What is commonly missed in the suicidal risk assessments in the emergency room?
Bibliographic record
Abstract
Introduction Suicidal behaviour remains the most common reason for presentation to the emergency rooms. In spite of identifiable risk factors, suicide remains essentially unpredictable by current tools and assessments. Moreover, some factors may not be included consistently in the suicidal risk assessments in the emergency room by either emergency medicine physicians or psychiatrists. Method Step 1 involved the administration of a survey on the importance of suicide predictors for assessment between psychiatry and emergency medicine specialties. In step 2 a chart review of psychiatric emergency room patients in Kingston, Canada was conducted to determine suicide predictor documentation rates. In step 3, based on the result of the first 2 steps a suicide risk assessment tool (Suicide RAP [Risk Assessment Prompt]) was developed and presented to both teams. A second patient chart review was conducted to determine the effectiveness of the educational intervention and suicide RAP in suicide risk assessment. Results Significant differences were found in the rating of importance and the documentation rates of suicide predictors between the two specialties. Several predictors deemed important, have low documentation rates. Thirty of the suicide predictors showed increased rates of documentation after the educational intervention and the presentation of the suicide RAP. Conclusion Though a surfeit of information regarding patient risk factors for suicide is available, clinicians and mental health professionals face difficulties in integrating and applying this information to individuals. Based on the result of this study suicide RAP and educational intervention could be helpful in improving the suicidal risk assessment. Disclosure of interest The authors have not supplied their declaration of competing interest.
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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 | 0.002 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".