Homicide and schizophrenia: maybe treatment does have a preventive effect
Bibliographic record
Abstract
BACKGROUND: Persons with schizophrenia have been found to be at increased risk for homicide as compared with the general population. The increased risk may be associated with the implementation of the policy of deinstitutionalization. METHOD: Persons with schizophrenia who had committed or attempted homicide in the German state of Hessen from 1992 to 1996 and in the Federal Republic of Germany from 1955 to 1964 were compared. RESULTS: Schizophrenia increased the risk of homicide 16.6 times (95% CI 11.2-24.5) in the recent cohort and 12.7 times (95% CI 11.2-14.3) in the older cohort. These odds ratios are not statistically different. The lack of appropriate services for chronic high-risk patients and the non-use of mental health services by first episode, acutely psychotic patients were associated with homicide. CONCLUSION: There has been no increase in the risk of homicide among persons with schizophrenia since the implementation of the policy of deinstitutionalization. The examination of the recent period suggests that the provision of specialized long-term care to persons with schizophrenia who are at high risk for violent behaviour and the use of mental health services by acutely psychotic persons may reduce the risk of homicide.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".