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This study is a preliminary exploration of adoption of generative adversarial network (GAN)-derived avatar healthcare providers (HCPs). To our knowledge, GAN-derived avatars as de facto HCPs have not been investigated in relation to user trust and behavioral intention in a simulated telehealth setting. Therefore, drawing from the Computers are Social Actors (CASA) paradigm, this study focuses on how perception of GAN-derived avatar HCPs in a one-way video encounter impacts trust and behavioral intention. A pretest-posttest experiment was conducted to gain insight into participants' trust and behavioral intention. A survey was used as the instrument to collect responses before/after viewing a brief video featuring an HCP (human or GAN-derived avatar) presenting information on a common medical condition. Hypotheses were that GAN-derived avatar and human counterparts would be (1) perceived as equally trustworthy and (2) associated with similar behavioral intentions (i.e., following provider advice, returning to provider, recommending provider). The analysis (N=147) offers evidence in support of both hypotheses, showing that avatar HCPs and human HCPs are not perceived significantly differently in terms of trust and behavioral intention. Although participant ratings of trust and behavioral intention were similar for both types of HCPs, findings indicated participant trust and behavioral intention declined for both types of HCP encounters over time (compared to pre-encounter beliefs/expectations). Additionally, participants were more willing to offer trust than behavioral intention for both types of HCPs. Findings lay groundwork for further inquiry of establishing novel roles for GAN-derived avatars in healthcare contexts such as telehealth.
