Published online Aug 19, 2023. doi: 10.5498/wjp.v13.i8.573
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
Processing time: 63 Days and 22.9 Hours
Mental health problems in college students have become the focus of academic and social attention. The main reason is that college students are facing many pressures and challenges, such as academic pressure, social pressure, career planning pressure, and so on. In addition, the rapid development of modern society and the competitive environment have also brought new challenges and threats to the mental health of college students. Therefore, the study of college students’ mental health has profound practical significance and theoretical value.
With the increasing pressure and challenges faced by college students, their mental health problems are becoming more and more serious, and the detection rate is increasing yearly.
Research on the mental health status of current college students and the construction of a risk prediction model can not only help us to understand the mental health problems faced by college students more comprehensively, but also provide a valuable reference for prevention strategies. It can also identify and intervene in mental health problems at an earlier time point to avoid further deterioration of the problem. In addition, future research in this field can also explore the relationship between mental health status and college students’ learning, life, and interpersonal communication, and provide useful support for improving the overall quality and development of college students.
The objective of the current research was to examine the mental well-being of 40874 undergraduate and graduate students enrolled in various higher education institutions within a particular geographical area. Additionally, using logistic regression analysis, the determinants that exert a substantial influence on the psychological health of university students were investigated. This model has high accuracy and interpretability. This study used R software to construct a risk prediction nomogram model, which enabled researchers to understand the influence and relationship of different variables more intuitively and improved the visualization and comprehensibility of the research. In summary, this study adopted a variety of advanced research methods, which had a wide range of reference values and application prospects.
The survey found that 11.3% of college students had psychological problems. The risk factors for college students’ mental health include being from rural areas, non-single children, major life events, parents’ marital divorce, infrequent exercise, and no close friends. The area under the receiver operating characteristic (ROC) curve in the training set was 0.972, the specificity was 0.888, and the sensitivity was 0.972. The area under the ROC curve in the validation set was 0.979, the specificity was 0.942, and the sensitivity was 0.939. These findings reflect the current mental health status of college students and is of great significance for the public to raise attention and awareness of mental health problems. It provides a basis for the government and schools to formulate mental health policies and help to formulate effective mental health management measures. At present, there are still some problems in the design and application of college students’ mental health questionnaires, as some students could not understand or answer the questions in the questionnaire. More comprehensive and in-depth analysis and research are still needed to ensure the accuracy and reliability of the analysis and statistical results.
From this research, we conclude that the current mental health status of college students is good. New methods used in this study include the use of a logistic regression model and the use of R software to construct a risk prediction nomogram model to explore the related factors affecting the mental health of college students. These methods can predict the risk factors related to college students’ mental health more accurately and provide more effective intervention measures and prevention methods.
Assessing and monitoring the mental health of college students can help schools and other institutions to better understand the needs of college students and take timely measures to prevent the emergence of mental health problems. Future research should focus on developing more effective assessment tools and establishing tracking and monitoring systems.