ArticleFrontiers in neuroscience2022
Development and validation of mathematical nomogram for predicting the risk of poor sleep quality among medical students.
Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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3 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Prevalence of sleep disturbance among chinese college students: an updated meta-analysis.BMC psychiatry · 2026Pooled it
- Establishment and validation of a nomogram for dropout intention in Chinese early year medical undergraduates.BMC medical education · 2024Article
- [Postoperative Sleep Disturbance in Patients Undergoing Arthroplasty: Risk Prediction Modeling Based on Logistic Regression].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2023Article
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Authors and funding
11 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Despite the increasing prevalence of poor sleep quality among medical students, only few studies have identified the factors associated with it sing methods from epidemiological surveys. Predicting poor sleep quality is critical for ensuring medical Students' good physical and mental health. The aim of this study was to develop a comprehensive visual predictive nomogram for predicting the risk of poor sleep quality in medical students. Methods: We investigated medical Students' association with poor sleep quality at JiTang College of North China University of Science and Technology through a cross-sectional study. A total of 5,140 medical students were randomized into a training cohort (75%) and a validation cohort (25%). Univariate and multivariate logistic regression models were used to explore the factors associated with poor sleep quality. A nomogram was constructed to predict the individual risk of poor sleep quality among the medical students studied. Results: 31.9% of medical students in the study reported poor sleep quality. We performed multivariate logistic analysis and obtained the final model, which confirmed the risk and protective factors of poor sleep quality ( Conclusion: Our nomogram helps predict the risk of poor sleep quality among medical students. The nomogram used includes the five factors of drinking, study stress, recent physical discomfort, depressive symptoms, and anxiety symptoms. The model has good performance and can be used for further research on and the management of the sleep quality of medical students.
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