomes associated with SCFs that warrants a comprehensive review. Thus, this scoping review examined the impact and effectiveness of SCFs related to: 1) individual outcomes for people who inject drugs; 2) community outcomes associated with SCFs; and 3) the cost-effectiveness of SCFs. The search strategy, developed by the lead author and a social work librarian, followed the PRISMA scoping review extension guidelines. We searched eight databases for peer-reviewed qualitative and quantitative articles published in English over the past decade, returning a total of 1,255 articles. After screening, we extracted data from 24 articles. Findings indicate that SCFs were associated with reducing drug use related infection and disease transmission, enhancing access to addiction and other health services, reducing the risk of non-fatal overdoses, and were not associated with a significant increase in drug use, an increased rate of drug-related crime. Both qualitative and quantitative research support SCFs as a cost-effective approach to harm reduction for people who inject drugs with positive community outcomes as well. This review discusses the current state of the evidence and provides recommendations for future research directions.
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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 | 0.026 | 0.102 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.021 | 0.026 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".