The Patterns and Predictors of Loneliness for the Chinese Medical Students Since Post-Lockdown to New Normal With COVID-19

Background: The coronavirus disease 2019 (COVID-19)-related quarantine has had unique psychological challenges for medical students, particularly loneliness. In this study, we demonstrated the patterns and predictors of loneliness in medical students since post-lockdown to new normal with COVID-19.M...

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Main Authors: Hui Zhang, Jun Yang, Yuxin Li, Gaoyue Ren, Lina Mu, Yunjiang Cai, Qiusha Luo, Yuqiu Zhou
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-07-01
Series:Frontiers in Public Health
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2021.679178/full
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spelling doaj-b78382ba9b41495cb42fe7e625a30d4c2021-07-01T14:33:50ZengFrontiers Media S.A.Frontiers in Public Health2296-25652021-07-01910.3389/fpubh.2021.679178679178The Patterns and Predictors of Loneliness for the Chinese Medical Students Since Post-Lockdown to New Normal With COVID-19Hui ZhangJun YangYuxin LiGaoyue RenLina MuYunjiang CaiQiusha LuoYuqiu ZhouBackground: The coronavirus disease 2019 (COVID-19)-related quarantine has had unique psychological challenges for medical students, particularly loneliness. In this study, we demonstrated the patterns and predictors of loneliness in medical students since post-lockdown to new normal with COVID-19.Methods: A convenience sampling method was used in this study. Face-to-face online questionnaires of UCLA Loneliness Scale and psychological characteristics scales were completed by 1,478 participants. Latent profile analysis and multinominal logistic regressions were performed.Results: Three latent profile models were identified in this study: low loneliness (52.3%), interpersonal sensitivity loneliness (3.5%), and high loneliness (44.1%). Sophomore (Est = 1.937; p < 0.05) and junior students (Est = 2.939; p < 0.05), neuroticism (Est = 2.475; p < 0.05), high arousal symptoms (Est = 2.618; p < 0.01), and the quality of support from friends (Est = 2.264; p < 0.05) were the risk factors for high loneliness profile. In addition, sophomore (Est = 2.065; p < 0.05) and junior students (Est = 2.702; p < 0.01), openness (Est = 2.303; p < 0.05), and conscientiousness personality (Est = −2.348; p < 0.05) were the predictors of an interpersonal sensitive loneliness profile. Good peer relationship (Est = −2.266; p < 0.05) and other support (Est = −2.247; p < 0.05) were protective factors for low loneliness profile.Limitations: Participants were selected from one medical university; the generalizability is limited.Conclusions: Timely loneliness-focused interventions should be targeted on the different profiles and predictors of loneliness in medical students.https://www.frontiersin.org/articles/10.3389/fpubh.2021.679178/fulllonelinesspatternspredictorsmedical studentsCOVID-19latent profile analysis
collection DOAJ
language English
format Article
sources DOAJ
author Hui Zhang
Jun Yang
Yuxin Li
Gaoyue Ren
Lina Mu
Yunjiang Cai
Qiusha Luo
Yuqiu Zhou
spellingShingle Hui Zhang
Jun Yang
Yuxin Li
Gaoyue Ren
Lina Mu
Yunjiang Cai
Qiusha Luo
Yuqiu Zhou
The Patterns and Predictors of Loneliness for the Chinese Medical Students Since Post-Lockdown to New Normal With COVID-19
Frontiers in Public Health
loneliness
patterns
predictors
medical students
COVID-19
latent profile analysis
author_facet Hui Zhang
Jun Yang
Yuxin Li
Gaoyue Ren
Lina Mu
Yunjiang Cai
Qiusha Luo
Yuqiu Zhou
author_sort Hui Zhang
title The Patterns and Predictors of Loneliness for the Chinese Medical Students Since Post-Lockdown to New Normal With COVID-19
title_short The Patterns and Predictors of Loneliness for the Chinese Medical Students Since Post-Lockdown to New Normal With COVID-19
title_full The Patterns and Predictors of Loneliness for the Chinese Medical Students Since Post-Lockdown to New Normal With COVID-19
title_fullStr The Patterns and Predictors of Loneliness for the Chinese Medical Students Since Post-Lockdown to New Normal With COVID-19
title_full_unstemmed The Patterns and Predictors of Loneliness for the Chinese Medical Students Since Post-Lockdown to New Normal With COVID-19
title_sort patterns and predictors of loneliness for the chinese medical students since post-lockdown to new normal with covid-19
publisher Frontiers Media S.A.
series Frontiers in Public Health
issn 2296-2565
publishDate 2021-07-01
description Background: The coronavirus disease 2019 (COVID-19)-related quarantine has had unique psychological challenges for medical students, particularly loneliness. In this study, we demonstrated the patterns and predictors of loneliness in medical students since post-lockdown to new normal with COVID-19.Methods: A convenience sampling method was used in this study. Face-to-face online questionnaires of UCLA Loneliness Scale and psychological characteristics scales were completed by 1,478 participants. Latent profile analysis and multinominal logistic regressions were performed.Results: Three latent profile models were identified in this study: low loneliness (52.3%), interpersonal sensitivity loneliness (3.5%), and high loneliness (44.1%). Sophomore (Est = 1.937; p < 0.05) and junior students (Est = 2.939; p < 0.05), neuroticism (Est = 2.475; p < 0.05), high arousal symptoms (Est = 2.618; p < 0.01), and the quality of support from friends (Est = 2.264; p < 0.05) were the risk factors for high loneliness profile. In addition, sophomore (Est = 2.065; p < 0.05) and junior students (Est = 2.702; p < 0.01), openness (Est = 2.303; p < 0.05), and conscientiousness personality (Est = −2.348; p < 0.05) were the predictors of an interpersonal sensitive loneliness profile. Good peer relationship (Est = −2.266; p < 0.05) and other support (Est = −2.247; p < 0.05) were protective factors for low loneliness profile.Limitations: Participants were selected from one medical university; the generalizability is limited.Conclusions: Timely loneliness-focused interventions should be targeted on the different profiles and predictors of loneliness in medical students.
topic loneliness
patterns
predictors
medical students
COVID-19
latent profile analysis
url https://www.frontiersin.org/articles/10.3389/fpubh.2021.679178/full
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