Technostress Creators and Outcomes Among Egyptian Medical Staff and Students: A Multicenter Cross-Sectional Study of Remote Working Environment During COVID-19 Pandemic - Kasemy, Zeinab A.; Sharif, Asmaa F.; Barakat, Ayah M.; Abdelmohsen, Shaimaa R.; Hassan, Nancy H.; Hegazy, Nagwa N.; Sharfeldin, Asmaa Y.; El-Ma'doul, Angham S.; Alsawy, Kholoud Adel; Abo Shereda, Hanaa M.; Abdelwanees, Sally (Frontiers in Public Health, 2022)
Objectives: This study aimed to investigate the technostress creators and outcomes among university medical and nursing faculties and students as direct effects of remote working environment during COVID-19 pandemic. Background: Due the current COVID-19 pandemic, shifting to virtual learning that implies utilizing the Information and Communication Technologies (ICTs) is urgent. Technostress is a problem commonly arising in virtual working environment and it occurs due to misfitting and maladaptation between the individual and the changeable requirements of ICTs is called technostress. Methods: A multicenter cross-sectional study was conducted in medicine and nursing colleges of 5 Egyptian universities and included both staff members and students. The data were collected through personal interviews, from January to May 2021. All participants took a four-part questionnaire that asked about personal and demographic data, technostress creators, job or study and technology characteristics and technostress outcomes (burnout, strain and work engagement). Furthermore, participants’ blood Cortisol and Co-enzyme Q10 (CoQ10) level were tested in a random sample of the students. Results: A total of 3582 respondents participated in the study, 1056 staff members and 2526 students where 33.3% of the staff members and 7.6% of students reported high technostress. Among staff members, total technostress score significantly predicted Cortisol level (β= 2.98, CI 95%: 0.13-5.83), CoQ10(β= -6.54, CI 95%: [(-8.52)-(-4.56), strain (β= 1.20, CI 95%: 0.93-1.47), burnout (β= 0.73, CI 95%: 0.48-0.97) and engagement (β=-0.44, CI 95%: [(-0.77)-(-0.11)]) whereas among students, total technostress score significantly predicted Cortisol level (β= 6.64, CI 95%: 2.78-10.49),strain (β= 1.25, CI 95%: 0.72-1.77) and burnout (β= 0.70, CI 95%: 0.37-1.04). Among staff members and students, technology characteristics were significantly positive predictor to technostress while job characteristics were significantly negative predictor to technostress. Conclusion: Egyptian medical staff members and students reported moderate to high technostress which was associated with high burnout, strain, and cortisol level; moreover, high technostress was associated with low work engagement and low CoQ10 enzyme. The current study highlighted the need to establish psychological support programs for staff members and students during COVID-19 pandemic.