The criminogenic, clinical, and social problems of forensic and civil psychiatric patients.
Bibliographic record
Abstract
Forensic psychiatric patients consume an increasing proportion of mental health resources in Canada and the United States. To inform mental health policy and practice, we compared the criminogenic, clinical, and social problems of forensic patients to those of civilly committed psychiatric patients in two Canadian studies. We predicted that forensic patients would score higher on criminogenic problems and lower on clinical and social problems than civil patients in two studies: one comparing 83 forensic and 189 civil inpatients on a clinician-completed form, the Resident Assessment Instrument--Mental Health, at an urban mental health center, and the second comparing 423 forensic and 178 civil patients assessed at different times using the Patient Problem Survey. The two studies were quite similar in their findings, despite differences in their samples, measures, and data collection methods. In both studies, forensic patients were similar to or lower than civil psychiatric patients in all criminogenic, clinical, and social problems. We conclude that forensic mental health services would benefit greatly by drawing from knowledge accumulated in the general psychiatric literature. This finding also supports the idea that many forensic patients can be appropriately diverted to nonforensic mental health services.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".