Covid-19 has caused a shift in the working environment, with people mandated to work from home where possible in the UK since March 2020. Cognitive workload is sensitive to environmental changes, so it’s possible that in moving from the office to working from home, people’s cognitive workload has been impacted. The research outlined presents findings from 11 interviews with office workers on whether their cognitive workload has been impacted due to changes in the working environment, consequence of Covid-19. Thematic analysis identified three themes that impact cognitive workload: The home environment, differing distractions and no longer having to commute. The paper finishes with a discussion of these themes in relation to cognitive workload and Covid-19 literature, as well as some recommendations on how employers should be flexible with employees to optimise workload.
This study evaluated the mental workload of military pilots during day and night conditions using night vision goggles (NVG) in a Flight Training Device, in order to rectify or ratify the fatigue correction factor used for flights using NVG. The experiment used basic military operational tasks measuring physiological data, specifically data on electrocardiography activity and galvanic skin response. Subjective data were gathered using NASA TLX and Psychomotor Vigilance Test methods. After collection, the data were subjected to treatment to correct possible errors during data acquisition and later analyzed in the domains of time and frequency. The analysis did not show a great change in mental workload between the day and night periods, which could be explained by the small sample, the small period between flights and the learning effect between day and night flight.
This study explored how students' main information problems during the information age, namely internet addiction, information overload, and social network addiction, influence holistic well-being and academic attainment. The participants were 226 university students, all UK based and regular internet users. They answered the Internet Addiction Test, Information Overload Scale, Bergen Social Media Addiction Scale, and the Wellbeing Process Questionnaire. Data were analysed with SPSS using correlation and linear regression analysis. The univariate analyses confirmed the negative impact of information overload, internet addiction and social media addiction on positive well-being but not academic attainment. However, multivariate analyses controlling for established predictors of well-being showed that the effects of information overload, internet addiction and social media addiction were largely non-significant, confirming other research using this analysis strategy. Future research should examine the type of internet use as well as the extent of it.
With current advancement in technology, it is expected and hoped that even a conditional or level 3 (L3) autonomous vehicle could alleviate older adults’ mobility issues. These conditional or level 3 autonomous vehicles allow the driver to engage in non-driving task (NDRT), but, it can request the driver to assume control of the vehicle via ‘Takeover request’ when it has reached its operational limits. Considering this could be a challenging for older drivers with their declined cognitive, perceptual, and motor capacities. A systematic review has been conducted to produce literature on their issues in a L3 autonomous vehicle. This review mainly focuses on older drivers’ challenges, perception of workload in AVs and takeover performance. This review is hoped to provide relevant literature on the subject and may help researchers improve and pursue research gaps identified in this paper.
For human factors researchers and practitioners, mental workload remains both a crucial concept and a nebulous one. After decades of work in this field, there is still no real consensus on the construct of mental workload, although there is wide agreement about its multidimensional nature and the main ways to measure it. With increasing automation in many domains, the issue of underload has attracted a considerable proportion of research effort. This paper summarises work to propose a theory of underload based on the notion of malleable attentional resources, but also raises challenges that this theory – and, perhaps, underload in general – may be specific to automation. The paper goes on to discuss the elusive ‘redlines’ of overload and underload, and concludes by considering both theoretical and applied challenges for current research into mental workload.
