Sleep Quality Among Psychiatry Residents
Bibliographic record
Abstract
OBJECTIVE: Medical residency programs are traditionally known for long working hours, which can be associated with a poor quality of sleep and daytime sleepiness. However, few studies have focused on this theme. Our objective was to investigate sleep quality, daytime sleepiness, and their relation with anxiety, social phobia, and depressive symptoms. METHODS: This cross-sectional observational study involved 59 psychiatry residents. The Pittsburgh Sleep Quality Index (PSQI) and the Epworth Sleepiness Scale (ESS) were used to measure the quality of sleep and excessive daytime sleepiness ([EDS] and ESS > 10), respectively. RESULTS: Among the 59 psychiatry residents, 59.3% had poor sleep quality (PSQI > 5) and 28.8% had EDS. Poor sleep quality was associated with higher EDS (P = 0.03) and the year of residency program (P = 0.03). Only 20% of residents with poor sleep had consulted at least once for sleep problems; 54.2% had used medications for sleep; and 16.9% were using medications at the time of interview. Only 30% obtained medication during medical consultations. Poor sleep was associated with irregular sleep hours (P = 0.001) and long periods lying down without sleep (P = 0.03). Poor sleep quality was also associated with high scores of anxiety symptoms (P < 0.001) and social phobia symptoms (P = 0.02). CONCLUSION: Psychiatry residents frequently have poor sleep quality and EDS. Considering that sleep disorders can affect quality of life, predispose to metabolic syndrome, and be associated with worse performance at work, attention to this clinical problem is needed.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".