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Data underlying the publication: Controlling Social Stress in Virtual Reality Environments

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posted on 29.07.2019 by Dwi Hartanto, I.L. (Isabel) Kampmann, N. (Nexhmedin) Morina, P.M.G. (Paul) Emmelkamp, M.A. (Mark) Neerincx, Willem-Paul Brinkman
Virtual reality exposure therapy has been proposed as a viable alternative in the treatment of anxiety disorders, including social anxiety disorder. Therapists could benefit from extensive control of anxiety eliciting stimuli during virtual exposure. Two stimuli controls are studied in this study: the social dialogue situation, and the dialogue feedback responses (negative or positive) between a human and a virtual character. In the first study, 16 participants were exposed in three virtual reality scenarios: a neutral virtual world, blind date scenario, and job interview scenario. Results showed a significant difference between the three virtual scenarios in the level of self-reported anxiety and heart rate. In the second study, 24 participants were exposed to a job interview scenario in a virtual environment where the ratio between negative and positive dialogue feedback responses of a virtual character was systematically varied on-the-fly. Results yielded that within a dialogue the more positive dialogue feedback resulted in less self-reported anxiety, lower heart rate, and longer answers, while more negative dialogue feedback of the virtual character resulted in the opposite. The correlations between on the one hand the dialogue stressor ratio and on the other hand the means of SUD score, heart rate and audio length in the eight dialogue conditions showed a strong relationship: r(6) = 0.90, p = 0.002; r(6) = 0.74, p = 0.036 and r(6) = -0.91, p = 0.002 respectively. Furthermore, more anticipatory anxiety reported before exposure was found to coincide with more self-reported anxiety, and shorter answers during the virtual exposure. These results demonstrate that social dialogues in a virtual environment can be effectively manipulated for therapeutic purposes.

Funding

Netherlands Organization for Scientific Research, 655.010.207

History

Contributors

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Intelligent Systems; University of Amsterdam

Publisher

4TU.Centre for Research Data

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media types: application/pdf, application/x-spss-sav, application/zip, text/csv, text/plain

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