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Self-disclosure counts as a key factor influencing successful healthtreatment, particularly when it comes to building a functioningpatient-therapist-connection. To this end, the use of chatbots may beconsidered a promising puzzle piece that helps foster respective informationprovision. Several studies have shown that people disclose more informationwhen they are interacting with a chatbot than when they are interacting withanother human being. If and how the chatbot is embodied, however, seems to playan important role influencing the extent to which information is disclosed.Here, research shows that people disclose less if the chatbot is embodied witha human avatar in comparison to a chatbot without embodiment. Still, there isonly little information available as to whether it is the embodiment with ahuman face that inhibits disclosure, or whether any type of face will reducethe amount of shared information. The study presented in this paper thus aimsto investigate how the type of chatbot embodiment influences self-disclosure inhuman-chatbot-interaction. We conducted a quasi-experimental study in which$n=178$ participants were asked to interact with one of three settings of achatbot app. In each setting, the humanness of the chatbot embodiment wasdifferent (i.e., human vs. robot vs. disembodied). A subsequent discourseanalysis explored difference in the breadth and depth of self-disclosure.Results show that non-human embodiment seems to have little effect onself-disclosure. Yet, our data also shows, that, contradicting to previouswork, human embodiment may have a positive effect on the breadth and depth ofself-disclosure.

Tell me, what are you most afraid of? Exploring the Effects of Agent Representation on Information Disclosure in Human-Chatbot Interaction