Persistent cannabis use as an independent risk factor for violent behaviors in patients with schizophrenia
Bibliographic record
Abstract
Although recent studies have shown a moderately strong association between cannabis use and violence among people with severe mental disorders, the direction of this association has not been investigated prospectively in a population with schizophrenia. Therefore, this study aims to determine, using cross-lag models, whether a temporal relationship between cumulative cannabis use and violence exists in a population with schizophrenia. The authors reported findings covering an 18-month period from a randomized, double-blind clinical trial of antipsychotic medications for schizophrenia treatment. Among the 1460 patients enrolled in the trial, 965 were followed longitudinally. Although persistent cannabis use predicted subsequent violence, violence did not predict cannabis use. The relationship was therefore unidirectional and persisted when controlling for stimulants and alcohol use. Finally, a significant body of evidence suggests a link between persistent cannabis use and violence among people with mental illnesses. Studies to further investigate the mechanisms underlying this association should be conducted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".