ArticleEducation and information technologies2022
Factors predicting videoconferencing fatigue among higher education faculty.
Article in Education and information technologies, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 47 citations in OpenAlex.
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- Health and occupational environment of Japanese expatriates in the United States: medical interview analysis using text mining.Journal of occupational health · 2026Article
- A cross-sectional survey of videoconferencing fatigue and its influencing factors during COVID-19 in the Chinese population.Scientific reports · 2025Article
- Describing Zoom exhaustion and fatigue in nursing students at a university in South Africa.Health SA = SA Gesondheid · 2024Article
- Too much to process? Exploring the relationships between communication and information overload and videoconference fatigue.PloS one · 2024Article
- Zoom fatigue related to online learning among medical students in Thailand: Prevalence, predictors, and association with depression.F1000Research · 2024Article
- E-learning readiness among dental students and faculty: a comparative study before and after the COVID-19 pandemic.Frontiers in medicine · 2024Article
- Hardiness and Zoom Fatigue on Nursing Students: A Cross-Sectional Study in Indonesia During Online Learning.Advances in medical education and practice · 2023Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The online remote learning revolution in the era of the pandemic has resulted in the massive explosion of videoconferencing technologies. The emergence of a new phenomenon of exhaustion and fatigue experienced during virtual meetings is evident. This study examined the predictors of videoconferencing fatigue among higher education faculty in the Philippines. A total of 322 faculty participated in this cross-sectional study. The online survey was administered using the Zoom Exhaustion and Fatigue scale as the primary data collection tool. Significant predictors of videoconferencing fatigue were identified using the multiple linear regression analysis. The results indicated that the videoconference fatigue composite score of the faculty was 3.35 out of 5 suggesting a moderate level of fatigue. Significant predictors of videoconferencing fatigue among higher education faculty include attitude, sense of being physically trapped, mirror anxiety, emotional stability domain of personality, interval between videoconferences, and duration of videoconferences. For better videoconferencing experience among faculty, mechanisms to ease fatigue during virtual meetings may be proposed based on the study result.
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