Anxiety and depressive symptoms in college students during the late stage of the COVID-19 outbreak: a network approach

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作者
Wei Bai
Hong Cai
Shou Liu
Xu Chen
Sha Sha
Teris Cheung
Jessie Jingxia Lin
Xiling Cui
Chee H. Ng
Yu-Tao Xiang
机构
[1] University of Macau,Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health Sciences
[2] University of Macau,Centre for Cognitive and Brain Sciences
[3] Institute of Advanced Studies in Humanities and Social Sciences,Department of Public Health
[4] University of Macau,Department of Rehabilitation Sciences, & Mental Health Research Centre
[5] Medical College,Department of Business Administration
[6] Qinghai University,Department of Psychiatry
[7] The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders,undefined
[8] Beijing Anding Hospital & the Advanced Innovation Center for Human Brain Protection,undefined
[9] Capital Medical University,undefined
[10] School of Nursing,undefined
[11] Hong Kong Polytechnic University,undefined
[12] Hong Kong Polytechnic University,undefined
[13] Hong Kong Shue Yan University,undefined
[14] The Melbourne Clinic and St Vincent’s Hospital,undefined
[15] University of Melbourne,undefined
[16] Richmond,undefined
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摘要
Mental health problems are common in college students even in the late stage of the coronavirus disease 2019 (COVID-19) outbreak. Network analysis is a novel approach to explore interactions of mental disorders at the symptom level. The aim of this study was to elucidate characteristics of depressive and anxiety symptoms network in college students in the late stage of the COVID-19 outbreak. A total of 3062 college students were included. The seven-item Generalized Anxiety Disorder Scale (GAD-7) and nine-item Patient Health Questionnaire (PHQ-9) were used to measure anxiety and depressive symptoms, respectively. Central symptoms and bridge symptoms were identified based on centrality and bridge centrality indices, respectively. Network stability was examined using the case-dropping procedure. The strongest direct relation was between anxiety symptoms “Nervousness” and “Uncontrollable worry”. “Fatigue” has the highest node strength in the anxiety and depression network, followed by “Excessive worry”, “Trouble relaxing”, and “Uncontrollable worry”. “Motor” showed the highest bridge strength, followed by “Feeling afraid” and “Restlessness”. The whole network was robust in both stability and accuracy tests. Central symptoms “Fatigue”, “Excessive worry”, “Trouble relaxing” and “Uncontrollable worry”, and critical bridge symptoms “Motor”, “Feeling afraid” and “Restlessness” were highlighted in this study. Targeting interventions to these symptoms may be important to effectively alleviate the overall level of anxiety and depressive symptoms in college students.
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