Evidence map›Paper›PMID 40604632›Full record

ArticleBMC public health2025

Development and internal validation of a nomogram for sleep quality among Chinese medical students: a cross-sectional study.

Zhen Lv, Hao Xu, Jun Chen, Handong Yang, Jishun Chen, Dongfeng Li, Ying Wang, Huailan Guo, Ningrui Zhang, Zhixin Liu and 2 more

Abstract readValidation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Zhen Lv *Sinopharm Dongfeng General Hospital (Hubei Clinical Research Center of Hypertension), School of Public Health, Hubei University of Medicine, No.16, Daling Road, Shiyan, 442000, China.
Hao Xu *Sinopharm Dongfeng General Hospital (Hubei Clinical Research Center of Hypertension), School of Public Health, Hubei University of Medicine, No.16, Daling Road, Shiyan, 442000, China.
Jun Chen *Sinopharm Dongfeng General Hospital (Hubei Clinical Research Center of Hypertension), School of Public Health, Hubei University of Medicine, No.16, Daling Road, Shiyan, 442000, China.
Handong YangSinopharm Dongfeng General Hospital (Hubei Clinical Research Center of Hypertension), School of Public Health, Hubei University of Medicine, No.16, Daling Road, Shiyan, 442000, China.
Jishun ChenSinopharm Dongfeng General Hospital (Hubei Clinical Research Center of Hypertension), School of Public Health, Hubei University of Medicine, No.16, Daling Road, Shiyan, 442000, China.
Dongfeng LiSinopharm Dongfeng General Hospital (Hubei Clinical Research Center of Hypertension), School of Public Health, Hubei University of Medicine, No.16, Daling Road, Shiyan, 442000, China.
Ying WangDepartment of Nosocomial Infection Management, Wuhan University Zhongnan Hospital, Wuhan, 430071, China.
Huailan GuoCenter for Environment and Health in Water Source Area of South-to-North Water Diversion, School of Public Health, Hubei University of Medicine, Shiyan, 442000, China.
Ningrui ZhangSinopharm Dongfeng General Hospital (Hubei Clinical Research Center of Hypertension), School of Public Health, Hubei University of Medicine, No.16, Daling Road, Shiyan, 442000, China.
Zhixin LiuCollege of Basic Medical Sciences, Hubei University of Medicine, No. 30, South Renmin Road, Shiyan, Hubei, 442000, China.
Xinwen MinSinopharm Dongfeng General Hospital (Hubei Clinical Research Center of Hypertension), School of Public Health, Hubei University of Medicine, No.16, Daling Road, Shiyan, 442000, China. minxinwen@163.com.
Wenwen WuSinopharm Dongfeng General Hospital (Hubei Clinical Research Center of Hypertension), School of Public Health, Hubei University of Medicine, No.16, Daling Road, Shiyan, 442000, China. wuwenwen108@126.com.

Funding

Advantages Discipline Group (Public Health) Project in Higher Education of Hubei Province (2021-2025) 2022PHXKQ2Faculty Development Grants from Hubei University of Medicine 2020QDJRW003Natural Science Foundation of Hubei Provincial Department of Education D20222105Principal Investigator Program at Hubei University of Medicine HBMUPI202102State Key Laboratory of Green Building in Western China LSKF202104
6 · The paper itself

Abstract

backgroundPoor sleep quality is common among Chinese medical students. Identifying its predictors is essential for implementing individualized interventions. However, clinical prediction models targeting sleep quality in this population remain scarce. This study aimed to develop and validate a nomogram to predict poor sleep quality among Chinese medical students.

methodsA cross-sectional study was used to collect data among Chinese medical students at the Hubei University of Medicine. A total of 2893 medical students were randomly divided into training (70%) and validation (30%) groups. Multivariable Firth logistic regression analysis was performed to examine factors associated with sleep quality. Thereafter, these factors were used to develop a nomogram for predicting sleep quality. The predictive performance was evaluated by receiver operating characteristic curve (ROC) analysis, calibration curve analysis, and decision curve analysis (DCA).

resultsA total of 70.4% of medical students in the study reported poor sleep quality. The predictors of sleep quality included grade, gender, self-assessment of interpersonal relationships, and self-assessment of health status. The scores of the nomogram ranged from 0 to 189, and the corresponding risk ranged from 0.50 to 0.95. The calibration curve showed that the nomogram had good classification performance. The area under the curve (AUC) of the ROC for the training group is 0.676, and that for the validation group is 0.702. The DCA demonstrated that the model also had good net benefits.

conclusionsThe nomogram prediction model has sufficient accuracies, good predictive capabilities, and good net benefits. The model can also provide a reference for predicting the sleep quality of medical students.

Indexed as

NomogramsSleep QualityStudents, MedicalAdultChinaCross-Sectional StudiesEast Asian PeopleFemaleHumansMaleSurveys and QuestionnairesYoung AdultMedical studentsNomogramPrediction modelSleep quality

Identifiers

PMID40604632
PMCPMC12218941

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.