The COVID-19 pandemic raised many challenges for university staff and students, including the need to work from home, which resulted in a greater reliance on technology. We collected questionnaire data from university students (N = 894) in three European countries: Greece, Italy, and the United Kingdom. Data were collected between 7th April 2020 and 19th June 2020, representing a period covering the first lockdown and university closures in these countries and across Europe generally. We tested the hypotheses that technology-related stressors (techno-overload, work-home conflict, techno-ease, techno-reliability, techno-sociality, and pace of change) would be associated with anxiety and depressive symptoms, and that coping styles (problem-focused, emotion-focused, and avoidance) would mediate these relationships. Results showed significant positive associations between techno-overload, work-home conflict and anxiety and depressive symptoms, and significant negative associations between techno-reliability, techno-ease and anxiety and depressive symptoms. A significant negative association was found between techno-sociality and depressive symptoms but not anxiety symptoms. No evidence was found for an association between pace of change and anxiety or depressive symptoms. Multiple mediation analyses revealed significant direct effects of techno-overload, work-home conflict and techno-ease on anxiety symptoms, and of work-home conflict and techno-ease on depressive symptoms. Work-home conflict had significant indirect effects on anxiety and depressive symptoms through avoidance coping. Techno-overload and techno-ease both had significant indirect effects on anxiety symptoms through problem- and emotion-focused coping. Techno-ease also had a significant indirect effect on depressive symptoms through problem-focused coping. The findings add to the body of evidence on technostress amongst university students and provide knowledge on how technostress translates through coping strategies into anxious and depressive symptoms during the disruption caused by the outbreak of a pandemic disease.

Approximately 20% of the working population report symptoms of feeling fatigued at work. The aim of the study was to investigate whether an alternative mobile version of the 'gold standard' Psychomotor Vigilance Task (PVT) could be used to provide an objective indicator of fatigue in staff working in applied safety critical settings such as train driving, hospital staffs, emergency services, law enforcements, etc., using different mobile devices. 26 participants mean age 20 years completed a 25-minute reaction time study using an alternative mobile version of the Psychomotor Vigilance Task (m-PVT) that was implemented on either an Apple iPhone 6s Plus or a Samsung Galaxy Tab 4. Participants attended two sessions: a morning and an afternoon session held on two consecutive days counterbalanced. It was found that the iPhone 6s Plus generated both mean speed responses (1/RTs) and mean reaction times (RTs) that were comparable to those observed in the literature while the Galaxy Tab 4 generated significantly lower 1/RTs and slower RTs than those found with the iPhone 6s Plus. Furthermore, it was also found that the iPhone 6s Plus was sensitive enough to detect lower mean speed of responses (1/RTs) and significantly slower mean reaction times (RTs) after 10-minutes on the m-PVT. In contrast, it was also found that the Galaxy Tab 4 generated mean number of lapses that were significant after 5-minutes on the m-PVT. These findings seem to indicate that the m-PVT could be used to provide an objective indicator of fatigue in staff working in applied safety critical settings such as train driving, hospital staffs, emergency services, law enforcements, etc.

Cronbach’s alpha (α) is the most widely used statistic denoting a scale’s internal reliability. Higher internal reliability is associated with greater confidence in the scale and the associated conclusions made from the results. Cronbach’s alpha is often used without consideration of the factors which may mediate coefficient statistics. The current report provides suggestions for future authors to improve their understanding of, inferences made from, and writing about Cronbach’s alpha.