ArticleF1000Research2024
Zoom fatigue related to online learning among medical students in Thailand: Prevalence, predictors, and association with depression.
Article in F1000Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Rethinking Basic Science Teaching in Medical Education: A Viewpoint on Its Past, Present, and Future.Interactive journal of medical research · 2026Article
- Interplay of academic stress, digital fatigue, and loneliness in predicting university students' mental health in the post-COVID era.Discover mental health · 2026Article
- Digital Solutions in HF Education: What Can Patients and Clinicians Gain?Current heart failure reports · 2026Review
- Digital governance pressure and digital burnout among grassroots public sector employees: the mediating roles of cognitive load and negative affect.Frontiers in psychology · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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