Identifying barriers and facilitators to accessing harm reduction services in prisons: A systematic narrative synthesis
Bibliographic record
Abstract
BACKGROUND: Drug use is prevalent in carceral settings globally. Although a comprehensive harm reduction package for people in prison (PIP) is recommended by international agencies, its implementation is limited. The aim of this systematic narrative synthesis was to explore barriers and facilitators to accessing harm reduction services (HRS) in prisons. METHODS: We searched MEDLINE, PsycINFO, SCOPUS, and CINAHL for English and French language articles published before June 26, 2024. Studies evaluating any HRS defined as condoms, pre-exposure prophylaxis, post-exposure prophylaxis, opioid agonist therapy, needle syringe programs, and hepatitis B vaccination in prison were included. Two independent reviewers evaluated articles selected for full text review. Disagreements were resolved by consensus. We performed a qualitative content analysis based on the Socio-Ecological Model, utilizing constant comparative methods to generate themes and subthemes. RESULTS: A total of 8,324 unique articles were identified, 400 were eligible for full text review, and 94 were included in the final analysis; 80 studies (85%) were conducted in high-income countries. Individual-level barriers included fear of repercussions due to HRS participation, interpersonal-level barriers such as negative perceptions of HRS in PIP and staff, institutional-level barriers such as limited resource allocation and public policy/societal-level barriers including rigid administrative policies. Facilitators of HRS use included education about risk prevention, positive previous experiences with HRS, and support from prison leadership. CONCLUSION: Several multi-level barriers and facilitators to accessing prison-based HRS exist. To improve HRS uptake, implementing holistic education for PIP and carceral employees, enhancing awareness of HRS through peer-led initiatives, and ensuring buy-in and support from prison leadership will be important. Furthermore, allocation of specific resources and enhanced policies that promote HRS will be beneficial.
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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 | 0.047 | 0.117 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 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".