Self-identification with a Virtual Experience and Its Moderating Effect on Self-efficacy and Presence

ABSTRACT

Effective psychological interventions for anxiety disorders often include exposure to fearful situations. However, individuals with low self-efficacy may find such exposure too overwhelming. We created a vicarious experience in virtual reality, which enables observation of one’s experience from a first person perspective without actual performance and which might increase self-efficacy. With similarities to both traditional vicarious experiences and direct experiences, the level of self-identification with the experience was hypothesized to affect self-efficacy and its relationship with direct experiences. To test this, vicarious experiences with two distinct levels of self-identification were compared in a between-subjects experiment ($n=60$). After being exposed to a vicarious experience of giving lectures on elementary arithmetic in front of a virtual audience with either a high or low level of self-identification with the public speaker, participants from both conditions actively gave another lecture. The results revealed that self-identification affected people’s self-efficacy after vicarious experience. They further revealed that self-identification is a moderator of (1) the correlation between perceived performance and self-efficacy, (2) the correlation between self-efficacy measured after the vicarious and the follow-up direct experience; and (3) the correlation between the sense of presence reported in the vicarious and in the follow-up direct experience. We anticipate that the first-person-perspective experiences with high-level of self-identification have the potential to be beneficial for training where changing people’s self-efficacy is desirable.

Notes

1. These files are stored for public access on a national database for research data with the 4TU Center for Research Data in the Netherlands. The DOI to this storage is https://doi.org/10.4121/12826307.v2.

2. Even with a posthoc correction for four phases, the result remained significant ($t(58)=-2.71$, $p=0.03$).

Additional information

Funding

This research is supported by the Netherlands Organization for Scientific Research (NWO), grant number [655.010.207], and China Scholarship Council (CSC), grant number [2010609042 and 201506090167].

Notes on contributors

Ni Kang

Ni Kang received her Ph.D. degree in computer science at the Delft University of Technology, The Netherlands. She is currently working as a data scientist, specializing in statistical analysis and pattern recognition. The application context of her projects varies from defect detection in production line to clinical diagnosis.

Ding Ding

Ding Ding received his Ph.D. degree in Interactive Intelligence Group at the Delft University of Technology, The Netherlands. He is currently an assistant professor in the school of computer science and engineering at Southeast University, China. His research focuses on human–computer interaction, developing computer-supported training, education, and therapy systems.

M. Birna Van Riemsdijk

M. Birna van Riemsdijk is associate professor Intimate Computing at University of Twente. Her research investigates how to take into account our human vulnerability in the design and run-time reasoning of intimate technologies. She was awarded a Vidi personal grant and the Dutch Prize for Research in ICT 2014.

Nexhmedin Morina

Nexhmedin Morina received his Ph.D. from the Department of Psychology, University of Jena, Germany. He is currently professor of Clinical Psychology and Psychotherapy at the University of Münster, Germany. His research interests include investigating the etiology and treatment of posttraumatic stress disorder, anxiety disorders, and depression as well as comparison processes.

Mark A. Neerincx

Mark A. Neerincx received a Ph.D. degree in psychology from the University of Groningen, The Netherlands. He is currently a principal scientist at TNO and a professor in Human-Centered Computing at TU Delft, The Netherlands. His research interests include cognitive engineering, social robots, and cognitive task load modeling for adaptive interfaces.

Willem-Paul Brinkman

Willem-Paul Brinkman received his PhD degree in 2003 at Eindhoven University of Technology, The Netherlands. Currently he is an associate professor in the Intelligent Systems Department at Delft University of Technology. His main research interests lie in the area behavior change support systems, including virtual reality systems, and conversational agents.