Abstract
A healthcare provider’s gender not only influences patients’ health-related behaviors but also the reliability of health information. Grounded in the Computers Are Social Actors (CASA) theory and prior health literature, the current study examines how healthcare chatbots’ gender cues and user gender affect intentions to use the chatbot and chatbot expertise perceptions. Using a 3 (Chatbot Gender Cues: Chatbot vs. Male Doctor vs. Female Doctor) X 2 (User Gender: Male vs. Female) between-subjects experiment, this study indicates that the female-doctor design cues led to significantly higher perceived warmth and communication satisfaction, which subsequently increased social presence and future intentions to use the chatbot. Results also indicated a significant gender congruence effect between female users and the female-doctor design cue chatbot to yield greater communication satisfaction. This study, however, did not find a significant difference in perceived expertise between male versus female doctor design cues. Theoretical and practical implications are discussed.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Eunjoo Jin
Eunjoo Jin is an Assistant Professor of Strategic Communication in the Jack J. Valenti School of Communication at the University of Houston. Her research is to enhance persuasion and user engagement in computer-mediated communication and human-computer interaction.
Matthew Eastin
Matthew Eastin is a Professor in the Department of Advertising and Public Relations at The University of Texas at Austin. He has investigated information processing as well as the social and psychological factors associated with game play involvement, new media adoption, e-commerce, e-health, and organizational use.