Resident Physicians are at Increased Risk for Dangerous Driving after Extended-duration Work Shifts: A Systematic Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Resident physicians often work longer than 24 consecutive hours with little or no sleep. A systematic review of the literature was conducted to investigate the risk of resident physician motor vehicle collisions (MVC), and dangerous driving, after extended-duration work shifts (EDWS). MATERIAL AND METHODS: A keyword search was performed for original research articles evaluating any aspect of driving safety following EDWS for the resident physician population. Two authors independently reviewed articles for inclusion. Subsequent independent data abstraction and quality appraisal were carried out. Five articles met the study inclusion criteria. RESULTS: The quality of the evidence was low to very low. Results were not pooled due to study heterogeneity. Residents reported between 2.3 to 3.8 hours of sleep during EDWS. Three survey-based studies identified an increased risk of MVCs and falling asleep at the wheel after EDWS. One study associated weekly cumulative sleep hours lost with the risk of falling asleep while driving. Both driving simulation and survey studies linked EDWS with MVCs. Notably, a driving simulation study found an increase in crash frequency in male residents post-EDWS. Additionally, a survey reported that the risk of an MVC post-EDWS increased by 16.2% per shift worked in a month. CONCLUSION: The period following EDWS is associated with an increased risk of potentially life-threatening driving safety risks for resident physicians. These observations warrant careful consideration. They suggest that there is a need for greater awareness and action in order to avoid the occupational and public health risks of driving after EDWS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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 it