O045 Sleep management strategies among medical students
Bibliographic record
Abstract
Abstract Introduction Medical students are undertaking an intense curriculum, the stress of which may cause or worsen insomnia and depressive symptoms. We aim to investigate factors which might affect the sleep of medical students, and how they currently manage their sleep. Methods A brief online survey was sent to medical students, consisting of validated questionnaires, and questions related to sleep management strategies. Results We recruited 828 participants—49.5% reported insomnia symptoms and 51.4% reported depressive symptoms. After adjusting for gender, ethnicity and age, depressive symptoms (Mild: odds ratio (OR) = 6.26; Moderate: OR = 18.13; Severe: OR = 15.57), and sleep hygiene (OR = 1.07) were associated with insomnia symptoms. Commonly endorsed strategies for sleep management by students were undertaking regular exercise (80.1%), having consistent sleep-wake time (71.3%), and limiting caffeine intake (70.3%). Few were willing to see a clinician (23.4%) or take medication (22.3%). Participants with insomnia symptoms were more likely to prefer limiting their alcohol intake (OR = 1.77), limiting daytime naps (OR = 1.5), seeing clinicians (OR = 1.86), and taking sleep medication (OR = 3.98), but less likely to prefer avoiding intense work (OR = 0.71) or minimizing using electronics (OR = 0.60) close to bedtime than those without insomnia symptoms. High sleep self-efficacy was associated with lower odds for having insomnia symptoms (OR = 0.74 (0.70, 0.77)). Discussion Self-reported insomnia and depression are common among medical students. Increased awareness and greater resources are needed to support the sleep health and emotional well-being of medical students.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".