AI healthcare adoption: a privacy calculus model incorporating emotions and technosocial factors.

This research investigates technical characteristics and technological, social, and affective factors that influence the evaluation of perceived privacy risks and benefits toward adopting AI-based smart healthcare services in the USA. The study develops a research model that integrates Privacy Calculus Theory (PCT) with new constructs, i.e., AI technical characteristics (personalization and anthropomorphism), technological factors (perceived ease of use and perceived usefulness), social factors (social influence and privacy regulation) and two opposite emotional states (enjoyment and exhaustion). A survey will be developed and distributed using crowdsourcing through Prolific. The findings of our research will shed light on the different role of technical characteristics and technological, social, and affective factors on the calculus between perceived risks and benefits in relation to the adoption of AI-based smart healthcare services. [ABSTRACT FROM AUTHOR]