  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.
