Landscapes of psychological trauma in residency education: Exploring lived experiences
Bibliographic record
Abstract
INTRODUCTION: Resident physicians may experience psychological trauma both at work and in their personal lives. Injury from trauma can impact learning, patient care, relationships, mental health and well-being. Residents' experiences of traumatic injury have not been well-described in the literature. The purpose of this study was to explore residents' lived experiences of psychological traumatic injury. METHODS: The research employed a hermeneutic phenomenological methodology. All residents at a single Canadian medical school and support professionals who work with them were invited to participate in semi-structured interviews. Anonymized transcripts were analysed in duplicate and findings interpreted through discussion amongst the research team. RESULTS: Thirteen residents and three support professionals participated. Four core domains of lived experience within participant narratives were identified, each with multiple dimensions: impacts of traumatic injury (multifaceted, internal reactions, layered judgements), adaptations to traumatic injury (shifts in mindset and behaviour), traumatic injury over time (acknowledging, oscillation, meaning-making) and modifiers of traumatic injury (previous life experiences, internal resources, contextual circumstances). Three metanarratives intersecting these dimensions of experience were complexity, sociocultural influences and existential tensions. CONCLUSION: In summary, residents' experiences of trauma and the associated traumatic injury are complex, highly individual and difficult to anticipate or resolve with linear support models. This research will help guide ways to better support residents while addressing problematic aspects of medical education that may contribute to experiences of trauma.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".