Psychiatrists’ experiences of patient suicide loss: perspectives from residency and supervision
Bibliographic record
Abstract
BACKGROUND: Patient suicide is a common adverse event during psychiatric residency. This study aimed to understand psychiatry residents' experiences of patient suicide from the perspectives of psychiatrists who experienced this loss as a resident and/or as a psychiatrist supervising residents, and to assess which interventions may help residents feel supported after such tragedies. METHODS: This is a secondary qualitative analysis based on a previous study in which psychiatrists who experienced a patient's death by suicide were interviewed about their experiences. Of the 18 participants interviewed, 13 participants had experienced the death of a patient by suicide during residency and/or had experience supervising residents in the context of this loss. Direct transcriptions from these 13 interviews were analyzed using constructivist grounded theory. RESULTS: Participants' experiences of patient suicide during training were influenced by the practice setting, patient-related factors, learners' personal circumstances, and the supervisor-trainee relationship. Participants described feeling supported by supervisors from a practical perspective, such as offering a modified workload. Emotional, professional, and existential supports were identified as helpful, though their provision varied depending on the supervisory dynamic. There were differences between resident and supervisor responses to patient suicide, which may be due to residents' fear of negative evaluations and lack of formal training for supervisors. CONCLUSIONS: The experience of a patient's death by suicide during residency is diverse and multifactorial. Encouraging connection within the supervisory relationship is critical for both residents and supervisors in coping with the loss and effectively supporting trainees.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".