Perseverance, faith and stoicism: a qualitative study of medical student perspectives on managing fatigue
Bibliographic record
Abstract
CONTEXT: Fatigue risk management (FRM) strategies offer a potential solution to the widespread problem of fatigued trainees in the clinical workplace. These strategies assume a shared perception that fatigue is hazardous. Despite the growing body of evidence suggesting that fatigue leads to burnout and medical errors, previous research suggests that residents perceive fatigue as a personal, surmountable burden rather than an occupational hazard. Before we can implement FRM, we need a better understanding of when and how such problematic notions of fatigue are adopted by medical trainees. Thus, we sought to explore how third-year medical students understand and manage the workplace fatigue they experience during their first year of clinical rotations. METHODS: A total of 22 third-year medical students participated in semi-structured interviews exploring their perspectives of workplace fatigue. Data collection and analysis occurred iteratively in keeping with constructivist grounded theory methodology and were informed by theoretical sampling to sufficiency. RESULTS: Our participants described unprecedented levels of sleep deprivation combined with uncertainty and confusion that led to significant fatigue during training. Drawing on their workplace experience, trainees believed that fatigue posed three distinct threats, which evoked different coping strategies: (i) threat to personal health, managed by perseverance; (ii) threat to patients, managed by faith in the system, and (iii) threat to professional reputation, managed by stoicism. CONCLUSIONS: Our findings highlight how senior medical students grapple with fatigue, as they understand it, within a training context in which they are expected to deny the impact of their fatigue on patients and themselves. Despite empirical evidence to the contrary, the prevailing assumption amongst our participants is that an ability to withstand sleep deprivation without impairment will develop naturally over time. Efforts to implement FRM strategies will need to address this assumption if these strategies are to be successfully taken up and effective.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".