The Longitudinal Features of Depressive Symptoms During the COVID-19 Pandemic Among Chinese College Students: A Network Perspective.

Publisher: Kluwer Academic/Plenum Publishers Country of Publication: United States NLM ID: 0333507 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-6601 (Electronic) Linking ISSN: 00472891 NLM ISO Abbreviation: J Youth Adolesc Subsets: MEDLINE

Publication: 1999- : New York, NY : Kluwer Academic/Plenum Publishers
Original Publication: New York, Plenum Press.

Depression*/epidemiology ; Depression*/diagnosis ; COVID-19*/epidemiology; Humans ; Female ; Young Adult ; Adult ; Infant ; Male ; Pandemics ; Longitudinal Studies ; Students ; Fatigue/etiology ; Fatigue/epidemiology

There is substantial evidence that the Corona Virus Disease 2019 (COVID-19) pandemic increased the risk of depressive symptoms among college students, but the long-term features of depressive symptoms on a symptom level have been poorly described. The current study investigated interaction patterns between depressive symptoms via network analysis. In this longitudinal study, participants included 860 Chinese college students (65.8% female; M age  = 20.6, SD age  = 1.8, range: 17-27) who completed a questionnaire at three-time points three months apart. Results demonstrated that fatigue was the most influential symptom, and the occurrence of fatigue could give rise to other depressive symptoms. In addition to predicting other symptoms, fatigue could be predicted by other symptoms in the measurement. The network structures were similar across time, suggesting that the overall interaction pattern of depressive symptoms was stable over the longitudinal course. These findings suggest that depressive symptoms during the COVID-19 period are associated with the presence of fatigue.
(© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

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2021A1515011330 Natural Science Foundation of Guangdong Province; cgpy21001 Shenzhen Education Science Planning Project

Keywords: COVID-19; College students; Depressive symptoms; Network analysis

Date Created: 20230612 Date Completed: 20230728 Latest Revision: 20230728

20231215

10.1007/s10964-023-01802-w

37306836