Exploring Uniformity of Clinical Judgment: A Vignette Approach to Understanding Healthcare Professionals’ Suicide Risk Assessment Practices
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objectives Suicide risk assessment often requires health professionals to consider a complex interplay of multiple factors, with a significant reliance on judgment, which can be influenced by factors such as education and experience. Our study aimed at assessing the uniformity of decision making around suicide risk within healthcare professionals. Methods We used a factorial survey approach to gather information on healthcare professionals’ demographics, clinical experience, and their decision on 3 vignettes of patients with suicidal ideation. We used Kruskal-Wallis tests for determining if there were significant differences between groups for continuous variables and Spearman rank correlation for measuring the association between continuous variables. Content analysis was used for analyzing free-text comments. Results Responses were gathered from 79 healthcare professionals (nurses, nurse practitioners, physicians) who worked in primary care, mental health, or emergency department settings. Median suicide risk rates across all respondents were 90%, 50%, and 53% for vignettes 1, 2, and 3, respectively. Confidence in healthcare professionals’ decisions was significantly associated with the clinical designation and personal risk profile of the healthcare professional in certain vignettes, with nurses and those willing to take more risks having a higher confidence in their decisions for vignettes 1 and 3, respectively. Treatment decision was significantly associated with mental health experience (i.e., those with lengthier mental health experiences were less likely to choose “admit to psychiatry ward” for vignette 2), clinical designation (i.e., nurses were more likely to “admit to psychiatry ward” for vignette 1), and practice setting. It should be noted that these associations were not consistent across all 3 vignettes, and results for each association were only specific to 1 of the 3 vignettes. Discussion Findings compare decision-making practices for suicide risk assessment across several types of healthcare professions over a range of practice settings, with the high-risk vignette showing the least variability. Insights from this study are relevant when building clinical decision support systems for suicide risk assessment. Designers should think about incorporating tailored messaging and alerts to health professionals’ mental health experience and/or designation. Conclusions Within our Canadian sample, there was considerable variability among healthcare professionals assessing the risk of suicide, with important implications for tailoring education and decision support.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it