Effects of a computer's human likeness on disclosure in psychosocial assessments: A randomised trial

Highly realistic embodied conversational agents (virtual humans) are starting to be used in healthcare, yet we know little about how their human likeness affects self-disclosure compared to other digital assessment methods. This research aimed to investigate the effects of a computer's human likeness on disclosure during a psychosocial assessment. 160 participants (mean age 24 years, 117 females, 42 males, 1 gender diverse) were randomized to receive a psychosocial interview from a realistic virtual human, a text chatbot, or an online questionnaire. The assessment comprised 18 close-ended items and six open-ended questions on diet, exercise, sexual practices, substance use, recent emotional experiences and loneliness. Socially desirable responding and unwillingness to respond were identified from answers, amount of disclosure was assessed from word count, and perceived anthropomorphism was assessed using self-report. Results demonstrated that for sensitive questions, there was higher socially desirable responding in the virtual human group as shown by significantly lower loneliness scores and higher rates of declining to answer a question compared to the other groups. For non-sensitive questions, socially desirable responding and proportion of declined answers did not differ by group. Participants in the virtual human group used more words when reporting stressful events and positive emotional experiences. Thematic analysis showed people felt rapport with both the virtual human and chatbot, but some felt social evaluative pressure with the virtual human. This supports theories that as human likeness cues increase, humans treat robots more socially. These findings should be considered when humanlike technologies are used clinically.