Impact of patient suicide on psychiatry residents: protocol of a qualitative study
Bibliographic record
Abstract
INTRODUCTION: Psychiatrists' first exposure to patient suicide often occurs during residency training. Previous research shows that experiencing a patient's death by suicide during residency can have significant impacts on trainees' well-being, self-esteem and approach to practice. However, existing research on this topic is mostly limited to survey-based data, which does not facilitate nuanced exploration. This study will use a qualitative approach to gain an in-depth understanding of Canadian psychiatry residents' experiences of a patient's death by suicide and the types of supports that may help trainees to process this loss and integrate this experience into their professional identity formation. METHODS AND ANALYSIS: This study will conduct 15-25 semistructured qualitative interviews with psychiatry resident physicians across Canada to explore their experiences of patient loss by suicide during training. Interview data will be transcribed verbatim and analysed using the principles of Constructivist Grounded Theory. ETHICS AND DISSEMINATION: The study findings will be reported and accessible to residency training programmes, the academic community, the media and the public.This study was approved by the Research Ethics Board of the Centre for Addiction and Mental Health (Protocol Identifying Number 2024/125).
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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 | 0.101 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.034 | 0.005 |
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".