Impact of 24‐Hour On‐Call Shifts on Headache in Medical Residents: A Cohort Study
Bibliographic record
Abstract
BACKGROUND: During 24-hour on-call shifts medical residents are exposed to diverse circumstances such as sleep deprivation and stress. OBJECTIVE: Our aim is to assess the effect of 24-hour on-call shifts on medical residents' headache-related disability. METHODS: The Migraine Disability Assessment Scale (MIDAS), the Headache Impact Test (HIT-6), the Pittsburgh Sleep Quality Index (PSQI), and the Hospital Anxiety and Depression Scale (HADS) questionnaires were administered to medical residents who had never performed on-call shifts at baseline and 6 months after beginning 24-hour on-call shifts. Scores were compared. RESULTS: About 66 medical residents completed this study. About 21.2% (n = 14) had history of migraine, 42.4% (n = 28) had a history of tension-type headache (TTH) and 12.1% (n = 8) had a history of both migraine and TTH. Among medical residents with migraine, the median MIDAS score was significantly higher after starting 24-hour on-call shifts than at a baseline (4.0 vs 8.0; Wilcoxon, P = .001), meaning that, on average, disability increased from little or no disability, to moderate disability. No difference in HIT-6 scores was found. The median score of PSQI and HADS was higher at 6 months (PSQI: 7.0 vs 8.0; P = .003), (HADS: 5.0 vs 8.0; P < .001) for the general group. CONCLUSIONS: In medical residents with migraine, migraine-related disability increased after starting 24-hour on-call shifts. We also found a worsening in depression and anxiety symptoms and self-reported sleep quality in medical residents with and without headache history.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".