TY  - JOUR
AU  - Tanaka, Hiroki
AU  - Nakamura, Satoshi
PY  - 2022
DA  - 2022/3/29
TI  - The Acceptability of Virtual Characters as Social Skills Trainers: Usability Study
JO  - JMIR Hum Factors
SP  - e35358
VL  - 9
IS  - 1
KW  - social skills training
KW  - virtual agent design
KW  - virtual assistant
KW  - virtual trainer
KW  - chatbot
KW  - acceptability
KW  - realism
KW  - virtual agent
KW  - simulation
KW  - social skill
KW  - social interaction
KW  - design
KW  - training
KW  - crowdsourcing
AB  - Background: Social skills training by human trainers is a well-established method to provide appropriate social interaction skills and strengthen social self-efficacy. In our previous work, we attempted to automate social skills training by developing a virtual agent that taught social skills through interaction. Previous research has not investigated the visual design of virtual agents for social skills training. Thus, we investigated the effect of virtual agent visual design on automated social skills training. Objective: The 3 main purposes of this research were to investigate the effect of virtual agent appearance on automated social skills training, the relationship between acceptability and other measures (eg, likeability, realism, and familiarity), and the relationship between likeability and individual user characteristics (eg, gender, age, and autistic traits). Methods: We prepared images and videos of a virtual agent, and 1218 crowdsourced workers rated the virtual agents through a questionnaire. In designing personalized virtual agents, we investigated the acceptability, likeability, and other impressions of the virtual agents and their relationship to individual characteristics. Results: We found that there were differences between the virtual agents in all measures (P<.001). A female anime-type virtual agent was rated as the most likeable. We also confirmed that participants’ gender, age, and autistic traits were related to their ratings. Conclusions: We confirmed the effect of virtual agent design on automated social skills training. Our findings are important in designing the appearance of an agent for use in personalized automated social skills training. 
SN  - 2292-9495
UR  - https://humanfactors.jmir.org/2022/1/e35358
UR  - https://doi.org/10.2196/35358
UR  - http://www.ncbi.nlm.nih.gov/pubmed/35348468
DO  - 10.2196/35358
ID  - info:doi/10.2196/35358
ER  -