Interventions for Adult Offenders With Serious Mental Illness [Internet]
Bibliographic record
Abstract
Objective To comprehensively review the evidence for treatments for offenders with serious mental illness (i.e., schizophrenia, schizoaffective disorder, bipolar disorder, or major depression) in jail, prison, or forensic hospital, or transitioning from any of these settings to the community (e.g., home, halfway house). Data sources We searched 12 internal and external databases including MEDLINE®, PreMEDLINE®, and Embase® for the time period January 1, 1990, through August 20, 2012. Review methods We refined the topic, Key Questions, and protocol with experts in the field and determined the study inclusion criteria and risk-of-bias items a priori. Abstract and full-text review and the risk-of-bias assessment were done in duplicate. A second reviewer verified data extraction. Extracted study information included study design, patient enrollment and baseline characteristics, risk-of-bias items, and outcome data. Because of the nature of the available evidence, we chose to perform a qualitative synthesis rather than meta-analysis. We graded the strength of evidence for each treatment comparison and outcome based on the size, risk of bias, and results of the evidence base. We discussed applicability by focusing on the populations, interventions, and settings of the studies. Results We included 19 publications describing 16 comparative trials. The studies were conducted in the United States, Canada, United Kingdom, New Zealand, and Australia. The risk of bias for all reported outcomes was medium for 15 trials and low for 1 trial. For incarceration-based interventions, evidence of low strength favored antipsychotics other than clozapine over treatment with clozapine for improving psychiatric symptoms. For all other incarceration-based interventions assessed—other pharmacologic therapies, cognitive therapy, and modified therapeutic community—evidence was insufficient to draw any conclusions. For individuals transitioning from the incarceration setting to the community, evidence of low strength supported discharge planning with benefit-application assistance and integrated dual disorder treatment compared with standard of care for increasing mental health service use and/or reducing psychiatric hospitalizations. Evidence was insufficient for comparing interventions administered by a forensic specialist with interventions administered by mental health professionals and for comparing interpersonal therapy with psychoeducation for offenders transitioning from incarceration to the community. More comparative trials are needed to increase our confidence in the findings for which the strength of evidence is low and to address the questions for which the evidence was insufficient. Conclusions We identified some promising treatments for individuals with serious mental illness during incarceration or during transition from incarceration to community settings. Treatment with antipsychotics other than clozapine appears to improve psychiatric symptoms more than clozapine in an incarceration setting. Two interventions, discharge planning with Medicaid-application assistance and integrated dual disorder treatment programs, appear to be effective interventions for seriously mentally ill offenders transitioning back to the community. The applicability of our findings may be limited to the populations and settings in the included studies.
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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 | 0.006 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".