Impact of human-robot interaction on user satisfaction with humanoid-based healthcare

Abstract

Background/Objectives: The advent of self-service technology (SST) (e.g.,kiosks and Automatic Response System), has made it possible for service providersto make use of non-face-to-face channels to meet users'needs and decrease users'costs and time. On the other hand, however, more complex technology and/or services inhibit users' satisfaction and,consequently,the intention to adopt SST, because such SST can instill fear in users. Nevertheless, at present, patients and other people who are interested in their own health and well-being are paying great attention to healthcare robots (as a form of SST)and,consequently, it has become crucial to investigate how these healthcare robots can positively influence users' satisfaction with them. Hence, this study aims to empirically investigate the factors that affect users' satisfaction with healthcare robots, especially in regard to human-robot interaction (HRI). Methods/Statistical analysis: We focused on the theory of heterophily and applied a series of factors identified in previous robot-adoption studies.Uniquely, this study focuses on users' heterophily with healthcare robots, examining heterophily through three fundamental ele-ments, empathy, professionalism, and personality, which we considered to be suitable fordetermining user satisfaction with HRI-based communication.To prove the validity of our hypotheses, we conducted an empirical testthat involved participants receiving a short health assessment from a robot. Findings: The findings of our empirical test supported our hypothesis that the lower the difference in empathy between a user and robot, the higher the level of user satisfaction with the humanoid-style healthcare service. Further, our results also suggest that heterogeneity between a user and healthcare robot is positively associated with user satisfaction. Improvements/Applications: First, to increase user satisfaction,robots must be provided with the ability to somehow recognizea user's personality and adjust their own accordingly before beginning the robot-based healthcare service. Secondly, users' behavior patterns should be analyzed by the healthcare robot. Overall, our study empirically shows the importance of ensuring thatprofessionalism is present in healthcare-domain-related HRI.