Dual harm among patients in the Ontario forensic mental health system
Bibliographic record
Abstract
BACKGROUND: Dual harm involves the unfortunate experience of harm to self and others/objects. Safeguarding individuals in forensic psychiatric settings against all forms of harm to self and others is sacrosanct. While understanding dual harm is crucial in the care and rehabilitation of patients in forensic psychiatric settings, only a few studies have explored this phenomenon. This study examined dual harm and its associated clinical and sociodemographic factors among forensic patients in Ontario, Canada. METHODS: In this retrospective study, we used data from the Ontario Review Board (ORB) (n = 1240; mean age 42.54±3.32 years, and 85.73% male). We defined dual harm as the co-occurrence of self-harming behaviour in the last 12 months and violent behaviour towards others or objects (such as verbal, physical, or sexual aggression). We analysed the data in relation to clinical and sociodemographic factors. RESULTS: Of 1240 patients, 43 (3.55%) had engaged in dual harm. Most of them had engaged in dual harm related to verbal aggression (3.15%), followed by dual harm related to aggression towards objects (2.97%), dual harm related to aggression towards others (2.73%), and dual harm related to sexual aggression was the rarest (1.32%). Only 12 patients had engaged in all types of dual harm. Having a previous history of dual harm and a diagnosis of a neurodevelopmental disorder increased the chance of perpetrating/engaging in dual harm. However, increasing age and a higher education decreased the chance of dual harm. These factors were similar for different types of dual harm, except for dual harm related to sexual aggression, which was the only subtype associated with having a personality disorder diagnosis. Again, the experience of violence increased the chance of self-harm. CONCLUSION: Dual harm is present among forensic patients in Ontario, and self-harm is prevalent among individuals with various forms of aggression, especially when the violence was perpetrated towards objects. Strategies to manage the risk of self-harm among aggressive patients should be put in place to mitigate dual harm and the associated complications, especially among individuals with neurodevelopmental disorders.
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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 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".