Factors associated with drug use in prison: A systematic review of quantitative and qualitative evidence
Bibliographic record
Abstract
BACKGROUND: About a third of people use drugs during their incarceration, which is associated with multiple adverse health and criminal justice outcomes. Many studies have examined factors associated with in-prison drug use, but this evidence has not yet been systematically reviewed. We aimed to systematically review and synthesise the evidence on factors related to drug use in prison. METHODS: Three databases (PubMed, PsycINFO and Embase) were systematically searched as well as grey literature, for quantitative, qualitative and mixed-methods studies examining factors related to drug use inside prison. We excluded studies that did not explicitly measure in prison drug use or only measured alcohol and/or tobacco use. Study quality was assessed using the Newcastle Ottawa Scale (NOS) for quantitative studies and Critical Appraisal Skills Programme (CASP) for qualitative studies. The review was prospectively registered on PROSPERO (CRD42021295898). RESULTS: Fifty-four studies met the inclusion criteria, reporting data on 26,399 people in prison. Most studies were of low or moderate-quality, and all used self-report to assess drug use. In quantitative studies, studies found that previous criminal justice involvement, poor prison conditions, pre-prison drug use and psychiatric diagnosis were positively associated with drug use in prison. In qualitative studies, reasons for drug use were closely linked to the prison environment lacking purposeful activity and the social context of the prison whereby drug use was seen as acceptable, necessary for cohesion and pressurised. CONCLUSION: In the first systematic review of factors associated with drug use in prison, key modifiable risk factors identified from quantitative and qualitative studies were psychiatric morbidity and poor prison conditions. Non-modifiable factors included previous drug use and criminal history linked to substance use. Our findings indicate an opportunity to intervene and improve the prison environment to reduce drug use and associated adverse outcomes.
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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 | 0.041 | 0.131 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.024 | 0.020 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".