Psychosis in high-security and general psychiatric services
Bibliographic record
Abstract
BACKGROUND: Serious violence is an unusual but significant correlate of psychosis, and leads to the need for specialist secure psychiatric services. Most such service users have previously used general psychiatric services. AIMS: To examine diagnostic and socio-demographic differences between high-security psychiatric service users from their peers in community services. METHOD: Two groups of patients with psychosis were compared: a national sample of high-security hospital residents, and a sample of patients in contact with general psychiatric services. RESULTS: Schizophrenia was the almost invariable diagnosis for all special hospital patients. White patients in the community sample were significantly more likely to have affective components to their illness compared with African-Caribbean patients; unlike those in special hospitals. There was a small excess in the proportion of African-Caribbean patients in the special hospital group, controlling for diagnosis, gender and locality. Men were overrepresented in this group. CONCLUSIONS: Among patients with psychosis, having a diagnosis of schizophrenia and being male increase the likelihood of special hospital admission. Suggestions that ethnic minority patients are much more likely to have engaged in serious violence and need high-security placement were not borne out.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".