Is Risk-Need-Responsivity Enough? Examining Differences in Treatment Response Among Male Incarcerated Persons
Bibliographic record
Abstract
Research examining the efficacy of cognitive behavioral therapy (CBT) in reducing recidivism has paid little attention to treatment factors contributing to response variability. Using an archival sample of 448 participants exposed to a risk-need-responsivity (RNR)-informed CBT program or no treatment, a multigroup latent profile analysis yielded a four-profile solution: a treatment-nonresponsive group and three treatment-responsive groups. Among the treatment-responsive profiles, reduced criminal attitudes were most predictive of desistance from reoffending. Elevated rates of recidivism and negligible gains following treatment were associated with pretreatment elevations in antisocial traits, risk level, and negative attitudes toward treatment. These findings underscore a greater need for individualized assessment of risk and treatment motivation, the importance of altering criminal sentiments to prevent reentry into the system upon release, and challenge the idea that 200 hours of treatment is sufficient for lasting change. Study limitations and further directions are discussed, including the need for correctional treatment outcome research to better isolate individual differences.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".