  Self-disclosure counts as a key factor influencing successful health
treatment, particularly when it comes to building a functioning
patient-therapist-connection. To this end, the use of chatbots may be
considered a promising puzzle piece that helps foster respective information
provision. Several studies have shown that people disclose more information
when they are interacting with a chatbot than when they are interacting with
another human being. If and how the chatbot is embodied, however, seems to play
an important role influencing the extent to which information is disclosed.
Here, research shows that people disclose less if the chatbot is embodied with
a human avatar in comparison to a chatbot without embodiment. Still, there is
only little information available as to whether it is the embodiment with a
human face that inhibits disclosure, or whether any type of face will reduce
the amount of shared information. The study presented in this paper thus aims
to investigate how the type of chatbot embodiment influences self-disclosure in
human-chatbot-interaction. We conducted a quasi-experimental study in which
$n=178$ participants were asked to interact with one of three settings of a
chatbot app. In each setting, the humanness of the chatbot embodiment was
different (i.e., human vs. robot vs. disembodied). A subsequent discourse
analysis explored difference in the breadth and depth of self-disclosure.
Results show that non-human embodiment seems to have little effect on
self-disclosure. Yet, our data also shows, that, contradicting to previous
work, human embodiment may have a positive effect on the breadth and depth of
self-disclosure.
