Observational Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Psychiatry. Aug 19, 2023; 13(8): 573-582
Published online Aug 19, 2023. doi: 10.5498/wjp.v13.i8.573
Investigation of contemporary college students’ mental health status and construction of a risk prediction model
Xiao-Li Mao, Hong-Mei Chen
Xiao-Li Mao, Hong-Mei Chen, School of Health and Nursing, Wuchang University of Technology, Wuhan 430223, Hubei Province, China
Author contributions: Mao XL designed and performed the research and wrote the paper; Chen HM designed the research and contributed to the analysis.
Supported by Hubei Province Education Science Planning Project, No. 2020GB132.
Institutional review board statement: The study procedures were approved by the Ethics Committee of the School of Health and Nursing, Wuchang University of Technology (No. 20234002).
Informed consent statement: All participants signed an informed consent form.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: The data used in this study can be obtained from the corresponding author upon request.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Xiao-Li Mao, MBBS, Associate Professor, School of Health and Nursing, Wuchang University of Technology, No. 16 Jiangxia Avenue, Wuhan 430223, Hubei Province, China. maoxiaoli1973@163.com
Received: June 14, 2023
Peer-review started: June 14, 2023
First decision: July 3, 2023
Revised: July 6, 2023
Accepted: July 14, 2023
Article in press: July 14, 2023
Published online: August 19, 2023

Due to academic pressure, social relations, and the change of adapting to independent life, college students are under high levels of pressure. Therefore, it is very important to study the mental health problems of college students. Developing a predictive model that can detect early warning signals of college students’ mental health risks can help support early intervention and improve overall well-being.


To investigate college students’ present psychological well-being, identify the contributing factors to its decline, and construct a predictive nomogram model.


We analyzed the psychological health status of 40874 university students in selected universities in Hubei Province, China from March 1 to 15, 2022, using online questionnaires and random sampling. Factors influencing their mental health were also analyzed using the logistic regression approach, and R4.2.3 software was employed to develop a nomogram model for risk prediction.


We randomly selected 918 valid data and found that 11.3% of college students had psychological problems. The results of the general data survey showed that the mental health problems of doctoral students were more prominent than those of junior college students, and the mental health of students from rural areas was more likely to be abnormal than that of urban students. In addition, students who had experienced significant life events and divorced parents were more likely to have an abnormal status. The abnormal group exhibited significantly higher Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 scores than the healthy group, with these differences being statistically significant (P < 0.05). The nomogram prediction model drawn by multivariate analysis included six predictors: The place of origin, whether they were single children, whether there were significant life events, parents’ marital status, regular exercise, intimate friends, and the PHQ-9 score. The training set demonstrated an area under the receiver operating characteristic (ROC) curve (AUC) of 0.972 [95% confidence interval (CI): 0.947-0.997], a specificity of 0.888 and a sensitivity of 0.972. Similarly, the validation set had a ROC AUC of 0.979 (95%CI: 0.955-1.000), with a specificity of 0.942 and a sensitivity of 0.939. The H-L deviation test result was χ2 = 32.476, P = 0.000007, suggesting that the model calibration was good.


In this study, nearly 11.3% of contemporary college students had psychological problems, the risk factors include students from rural areas, divorced parents, non-single children, infrequent exercise, and significant life events.

Keywords: College, Predictive models, Psychological health, Risk factors, Logistic regression analysis, Influencing factors

Core Tip: Mental health problems in college students have a marked impact on their physical and mental health, and learning capacity, and are also one of the key issues of concern to educators and society. This study analyzed the mental health status of 40874 college students in selected colleges and universities in Hubei Province, China. A logistic regression model was used to explore the factors affecting the mental health of college students. A risk prediction nomogram model was constructed by R software, which improved the visualization and comprehensibility of the research.