@article{ref1,
title="Mental health profiles and the related socio-demographic predictors in Hong Kong university students under the COVID-19 pandemic: a latent class analysis",
journal="Psychiatry research",
year="2023",
author="Chai, Wenyu and Shek, Daniel T. L.",
volume="331",
number="",
pages="e115666-e115666",
abstract="While the COVID-19 pandemic has brought about significant challenges to mental health of university students, there is limited research in this area. Particularly, few studies examined the person-centered mental health symptom profiles such as depression and anxiety and the related socio-demographic predictors. Using Latent Class Analysis (LCA), this study investigated the symptom profiles of depression and anxiety in university students in Hong Kong under the COVID-19 pandemic and the socio-demographic predictors. A total of 978 undergraduate students completed an online questionnaire including socio-demographic factors and measures of depression and anxiety during the summer of 2022. The LCA identified three latent classes: &quot;normal&quot; group, &quot;moderate comorbid depression and anxiety&quot; group and &quot;severe comorbid depression and anxiety&quot; group. Multinominal logistic regression showed that comparing with the &quot;normal&quot; group and the &quot;moderate symptom&quot; group, the &quot;severe symptom&quot; group had higher personal financial difficulties and individual/family member unemployment during the pandemic. In contrast, other socio-demographic factors (age, gender, year of study, living status, and COVID-19 infection status) had no significant association with group status. The study contributes to understanding of person-centered depression and anxiety symptom profiles and the risk role of personal financial difficulty in mental health of university students under the pandemic.<p /> <p>Language: en</p>",
language="en",
issn="0165-1781",
doi="10.1016/j.psychres.2023.115666",
url="http://dx.doi.org/10.1016/j.psychres.2023.115666"
}