Participatory Design of Virtual Humans for Mental Health Support Among North American Computer Science Students: Voice, Appearance, and the Similarity-attraction Effect
Authors: 
Pedro Guillermo Feijóo-García, Chase Wrenn, Jacob Stuart, Alexandre Gomes De Siqueira, Benjamin LokAuthors Info & Claims
Pedro Guillermo Feijóo-García, Chase Wrenn, Jacob Stuart, Alexandre Gomes De Siqueira, Benjamin LokAuthors Info & ClaimsArticle No.: 11, Pages 1 - 27
Abstract
Virtual humans (VHs) have the potential to support mental wellness among college computer science (CS) students. However, designing effective VHs for counseling purposes requires a clear understanding of students’ demographics, backgrounds, and expectations. To this end, we conducted two user studies with 216 CS students from a major university in North America. In the first study, we explored how students co-designed VHs to support mental wellness conversations and found that the VHs’ demographics, appearance, and voice closely resembled the characteristics of their designers. In the second study, we investigated how the interplay between the VH’s appearance and voice impacted the agent’s effectiveness in promoting CS students’ intentions toward gratitude journaling. Our findings suggest that the active participation of CS students in VH design leads to the creation of agents that closely resemble their designers. Moreover, we found that the interplay between the VH’s appearance and voice impacts the agent’s effectiveness in promoting CS students’ intentions toward mental wellness techniques.
References
[1]
Icek Ajzen. 1985. From Intentions to Actions: A Theory of Planned Behavior. Springer, Berlin, 11–39.
[2]
Daniel R. Ames. 2004. Inside the mind reader’s tool kit: Projection and stereotyping in mental state inference. J. Personal. Soc. Psychol. 87, 3 (2004), 340.
[3]
Judd Antin and Aaron Shaw. 2012. Social desirability bias and self-reports of motivation: A study of amazon mechanical turk in the U.S. and India. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’12). ACM, New York, NY, 2925–2934.
[4]
Burton L Backner. 1970. Counseling black students: Any place for whitey?J. Higher Edu. 41, 8 (1970), 630–637.
[5]
Amy Baylor, E. Shen, and Xiaoxia Huang. 2003. Which pedagogical agent do learners choose? The effects of gender and ethnicity. In Proceedings of the World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (E-Learn’03). Association for the Advancement of Computing in Education (AACE), 1507–1510.
[6]
Amy L. Baylor and Yanghee Kim. 2004. Pedagogical agent design: The impact of agent realism, gender, ethnicity, and instructional role. In Proceedings of the International Conference on Intelligent Tutoring Systems. Springer, 592–603.
[7]
Margaret Bearman, Branko Cesnik, and Merilyn Liddell. 2001. Random comparison of “virtual patient” models in the context of teaching clinical communication skills. Med. Edu. 35, 9 (2001), 824–832.
[8]
Emily P. Bernier and Brian Scassellati. 2010. The similarity-attraction effect in human-robot interaction. In Proceedings of the IEEE 9th International Conference on Development and Learning. IEEE, 286–290.
[9]
Kuldhir S. Bhati. 2014. Effect of client-therapist gender match on the therapeutic relationship: An exploratory analysis. Psychol. Rep. 115, 2 (2014), 565–583.
[10]
Adrian J. Blow, Tina M. Timm, and Ronald Cox. 2008. The role of the therapist in therapeutic change: Does therapist gender matter?J. Femin. Family Ther. 20, 1 (2008), 66–86.
[11]
Raquel R. Cabral and Timothy B. Smith. 2011. Racial/ethnic matching of clients and therapists in mental health services: A meta-analytic review of preferences, perceptions, and outcomes.J. Counsel. Psychol. 58, 4 (2011), 537.
[12]
Aaron Castelan Cargile. 2000. Evaluations of employment suitability: Does accent always matter?J. Employ. Counsel. 37, 3 (2000), 165–177.
[13]
Pauline Rose Clance and Suzanne Ament Imes. 1978. The imposter phenomenon in high achieving women: Dynamics and therapeutic intervention.Psychother.: Theory, Res. Pract. 15, 3 (1978), 241.
[14]
Benjamin R. Cowan, Derek Gannon, Jenny Walsh, Justin Kinneen, Eanna O’Keefe, and Linxin Xie. 2016. Towards understanding how speech output affects navigation system credibility. In Proceedings of the CHI Conference Extended Abstracts on Human Factors in Computing Systems. 2805–2812.
[15]
Scotty D. Craig and Noah L. Schroeder. 2017. Reconsidering the voice effect when learning from a virtual human. Comput. Edu. 114 (2017), 193–205.
[16]
CSUSM. 2022. Inclusive Language Guidelines: Gender Identity. Retrieved from https://www.csusm.edu/ipa/surveys/inclusive-language-guidelines.html.Retrieved June 20, 2022.
[17]
Nils Dahlbäck, QianYing Wang, Clifford Nass, and Jenny Alwin. 2007. Similarity is more important than expertise: Accent effects in speech interfaces. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 1553–1556.
[18]
Andrew Danowitz and Kacey Beddoes. 2018. Characterizing mental health and wellness in students across engineering disciplines. In Proceedings of the Collaborative Network for Engineering and Computing Diversity Conference.
[19]
Malin Eiband, Mohamed Khamis, Emanuel von Zezschwitz, Heinrich Hussmann, and Florian Alt. 2017. Understanding shoulder surfing in the wild: Stories from users and observers. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI’17). ACM, New York, NY, 4254–4265.
[20]
Teresa M. Evans, Lindsay Bira, Jazmin Beltran Gastelum, L. Todd Weiss, and Nathan L. Vanderford. 2018. Evidence for a mental health crisis in graduate education. Nature Biotechnol. 36, 3 (2018), 282–284.
[21]
Pedro Guillermo Feijóo-García, Mohan Zalake, Alexandre Gomes de Siqueira, Benjamin Lok, and Felix Hamza-Lup. 2021. Effects of Virtual Humans’ Gender and Spoken Accent on Users’ Perceptions of Expertise in Mental Wellness Conversations. ACM, New York, NY, 68–75.
[22]
Carol L. Flinchbaugh, E. Whitney G. Moore, Young K. Chang, and Douglas R. May. 2012. Student well-being interventions: The effects of stress management techniques and gratitude journaling in the management education classroom. J. Manage. Edu. 36, 2 (2012), 191–219.
[23]
Christopher Frauenberger, Judith Good, and Wendy Keay-Bright. 2011. Designing technology for children with special needs: Bridging perspectives through participatory design. CoDesign 7, 1 (2011), 1–28.
[24]
Clarice Gorenstein, Sabine Pompéia, and Laura Andrade. 1995. Scores of brazilian university students on the beck depression and the state-trait anxiety inventories. Psychol. Rep. 77, 2 (1995), 635–641.
[25]
Rosanna E. Guadagno, Kimberly R. Swinth, and Jim Blascovich. 2011. Social evaluations of embodied agents and avatars. Comput. Hum. Behav. 27, 6 (2011), 2380–2385.
[26]
Shivashankar Halan, Benjamin Lok, Isaac Sia, and Michael Crary. 2014. Virtual agent constructionism: Experiences from health professions students creating virtual conversational agent representations of patients. In Proceedings of the IEEE 14th International Conference on Advanced Learning Technologies. IEEE, 249–253.
[27]
Shivashankar Halan, Isaac Sia, Michael Crary, and Benjamin Lok. 2015. Exploring the effects of healthcare students creating virtual patients for empathy training. In Proceedings of the International Conference on Intelligent Virtual Agents. Springer, 239–249.
[28]
Sherry L. Hatcher, Todd K. Favorite, Elizabeth A. Hardy, Robert L. Goode, Linda A. DeShetler, and Rosa M. Thomas. 2005. An analogue study of therapist empathic process: Working with difference.Psychother.: Theory, Res., Pract., Train. 42, 2 (2005), 198.
[29]
Francisco Iacobelli and Justine Cassell. 2007. Ethnic identity and engagement in embodied conversational agents. In Proceedings of the International Workshop on Intelligent Virtual Agents. Springer, 57–63.
[30]
Peter Khooshabeh, Morteza Dehghani, Angela Nazarian, and Jonathan Gratch. 2017. The cultural influence model: When accented natural language spoken by virtual characters matters. AI Soc. 32, 1 (2017), 9–16.
[31]
Bruce M. King, Alexandra E. Scott, Elizabeth M. Van Doorn, Emily E. Abele, and Meredith E. McDevitt. 2020. Reasons students at a us university do or do not enrol in a human sexuality course. Sex Edu. 20, 1 (2020), 101–109.
[32]
Tomoko Koda and Yuuki Takeda. 2018. Perception of culture-specific gaze behaviors of agents and gender effects. In Proceedings of the 6th International Conference on Human-Agent Interaction. 138–143.
[33]
Eun Ju Lee, Clifford Nass, and Scott Brave. 2000. Can computer-generated speech have gender? An experimental test of gender stereotype. In Proceedings of the Extended Abstracts on Human Factors in Computing Systems (CHI’00). 289–290.
[34]
Shiri Lev-Ari and Boaz Keysar. 2010. Why don’t we believe non-native speakers? The influence of accent on credibility. J. Exper. Soc. Psychol. 46, 6 (2010), 1093–1096.
[35]
Shiri Lev-Ari and Boaz Keysar. 2012. Less-detailed representation of non-native language: Why non-native speakers’ stories seem more vague. Disc. Process. 49, 7 (2012), 523–538.
[36]
Joy Ming, Sharon Heung, Shiri Azenkot, and Aditya Vashistha. 2021. Accept or address? Researchers’ perspectives on response bias in accessibility research. In Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS’21). ACM, New York, NY, Article 20, 13 pages.
[37]
Andrea C. Morales, Maura L. Scott, and Eric A. Yorkston. 2012. The role of accent standardness in message preference and recall. J. Advert. 41, 1 (2012), 33–46.
[38]
Michael J. Muller and Sarah Kuhn. 1993. Participatory design. Commun. ACM 36, 6 (1993), 24–28.
[39]
David Obremski, Jean-Luc Lugrin, Philipp Schaper, and Birgit Lugrin. 2021. Non-native speaker perception of intelligent virtual agents in two languages: The impact of amount and type of grammatical mistakes. J. Multimodal User Interf. 15, 2 (2021), 229–238.
[40]
Jean A. Pratt, Karina Hauser, Zsolt Ugray, and Olga Patterson. 2007. Looking at human–computer interface design: Effects of ethnicity in computer agents. Interact. Comput. 19, 4 (2007), 512–523.
[41]
Belle Rose Ragins. 1997. Diversified mentoring relationships in organizations: A power perspective. Acad. Manage. Rev. 22, 2 (1997), 482–521.
[42]
Adam Rosenstein, Aishma Raghu, and Leo Porter. 2020. Identifying the prevalence of the impostor phenomenon among computer science students. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education (SIGCSE’20). ACM, New York, NY, 30–36.
[43]
Herbert W. Simons, Nancy N. Berkowitz, and R. John Moyer. 1970. Similarity, credibility, and attitude change: A review and a theory.Psychol. Bull. 73, 1 (1970), 1.
[44]
Jesper Simonsen and Toni Robertson. 2013. Routledge International Handbook of Participatory Design. Vol. 711. Routledge, New York.
[45]
Ramadhar Singh. 1974. Reinforcement and attraction specifying the effects of affective states. J. Res. Personal. 8, 3 (1974), 294–305.
[46]
Lígia Maria Soares Passos, Christian Murphy, Rita Zhen Chen, Marcos Gonçalves de Santana, and Giselle Soares Passos. 2020. The prevalence of anxiety and depression symptoms among brazilian computer science students. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education (SIGCSE’20). ACM, New York, NY, 316–322.
[47]
Mark A. Stewart, Ellen Bouchard Ryan, and Howard Giles. 1985. Accent and social class effects on status and solidarity evaluations. Personal. Soc. Psychol. Bull. 11, 1 (1985), 98–105.
[48]
Synthesia. 2022. Synthesia: AI video generation platform. Retrieved from https://www.synthesia.io/.Retrieved June 20, 2022.
[49]
Maarten Van Mechelen, Line Have Musaeus, Ole Sejer Iversen, Christian Dindler, and Arthur Hjorth. 2021. A systematic review of empowerment in child-computer interaction research. In Proceedings of the Conference on Interaction Design and Children (IDC’21). ACM, New York, NY, 119–130.
[50]
Asimina Vasalou, Seray Ibrahim, Michael Clarke, and Yvonne Griffiths. 2021. On power and participation: Reflections from design with developmentally diverse children. Int. J. Child-Comput. Interact. 27 (2021), 100241.
[51]
Steve Whittaker, Yvonne Rogers, Elena Petrovskaya, and Hongbin Zhuang. 2021. Designing personas for expressive robots: Personality in the new breed of moving, speaking, and colorful social home robots. ACM Trans. Hum.-Robot Interact. 10, 1 (2021), 1–25.
[52]
Matthew B. Wintersteen, Janell L. Mensinger, and Guy S. Diamond. 2005. Do gender and racial differences between patient and therapist affect therapeutic alliance and treatment retention in adolescents?Prof. Psychol.: Res. Pract. 36, 4 (2005), 400.
[53]
Jacob O. Wobbrock, Meredith Ringel Morris, and Andrew D. Wilson. 2009. User-defined gestures for surface computing. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI’09). ACM, New York, NY, 1083–1092.
[54]
Mohan Zalake, Alexandre Gomes de Siqueira, Krishna Vaddiparti, Pavlo Antonenko, and Benjamin Lok. 2021. Towards understanding how virtual human’s verbal persuasion strategies influence user intentions to perform health behavior. In Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents. 216–223.
[55]
Nolan Zane and Helen Ku. 2014. Effects of ethnic match, gender match, acculturation, cultural identity, and face concern on self-disclosure in counseling for asian americans.Asian Amer. J. Psychol. 5, 1 (2014), 66.
[56]
Caron Zlotnick, Irene Elkin, and M. Tracie Shea. 1998. Does the gender of a patient or the gender of a therapist affect the treatment of patients with major depression?J. Consult. Clin. Psychol. 66, 4 (1998), 655.
Index Terms
- Participatory Design of Virtual Humans for Mental Health Support Among North American Computer Science Students: Voice, Appearance, and the Similarity-attraction Effect
Recommendations
Can we talk about bruno?: exploring virtual human counselors' spoken accents and their impact on users' conversations
IVA '22: Proceedings of the 22nd ACM International Conference on Intelligent Virtual AgentsCounseling requires intimacy between a counselor and a patient to reach healing and growth. However, building rapport between virtual human counselors and computing college students is a complex problem. It requires understanding students' experiences ...
Exploring the Effects of User-Agent and User-Designer Similarity in Virtual Human Design to Promote Mental Health Intentions for College Students
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 ...
Participatory design of an online therapy for youth mental health
OzCHI '13: Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, CollaborationOnline therapy has the potential to extend existing face-to-face support for mental health, but designers face challenges such as lack of user engagement. Participatory design could improve outcomes but is difficult to pursue in the mental health ...
Comments
Information & Contributors
Information
Published In
July 2023
58 pages
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 20 September 2023
Online AM: 05 August 2023
Accepted: 19 July 2023
Revised: 15 June 2023
Received: 16 August 2022
Published in TAP Volume 20, Issue 3
Check for updates
Author Tags
Qualifiers
- Research-article
Funding Sources
- National Science Foundation
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 515Total Downloads
- Downloads (Last 12 months)411
- Downloads (Last 6 weeks)37
Reflects downloads up to 10 Nov 2024
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in