This study was designed to investigate the roles information and communications technology (ICT) played during the current COVID-19 pandemic. Specifically, we focused on the relationships between ICT use and perceived importance of social connectedness and future anxiety, while considering relevant personality and psychosocial factors. A U.S. sample of 394 adults answered questions about ICT use, pandemic-related reactions and actions, demographics, and psychosocial factors via an online survey. Using logistic regression, findings indicated that personality (extraversion and conscientiousness) and psychosocial (need to belong and perceived attachment to phone) factors, types of ICT as news source, and gender were associated with perceived importance of social connectedness. Neuroticism, time spent on ICT for social purposes, and perceived threat of COVID-19 were associated with future anxiety. In addition, using Mann–Whitney U test, people who rated higher on importance of social connectedness had higher ICT use, both in terms of types and time spent on ICT. Overall, results are consistent with the idea that technology is a coping tool during the pandemic and balanced use can lead to feelings of social connectedness and less future anxiety. Therefore, it is important for authorities to align their messaging and outreach with people’s psychosocial, personality, and health considerations through ICT channels while empowering ICT users to be responsible for their interactions with the technology.
This theoretical review focuses on defining users' mental models in modern computermediated communication (CMC) where users interact with intelligent virtual agents. The proposed framework integrates relevant literature in CMC, human-computer interaction, social behavior, and mental models and illustrates the relationship between emerging technology and user behaviors. Using an eHealth context, the framework outlines the initiating (user knowledge and intentions) and mediating (virtual agent representations, context, perceived agency, interactions, and limitations) factors for the development of users' mental models and the process for calibration and behavioral modification upon prolonged use. This framework is expected to be applied to other domain applications and to complement theoretical models that focus on the technological side of human-agent interaction. Better understanding of users' mental models will lead to the timely design and evaluation of intelligent systems and the redefinition of the roles for humans as we embrace more emerging and innovative technologies.
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