A Meta-Analysis of Substance Misuse Intervention Programs Offered to Women Offenders
Bibliographic record
Abstract
This meta-analytic review examined the effectiveness of substance misuse interventions in reducing recidivism and substance use outcomes among women offenders.A literature search revealed 22 evaluations, reporting 39 effect sizes.The effect estimate for recidivism outcomes revealed 53% to 79% reductions in the odds of recidivism for women participating in interventions.Effect estimates were similar for outcomes relating to substance use, with reductions in the odds of alcohol and drug use ranging from 13% to 82%.Across evaluations reporting recidivism outcomes, gender-neutral and gender-informed interventions were equally effective in reducing recidivism outcomes.Further, sub-group analyses revealed that study quality did not impact reductions in recidivism.Overall, this review lends support to the findings of previous research, suggesting that substance misuse interventions are effective in reducing both recidivism and substance use outcomes among women offenders.
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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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.026 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".