Associations between methadone maintenance treatment and crime: a 17‐year longitudinal cohort study of Canadian provincial offenders
Bibliographic record
Abstract
AIMS: To estimate and test the difference in rates of violent and non-violent crime during medicated and non-medicated methadone treatment episodes. DESIGN, SETTING AND PARTICIPANTS: The study involved linkage of population level administrative data (health and justice) for all individuals (n = 14 530) in British Columbia, Canada with a history of conviction and who filled a methadone prescription between 1 January 1998 and 31 March 2015. Methadone maintenance treatment was the primary independent variable and was treated as a time-varying exposure. Each participant's follow-up (mean: 8 years) was divided into medicated (methadone was dispensed) and non-medicated (methadone was not dispensed) periods with mean durations of 3.3 and 4.6 years, respectively. MEASUREMENTS: Socio-demographics of participants were examined along with the main outcomes of violent and non-violent offences. FINDINGS: During the first 2 years of treatment (≤ 2.0 years), periods in which methadone was dispensed were associated with a 33% lower rate of violent crime [0.67 adjusted hazard ratio (AHR), 95% confidence intervals (CI) = 0.59, 0.76] and a 35% lower rate of non-violent crime (0.65 AHR, 95% CI = 0.62, 0.69) compared with non-medicated periods. This equates to a risk difference of 3.6 (95% CI = 2.6, 4.4) and 37.2 (95% CI = 33.0, 40.4) fewer violent and non-violent offences per 100 person-years, respectively. Significant but smaller protective effects of dispensed methadone were observed across longer treatment intervals (2.0 to ≤ 5.0 years, 5.0 to ≤ 10.0 years). CONCLUSIONS: Among a cohort of Canadian offenders, rates of violent and non-violent offending were lower during periods when individuals were dispensed methadone compared with periods in which they were not dispensed methadone.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".