A Realist Evaluation of a Fatigue Risk Management Plan (FRMP) Implementation in Obstetrics and Gynecology Residency: Calls for Systemic, Structural and Cultural Reform
Bibliographic record
Abstract
Abstract Objective Accreditation standards in residency education are calling for initiatives to promote the wellness of resident physicians including the implementation of fatigue risk management plans (FRMPs). We sought to conduct a realist evaluation of a FRMP within a five-year Obstetrics and Gynecology (OBGYN) residency training program in labour and delivery units. Design Mixed method study design informed by realist inquiry. Setting A single OBGYN residency program comprised of N=32 resident physicians who provided in-house labour and delivery call at four hospitals across a city of over one million people. Method Realist inquiry askes what works, for whom, in what circumstances, and why? through examining contexts, mechanisms, and outcomes. We collected quantitative and qualitative data from resident physicians sequentially across three time points. Data were thematically analyzed, and configuration on contexts, mechanisms, and outcomes were identified using a realist approach. Results There was n=19 unique participants (60% response rate). Most of the participants identified as women (93.7%), single (56.2%) and without children (93.7%). Participants mean age was 28.5 years and ranged from junior to senior residents. We found no significant difference between median sleepiness scores across three timepoints (p=0.17) however 20% of residents reported starting and ending shifts with high sleepiness scores signaling impairment that is hazardous to both residents and patients. The n=6 resident interview participants, reported overlooking patient details (forgetting to order tests, and delaying care) as well as personal safety issues such as driving home whilst fatigued despite FRMP implementation. Conclusion Specific aspects of the OBGYN FRMP such as the nap model and nutrition could help with decreasing perceptions of fatigue related to lack of sleep and lack of available food. While FRMPs might be helpful in de-stigmatizing fatigue in residency, FRMPs are unlikely to decrease levels of resident fatigue because of systemic, structural, and cultural barriers.
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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 | 0.090 | 0.112 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".