Cargando…

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

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 depressio...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Zhuang, Liu, Rongxun, Zhang, Yue, Zhang, Ran, Liang, Lijuan, Wang, Yang, Wei, Yange, Zhu, Rongxin, Wang, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8506472/
https://www.ncbi.nlm.nih.gov/pubmed/34641795
http://dx.doi.org/10.1186/s12888-021-03459-w
_version_ 1784581713388634112
author Liu, Zhuang
Liu, Rongxun
Zhang, Yue
Zhang, Ran
Liang, Lijuan
Wang, Yang
Wei, Yange
Zhu, Rongxin
Wang, Fei
author_facet Liu, Zhuang
Liu, Rongxun
Zhang, Yue
Zhang, Ran
Liang, Lijuan
Wang, Yang
Wei, Yange
Zhu, Rongxin
Wang, Fei
author_sort Liu, Zhuang
collection PubMed
description 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 infected, and participate in mental health education on COVID-19. CONCLUSIONS: Our findings suggested that latent class analysis can be used to categorize different medical students according to their depression and anxiety symptoms during the outbreak of COVID-19. The main factors influencing the poor mental health group and the mild mental health group are basic demographic characteristics, disease history, COVID-19 related factors and behavioural lifestyle. School administrative departments can carry out targeted psychological counseling according to different subgroups to promote the physical and mental health of medical students.
format Online
Article
Text
id pubmed-8506472
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-85064722021-10-12 Latent class analysis of depression and anxiety among medical students during COVID-19 epidemic Liu, Zhuang Liu, Rongxun Zhang, Yue Zhang, Ran Liang, Lijuan Wang, Yang Wei, Yange Zhu, Rongxin Wang, Fei BMC Psychiatry Research 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 infected, and participate in mental health education on COVID-19. CONCLUSIONS: Our findings suggested that latent class analysis can be used to categorize different medical students according to their depression and anxiety symptoms during the outbreak of COVID-19. The main factors influencing the poor mental health group and the mild mental health group are basic demographic characteristics, disease history, COVID-19 related factors and behavioural lifestyle. School administrative departments can carry out targeted psychological counseling according to different subgroups to promote the physical and mental health of medical students. BioMed Central 2021-10-12 /pmc/articles/PMC8506472/ /pubmed/34641795 http://dx.doi.org/10.1186/s12888-021-03459-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Liu, Zhuang
Liu, Rongxun
Zhang, Yue
Zhang, Ran
Liang, Lijuan
Wang, Yang
Wei, Yange
Zhu, Rongxin
Wang, Fei
Latent class analysis of depression and anxiety among medical students during COVID-19 epidemic
title Latent class analysis of depression and anxiety among medical students during COVID-19 epidemic
title_full Latent class analysis of depression and anxiety among medical students during COVID-19 epidemic
title_fullStr Latent class analysis of depression and anxiety among medical students during COVID-19 epidemic
title_full_unstemmed Latent class analysis of depression and anxiety among medical students during COVID-19 epidemic
title_short Latent class analysis of depression and anxiety among medical students during COVID-19 epidemic
title_sort latent class analysis of depression and anxiety among medical students during covid-19 epidemic
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8506472/
https://www.ncbi.nlm.nih.gov/pubmed/34641795
http://dx.doi.org/10.1186/s12888-021-03459-w
work_keys_str_mv AT liuzhuang latentclassanalysisofdepressionandanxietyamongmedicalstudentsduringcovid19epidemic
AT liurongxun latentclassanalysisofdepressionandanxietyamongmedicalstudentsduringcovid19epidemic
AT zhangyue latentclassanalysisofdepressionandanxietyamongmedicalstudentsduringcovid19epidemic
AT zhangran latentclassanalysisofdepressionandanxietyamongmedicalstudentsduringcovid19epidemic
AT lianglijuan latentclassanalysisofdepressionandanxietyamongmedicalstudentsduringcovid19epidemic
AT wangyang latentclassanalysisofdepressionandanxietyamongmedicalstudentsduringcovid19epidemic
AT weiyange latentclassanalysisofdepressionandanxietyamongmedicalstudentsduringcovid19epidemic
AT zhurongxin latentclassanalysisofdepressionandanxietyamongmedicalstudentsduringcovid19epidemic
AT wangfei latentclassanalysisofdepressionandanxietyamongmedicalstudentsduringcovid19epidemic