A Theoretical and Empirical Review of Dialectical Behavior Therapy Within Forensic Psychiatric and Correctional Settings Worldwide
Bibliographic record
Abstract
Cognitive-behavioral programs which are structured, skills-based, and risk-focused have been found to reduce recidivism rates by up to 55%. Dialectical behavior therapy (DBT) exemplifies all of these components, and has been rapidly adapted and implemented in correctional and forensic psychiatric facilities worldwide to reduce recidivism. Regrettably, the widespread implementation of adapted DBT has outpaced the research on its effectiveness for this purpose. Thus, it is currently unclear whether these programs are meeting the rehabilitation needs of these systems. In the following article, a qualitative systematic literature review of all DBT programs within forensic psychiatric and correctional populations using the PRISMA statement guidelines is presented, along with a detailed exploration of how these programs align with best practices in offender rehabilitation, and whether they are effective in reducing recidivism risk. Results offer very preliminary evidence that DBT has the potential to reduce recidivism risk in criminal justice systems if applied within a Risk-Need-Responsivity framework.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".