Distinguishing the features of offenders who do and do not complete substance use treatment in corrections: Extending the reach of psychological services.
Bibliographic record
Abstract
Approximately 80% of offenders serving sentences in Canadian federal institutions present a history of substance use that requires psychological services. Correctional substance use programs (SUPs) have been shown to be effective in reducing reconviction for offenders who complete all sessions. However, a significant proportion of offenders entering an SUP do not complete the program for offender-related reasons such as dropping out or suspension. The purpose of the present study was to examine the prevalence of SUP noncompletion and the extent to which offenders who do not complete because of offender-related reasons differ from completers and those who do not complete for administrative reasons (e.g., transferred, released, program cancelled) on demographics, offense characteristics, substance use severity, SUP exposure, criminogenic needs, risk of recidivism, reintegration potential, and institutional charges. The study considered 4,592 federally sentenced men offenders who were enrolled in an SUP. Results showed that noncompleters for offender reasons were younger, less educated, less motivated for intervention, more likely to have committed a violent crime, more likely to have incurred a serious charge while incarcerated, more likely to have presented severe substance use, and more likely to report an unstable employment history. There were relatively few differences between SUP completers and SUP noncompleters for administrative reasons. The results highlight that noncompleters for offender reasons present individual characteristics that might affect their responsivity to treatment. Identifying offenders presenting this specific profile and tailoring psychological services to facilitate their learning could help reduce program noncompletion and improve rehabilitation. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".