Drug use and initiation in prison: results from a national prison survey in England and Wales
Bibliographic record
Abstract
AIMS: To investigate heroin and cocaine use in a sample of British prisoners, and to explore the characteristics of inmates who use these drugs for the first time while in prison. DESIGN, PARTICIPANTS: A cross-sectional survey of all prisons in England and Wales conducted as part of a major national study of psychiatric morbidity. A total of 3142 prisoners (88.2% of those selected) completed a structured interviewer-administered questionnaire. MEASUREMENTS: Interview measures of personal demographics, social history, psychiatric morbidity and drug use. Personality disorders were diagnosed via the Structured Clinical Interview for DSM-IV (SCID-II) and neurotic symptoms were assessed using the revised Clinical Interview Schedule (CIS-R). FINDINGS: More than 60% of the heroin users and cannabis users reported that they had used these drugs in prison compared with less than a quarter of the life-time cocaine users. More than a quarter of the heroin users reported that they had initiated use of this drug in prison. The extent of an individual's experience of prison was related more consistently to heroin and/or cocaine use in and out of prison than other personal background, social history or psychiatric variables assessed. CONCLUSIONS: The findings indicate that prisons are a high-risk environment for heroin and other drug initiation and use. Although related to drug use, psychiatric variables were not generally associated with initiation in prison, which was dominated by prison exposure. There is a need to explore ways of reducing heroin initiation in prison as part of a broader risk-prevention strategy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".