Self-harming behaviors and forensic system-related factors: an analysis of the Ontario review board database
Bibliographic record
Abstract
BACKGROUND: In Canada, ensuring public safety, and the safety and well-being of accused individuals under the jurisdiction of the provincial review board are very important. While previous studies have reported a significant risk of self-harming behaviors (non-suicidal self-injury and suicide attempt) in forensic psychiatric settings, no large population study has assessed any relationship between forensic system-related factors and self-harming behaviors. A better understanding of these factors can help clinicians implement protective measures to mitigate self-harming behaviors or actions. METHODS: Using the Ontario Review Board (ORB) database covering 2014-2015 period (n = 1211, mean age = 42.5 ± 13.37 years, males = 86.1%), we analyzed the prevalence and factors associated with self-harming behaviors, emphasizing the characterization of the forensic system-related factors (ORB status, legal status, type of offense, previous criminal history, and victim relationship). The relationships between the forensic system-related factors and self-harming behaviors were explored using five separate logistic regression models, controlling for clinical and sociodemographic characteristics. RESULTS: Approximately 4% of the individuals in the forensic system over the study period engaged in self-harming behaviors Among the studied patients, individuals determined to be unfit to stand trial and inpatients were significantly more likely to have self-harming behaviors. There was no significant relationship between the type of offence, victim relationship, and previous criminal history with self-harming behavior. CONCLUSION: Forensic psychiatry inpatients should have close observation, screening, monitoring, and individual tailored management strategies for self-harming behaviors. The findings of this study indicate that forensic system-related factors, especially those that pertain to the status of individuals in the forensic system (i.e., unfit to stand trial and being an inpatient) are more responsible for self-harming behaviors among forensic patients in Ontario.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".