Open AccessZoom fatigue and its risk factors in online learning during the COVID-19 pandemic
Author(s) -
Jonathan Salim,
Sutiono Tandy,
Jannatin Nisa Arnindita,
Jacobus Jeno Wibisono,
Moses Rizky Haryanto,
Maria Georgina Wibisono
Publication year - 2022
Publication title -
medical journal of indonesia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.164
H-Index - 9
eISSN - 2252-8083
pISSN - 0853-1773
DOI - 10.13181/mji.oa.225703
Subject(s) - pandemic , videoconferencing , anxiety , scale (ratio) , medicine , zoom , depression (economics) , psychology , covid-19 , multimedia , psychiatry , disease , computer science , geography , cartography , infectious disease (medical specialty) , economics , macroeconomics , engineering , petroleum engineering , lens (geology)
BACKGROUND Global nations have enforced strict health protocols because of the COVID-19’s high transmission, infectivity, and mortality. As shown by increased online learning and video conferencing, the employment and education sectors are shifting to home-based activities. Video conferencing as a communication medium has subtly led to zoom fatigue. This study aimed to analyze the risk factors of zoom fatigue for early prevention and treatment.
METHODS This cross-sectional study was conducted on 335 Indonesian university students selected by purposive sampling in July 2021. Data were collected using a demographic questionnaire including online courses duration during the COVID-19 pandemic; Pittsburgh sleep quality index; depression, anxiety and stress scale-21; and zoom & exhaustion fatigue (ZEF) scale through Google Form (Google LLC, USA) distributed via social media and student forums. Association and correlation tests were used, and the model was developed using linear regression.
RESULTS The respondents were aged 21.3 (1.8) years with 12.8 (5.1) months of online courses during the COVID-19 pandemic and a ZEF scale of 2.8 (0.9). Students with higher ZEF had irregular physical exercise, poorer sleep quality, longer video conferencing sessions, longer months of courses during the COVID-19 pandemic, and higher mental illness (i.e., stress, anxiety, and depression). Smoking negatively correlated with fatigue (r = −0.12). The model for ZEF showed good predictability for zoom fatigue (p<0.001, R2 = 0.57).
CONCLUSIONS Daily exposure to video conferencing in educational settings throughout the pandemic has drastically increased zoom fatigue. The stakeholders must act immediately to minimize the risks while providing maximum benefits.