The efforts of the United States government in the past 15 years have included harnessing the power of health information technology (HIT) to improve legibility, lessen medical errors, keep costs low, and elevate the quality of healthcare. However, user resistance is still a barrier to overcome in order to achieve desired outcomes. Understanding the nature of resistance is key to successfully increasing the adoption of HIT systems. Previous research has showed that perceived threats are a significant antecedent of user resistance; however, its nature and role have remained vastly unexplored. This study uses the psychological reactance theory to explain both the nature and role of perceived threats in HIT-user resistance. The study shows that perceived helplessness over process and perceived dissatisfaction over outcomes are two unique instances of perceived threats. Additionally, the results reveal that resistance to healthcare information systems can manifest as reactance, distrust, scrutiny, or inertia. The theoretical and practical implications of the findings are discussed.

Patients' initial impression can influence the kind of reactions they receive and their subsequent participation. Prior studies use inference models to examine participation as a continuum phenomenon. In the online health supporting communities (OHSCs), distinguishing giving participation from receiving participation provide interesting insights at the granular level. Using social presence theory, this study identifies and uses social presence cues in the initial post of 168 patients to predict patients' giving and receiving participation in a prominent OHSC. Findings reveal that the social presence cues affected the two participation dimensions differently. Specifically, while intimacy is the most important predictor of giving participation, nonverbal communication is the most important predictor for receiving participation. The study offers important contributions to research and practice.

Despite growing emphasis on the factors affecting different types of supports users receive from virtual health support communities (VHSC), theoretical knowledge on how social awareness capabilities determine the extent of the support received is yet to be investigated. Adopting social awareness theory and using data collected from the COVID-19 support community on a large VHSC platform, we apply linguistic analysis to measure the impacts of three social awareness variables-social sensitivity, social insight, and social communication-on users' response and support behaviors. The ordinary least square regression results show that social insight significantly influenced the number of replies to a post. In addition, results from the negative binomial regression also indicate that social sensitivity and social communication significantly predicted the number of support votes and thanks votes a user's post received. The findings reveal some important research and practical implications on the need to facilitate social awareness in VHSC forums.