Quality of Resident Violence Risk Assessments in Psychiatric Emergency Settings
Bibliographic record
Abstract
OBJECTIVE: To identify how psychiatric residents perceive their ability to conduct violence risk assessments and the risk factors they considered relevant in an emergency department setting. METHOD: We surveyed 55 of 159 psychiatric residents at the University of Toronto as to their experience and education in assessing suicide and violence risk. The residents, and a comparison group of 11 of 16 staff psychiatrists in the Law and Mental Health program at the Centre for Addiction and Mental Health, then participated in a mock interview with one of the authors. The subjects were directed to ask for all risk factors that would be relevant in determining the violence risk of a hypothetical patient with homicidal ideation. The risk factors they requested were compared with the risk factors found in the Historical, Clinical and Risk Management-20 (HCR-20) structured clinical judgment tool. RESULTS: Psychiatric residents, on average, inquired about 6 fewer HCR-20 risk factors than staff psychiatrists (8.5, compared with 14.7). The number of HCR-20 items identified by residents correlated with several items; more risk factors were elicited by residents in a higher year of training, those who had received more formal and informal education, the number of patients for whom they had discharged a duty to warn, and the number of suicidal and violent patients they had previously assessed. Confidence at assessing violence risk was not correlated with performance. CONCLUSIONS: Psychiatric residents identify significantly fewer risk factors for violence than staff psychiatrists. Resident performance was correlated with increasing experience and education. It was not related to self-confidence in performing this task.
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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".