Coercive measures by Ontario forensic hospitals.
Bibliographic record
Abstract
<div> The use of coercive measures such as seclusion and restraint in forensic mental healthcare settings is widespread but controversial. Efforts to reduce these measures require knowledge of patient-related risk factors. The present study aimed to identify and confirm factors related to seclusion and restraint that can be assessed upon admission among men and women admitted to forensic hospitals in Ontario, Canada. We included cross-sectional Ontario Mental Health Reporting System admission data for adult patients admitted to 10 forensic psychiatric hospitals between April 1, 2013, and March 31, 2023. We determined patient demographic, administrative, and clinical characteristics associated with seclusion and physical and manual restraint episodes during the first three days of admission. We conducted logistic Generalized Linear mixed Models (GLMM) to examine the association between the independent variables and restraint and seclusion while accounting for variability across facilities. Of 7635 patients, 30.2% (n = 2302) were secluded, and 3.7% (n = 286) were restrained within their first three days of admission. Secluded patients were more likely to be young adults, male, and scored higher on violence and aggression measures. Being admitted due to fitness-related reasons, lack of insight, medication non-adherence, higher scores on the mania scale and cognitive impairment further contributed to the higher odds of being secluded, whereas neurocognitive disorder diagnosis and elopement behavior were protective factors. Restrained patients were also more likely to be young adults, have a diagnosis of mood or anxiety, neurodevelopmental or personality disorder, and scored higher on violence and aggression measures. Fitness-related status, medication non-adherence, and cognitive impairment further contributed to this model of restraint. Indigenous self-identification and immigration status were not significant contributors to either model. Clinicians can assess indicators associated with seclusion and restraint when forensic patients are admitted to forensic hospitals or during the first three days of their stay, enabling effective targeting of those needs to reduce the use of coercive measures. </div>
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.540 | 0.002 |
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; both teacher heads agree on what is shown here.
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".