Exploring the Effects of User-Agent and User-Designer Similarity in Virtual Human Design to Promote Mental Health Intentions for College Students
Pedro Guillermo Feijóo-García, Chase Wrenn, Alexandre Gomes de Siqueira, Rashi Ghosh, Jacob Stuart, Heng Yao, Benjamin Lok
TL;DR
This study investigates how user-agent and user-designer demographic similarity influence co-designed virtual humans for mental health conversations among CS students. Through a two-part online study with 481 participants (Part 1) and 240 in Part 2, it analyzes agent-designer matching, appearance and voice selection rationales, and the effect of explicit designer cues on gratitude journaling intentions. Findings show strong tendencies for demographic similarity in design decisions (ethnicity, country of origin, gender) and clear preferences for appearance-voice alignment, yet explicit designer legacy cues do not significantly boost intervention effectiveness. The results highlight the complexity of visual versus verbal cues in shaping user perceptions and emphasize the need for broader, more inclusive VH design guidelines to support mental health outcomes in diverse student populations.
Abstract
Virtual humans (i.e., embodied conversational agents) have the potential to support college students' mental health, particularly in Science, Technology, Engineering, and Mathematics (STEM) fields where students are at a heightened risk of mental disorders such as anxiety and depression. A comprehensive understanding of students, considering their cultural characteristics, experiences, and expectations, is crucial for creating timely and effective virtual human interventions. To this end, we conducted a user study with 481 computer science students from a major university in North America, exploring how they co-designed virtual humans to support mental health conversations for students similar to them. Our findings suggest that computer science students who engage in co-design processes of virtual humans tend to create agents that closely resemble them demographically--agent-designer demographic similarity. Key factors influencing virtual human design included age, gender, ethnicity, and the matching between appearance and voice. We also observed that the demographic characteristics of virtual human designers, especially ethnicity and gender, tend to be associated with those of the virtual humans they designed. Finally, we provide insights concerning the impact of user-designer demographic similarity in virtual humans' effectiveness in promoting mental health conversations when designers' characteristics are shared explicitly or implicitly. Understanding how virtual humans' characteristics serve users' experiences in mental wellness conversations and the similarity-attraction effects between agents, users, and designers may help tailor virtual humans' design to enhance their acceptance and increase their counseling effectiveness.