An Empirical Study on Social Anxiety in a Virtual Environment through Mediating Variables and Multiple Sensor Data

Social anxiety disorder is a psychological condition characterized by excessive nervousness in social situations, such as interpersonal interactions. Exposure therapy has shown benefits in its treatment, and virtual reality (VR) technology has gained much attention for reducing physical and psychological distance and providing additional quantitative evidence from the data generated by standard VR devices (e.g., head-mounted display). Clinical psychology studies have highlighted the importance of mediating variables of social anxiety; however, existing VR-based social anxiety studies have neglected such variables with respect to user experience and data analysis in the context of VR, although these variables could provide insights into the design and use of VR for the treatment of social anxiety. In this study, we focused on two representative mediating variables of social anxiety: (1) the gap between self-presentation motivation and expectancy , and (2) self-focused attention . We used sensor data (e.g., head movement, eye movement, eye gaze, and psychological signals) to investigate the impact of these variables on users' anxiety responses in VR. We developed <u>VR</u>-based <u>S</u>ocial Anxiety Support <u>T</u>ool (VRST) that reflects the theoretical design elements of effective anxiety provocation. Based on the results of a user study with 30 participants, we confirmed that the mediating variables were associated with social anxiety in the VR environment. We also found that the mediating variables were associated with eye gaze, eye pupil, head movement, and body temperature. Our study results provide researchers, designers, and practitioners with empirical evidence and implications for the use of VR technology and sensor data in the mental health context.