{"title":"Zoom fatigue related to online learning among medical students in Thailand: Prevalence, predictors, and association with depression.","authors":"Veevarin Charoenporn, Sirashat Hanvivattanakul, Kanathip Jongmekwamsuk, Rinradee Lenavat, Korravit Hanvivattanakul, Thammanard Charernboon","doi":"10.12688/f1000research.146084.2","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Amidst the COVID-19 pandemic, the learning pattern of medical students shifted from onsite to online. This transition may contribute to what has been called \"Zoom fatigue.\" This study aimed to evaluate the prevalence of Zoom fatigue related to online learning, identify associated factors of Zoom fatigue, and explore its correlation with depression among medical students during the COVID-19 pandemic.</p><p><strong>Methods: </strong>This cross-sectional study was conducted among 1st to 6th-year Thai medical students. The online survey was administered using a demographic and health behavior questionnaire, the Patient Health Questionnaire-9 (PHQ-9), and the Thai version of the Zoom Exhaustion & Fatigue Scale (ZEF-T).</p><p><strong>Results: </strong>Among the 386 participating students, 221 (57%) were female, with a mean age of 20.6 years. The prevalence of high Zoom fatigue was 9.6%. In the multivariable regression analysis, a lower academic year and a higher number of online learning sessions were significant predictors of Zoom fatigue (p < 0.001), while regular exercise emerged as a protective factor (p = 0.009). The prevalence of depressive disorder was 61.9%, and a significant correlation was found between having a depressive disorder and experiencing Zoom fatigue (p = 0.004).</p><p><strong>Conclusion: </strong>Zoom fatigue among medical students was correlated with depression. Consequently, medical students experiencing Zoom fatigue should undergo further assessment for depression. It is crucial to closely monitor medical students in lower academic years with a high number of online sessions for signs of Zoom fatigue. Additionally, implementing strategies, such as reducing the frequency of online sessions and promoting regular exercise, may help alleviate the symptoms.</p>","PeriodicalId":12260,"journal":{"name":"F1000Research","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11364962/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"F1000Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12688/f1000research.146084.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"Pharmacology, Toxicology and Pharmaceutics","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Amidst the COVID-19 pandemic, the learning pattern of medical students shifted from onsite to online. This transition may contribute to what has been called "Zoom fatigue." This study aimed to evaluate the prevalence of Zoom fatigue related to online learning, identify associated factors of Zoom fatigue, and explore its correlation with depression among medical students during the COVID-19 pandemic.
Methods: This cross-sectional study was conducted among 1st to 6th-year Thai medical students. The online survey was administered using a demographic and health behavior questionnaire, the Patient Health Questionnaire-9 (PHQ-9), and the Thai version of the Zoom Exhaustion & Fatigue Scale (ZEF-T).
Results: Among the 386 participating students, 221 (57%) were female, with a mean age of 20.6 years. The prevalence of high Zoom fatigue was 9.6%. In the multivariable regression analysis, a lower academic year and a higher number of online learning sessions were significant predictors of Zoom fatigue (p < 0.001), while regular exercise emerged as a protective factor (p = 0.009). The prevalence of depressive disorder was 61.9%, and a significant correlation was found between having a depressive disorder and experiencing Zoom fatigue (p = 0.004).
Conclusion: Zoom fatigue among medical students was correlated with depression. Consequently, medical students experiencing Zoom fatigue should undergo further assessment for depression. It is crucial to closely monitor medical students in lower academic years with a high number of online sessions for signs of Zoom fatigue. Additionally, implementing strategies, such as reducing the frequency of online sessions and promoting regular exercise, may help alleviate the symptoms.
F1000ResearchPharmacology, Toxicology and Pharmaceutics-Pharmacology, Toxicology and Pharmaceutics (all)
CiteScore
5.00
自引率
0.00%
发文量
1646
审稿时长
1 weeks
期刊介绍：
F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities. F1000Research is a scholarly publication platform set up for the scientific, scholarly and medical research community; each article has at least one author who is a qualified researcher, scholar or clinician actively working in their speciality and who has made a key contribution to the article. Articles must be original (not duplications). All research is suitable irrespective of the perceived level of interest or novelty; we welcome confirmatory and negative results, as well as null studies. F1000Research publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others. Reviews and Opinion articles providing a balanced and comprehensive overview of the latest discoveries in a particular field, or presenting a personal perspective on recent developments, are also welcome. See the full list of article types we accept for more information.
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