Latent class analysis of depression and anxiety among medical students during COVID-19 epidemic

作者：Zhuang Liu, Rongxun Liu, Yue Zhang, Ran Zhang, Lijuan Liang, Yang Wang, Yange Wei, Rongxin Zhu, Fei Wang · 发表于：BMC Psychiatry · 年份：2021 · DOI：10.1186/s12888-021-03459-w · 被引用次数：45 · 研究领域：COVID-19 and Mental Health、Healthcare professionals’ stress and burnout、Mental Health Treatment and Access

OBJECTIVE: The novel coronavirus disease 2019 (COVID-19) is a global public health emergency that has caused worldwide concern. The mental health of medical students under the COVID-19 epidemic has attracted much attention. This study aims to identify subgroups of medical students based on depression and anxiety and explore the influencing factors during the COVID-19 epidemic in China. METHODS: A total of 29,663 medical students were recruited during the epidemic of COVID-19 in China. Depression and anxiety symptoms were assessed using Patient Health Questionnaire 9 (PHQ9) and Generalized Anxiety Disorder 7 (GAD7) respectively. Latent class analysis was performed based on depression and anxiety symptoms in medical students. The latent class subtypes were compared using the chi-square test. Multinomial logistic regression was used to examine associations between identified classes and related factors. RESULTS: In this study, three distinct subgroups were identified, namely, the poor mental health group, the mild mental health group and the low symptoms group. The number of medical students in each class is 4325, 9321 and 16,017 respectively. The multinomial logistic regression results showed that compared with the low symptoms group, the factors influencing depression and anxiety in the poor mental health group and mild mental health group were sex, educational level, drinking, individual psychiatric disorders, family psychiatric disorders, knowledge of COVID-19, fear of being...