Psychological Impact of COVID-19 on College Students After School Reopening: A Cross-Sectional Study Based on Machine Learning
COVID-19, the most severe public health problem to occur in the past 10 years, has greatly impacted people's mental health. Colleges in China have reopened, and how to prevent college students from suffering secondary damage due to school reopening remains elusive. This cross-sectional study wa...
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doaj-e9e09c006b9d4af0b61a64290603594f2021-04-29T05:05:45ZengFrontiers Media S.A.Frontiers in Psychology1664-10782021-04-011210.3389/fpsyg.2021.641806641806Psychological Impact of COVID-19 on College Students After School Reopening: A Cross-Sectional Study Based on Machine LearningZiyuan Ren0Yaodong Xin1Junpeng Ge2Zheng Zhao3Dexiang Liu4Roger C. M. Ho5Cyrus S. H. Ho6Department of Medical Psychology and Ethics, School of Basic Medicine Sciences, Cheeloo College of Medicine, Shandong University, Jinan, ChinaSchool of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, ChinaSchool of Biology Engineering, Shandong Jianzhu University, Jinan, ChinaDepartment of Medical Psychology and Ethics, School of Basic Medicine Sciences, Cheeloo College of Medicine, Shandong University, Jinan, ChinaDepartment of Medical Psychology and Ethics, School of Basic Medicine Sciences, Cheeloo College of Medicine, Shandong University, Jinan, ChinaDepartment of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, SingaporeDepartment of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, SingaporeCOVID-19, the most severe public health problem to occur in the past 10 years, has greatly impacted people's mental health. Colleges in China have reopened, and how to prevent college students from suffering secondary damage due to school reopening remains elusive. This cross-sectional study was aimed to evaluate the psychological impact of COVID-19 after school reopening and explore via machine learning the factors that influence anxiety and depression among students. Among the 478 valid online questionnaires collected between September 14th and September 20th, 74 (15.5%) showed symptoms of anxiety (by the Self-Rating Anxiety Scale), and 155 (32.4%) showed symptoms of depression (by Patient Health Questionnaire-9). Descriptive analysis of basic personal characteristics indicated that students at a higher grade, having relatives or friends who have been infected, fearing being infected, and having a pessimistic attitude to COVID-19 easily experience anxiety or depression. The Synthetic Minority Oversampling Technique (SMOTE) was utilized to counteract the imbalance of retrieved data. The Akaike Information Criterion (AIC) and multivariate logistic regression were performed to explore significant influence factors. The results indicate that exercise frequency, alcohol use, school reopening, having relatives or friends who have been infected, self-quarantine, quarantine of classmates, taking temperature routinely, wearing masks routinely, sleep quality, retaining holiday, availability of package delivery, take-out availability, lockdown restriction, several areas in school closed due to COVID-19, living conditions in the school, taking the final examinations after school reopening, and the degree to which family economic status is influenced by COVID-19 are the primary influence factors for anxiety or depression. To evaluate the effect of our model, we used 5-fold cross-validation, and the average area under the curve (AUC) values of the receiver operating characteristic (ROC) curves of anxiety and depression on the test set reached 0.885 and 0.806, respectively. To conclude, we examined the presence of anxiety and depression symptoms among Chinese college students after school reopening and explored many factors influencing students' mental health, providing reasonable school management suggestions.https://www.frontiersin.org/articles/10.3389/fpsyg.2021.641806/fullCOVID-19anxietydepressioncollege studentmachine learning |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ziyuan Ren Yaodong Xin Junpeng Ge Zheng Zhao Dexiang Liu Roger C. M. Ho Cyrus S. H. Ho |
spellingShingle |
Ziyuan Ren Yaodong Xin Junpeng Ge Zheng Zhao Dexiang Liu Roger C. M. Ho Cyrus S. H. Ho Psychological Impact of COVID-19 on College Students After School Reopening: A Cross-Sectional Study Based on Machine Learning Frontiers in Psychology COVID-19 anxiety depression college student machine learning |
author_facet |
Ziyuan Ren Yaodong Xin Junpeng Ge Zheng Zhao Dexiang Liu Roger C. M. Ho Cyrus S. H. Ho |
author_sort |
Ziyuan Ren |
title |
Psychological Impact of COVID-19 on College Students After School Reopening: A Cross-Sectional Study Based on Machine Learning |
title_short |
Psychological Impact of COVID-19 on College Students After School Reopening: A Cross-Sectional Study Based on Machine Learning |
title_full |
Psychological Impact of COVID-19 on College Students After School Reopening: A Cross-Sectional Study Based on Machine Learning |
title_fullStr |
Psychological Impact of COVID-19 on College Students After School Reopening: A Cross-Sectional Study Based on Machine Learning |
title_full_unstemmed |
Psychological Impact of COVID-19 on College Students After School Reopening: A Cross-Sectional Study Based on Machine Learning |
title_sort |
psychological impact of covid-19 on college students after school reopening: a cross-sectional study based on machine learning |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Psychology |
issn |
1664-1078 |
publishDate |
2021-04-01 |
description |
COVID-19, the most severe public health problem to occur in the past 10 years, has greatly impacted people's mental health. Colleges in China have reopened, and how to prevent college students from suffering secondary damage due to school reopening remains elusive. This cross-sectional study was aimed to evaluate the psychological impact of COVID-19 after school reopening and explore via machine learning the factors that influence anxiety and depression among students. Among the 478 valid online questionnaires collected between September 14th and September 20th, 74 (15.5%) showed symptoms of anxiety (by the Self-Rating Anxiety Scale), and 155 (32.4%) showed symptoms of depression (by Patient Health Questionnaire-9). Descriptive analysis of basic personal characteristics indicated that students at a higher grade, having relatives or friends who have been infected, fearing being infected, and having a pessimistic attitude to COVID-19 easily experience anxiety or depression. The Synthetic Minority Oversampling Technique (SMOTE) was utilized to counteract the imbalance of retrieved data. The Akaike Information Criterion (AIC) and multivariate logistic regression were performed to explore significant influence factors. The results indicate that exercise frequency, alcohol use, school reopening, having relatives or friends who have been infected, self-quarantine, quarantine of classmates, taking temperature routinely, wearing masks routinely, sleep quality, retaining holiday, availability of package delivery, take-out availability, lockdown restriction, several areas in school closed due to COVID-19, living conditions in the school, taking the final examinations after school reopening, and the degree to which family economic status is influenced by COVID-19 are the primary influence factors for anxiety or depression. To evaluate the effect of our model, we used 5-fold cross-validation, and the average area under the curve (AUC) values of the receiver operating characteristic (ROC) curves of anxiety and depression on the test set reached 0.885 and 0.806, respectively. To conclude, we examined the presence of anxiety and depression symptoms among Chinese college students after school reopening and explored many factors influencing students' mental health, providing reasonable school management suggestions. |
topic |
COVID-19 anxiety depression college student machine learning |
url |
https://www.frontiersin.org/articles/10.3389/fpsyg.2021.641806/full |
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