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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10119/19338
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| Title: | Assessing Self-Disclosure Willingness in Metaverse-Based Structured Group Encounter |
| Authors: | Kawakita, Teru Kanai, Hideaki |
| Keywords: | Kansei (affective) engineering Group therapy Avatar Metaverse Human-computer interaction |
| Issue Date: | 2024-07 |
| Publisher: | AHFE Open Access |
| Magazine name: | AHFE International |
| Volume: | 145 |
| Start page: | 78 |
| End page: | 85 |
| DOI: | 10.54941/ahfe1005143 |
| Abstract: | Avatar-based communication in the metaverse offers a more extensive range of nonverbal information compared to traditional web-conferencing platforms. This study introduced a metaverse-based structured group encounter (M-SGE) and examined its effects on state anxiety, mood, and self-disclosure. The results indicated a significant reduction in state anxiety among participants following their involvement in M-SGE (p=.01, d=0.90). Additionally, there was a marked increase in the participants’ willingness to self-disclose (p=.019, d=-0.79). However, no significant differences in mood were observed before and after the M-SGE. The M-SGE offers the advantage of enabling communication through avatars for individuals perceiving face-to-face conversations as a challenge, regardless of time and place constraints. During the experiment, there were occasional instances of voice feedback and audio difficulties among participants, indicating the need for an improved communication environment. |
| Rights: | Copyright (c) 2024 Authors. Teru Kawakita and Hideaki Kanai. AHFE International, Vol. 145, 2024, 78-85. This is an Open Access article distributed under the terms of Creative Commons Licence CC-BY [http://creativecommons.org/licenses/by/4.0/]. Original publication is available on AHFE Open Access via https://doi.org/10.54941/ahfe1005143. |
| URI: | http://hdl.handle.net/10119/19338 |
| Material Type: | publisher |
| Appears in Collections: | a11-1. 会議発表論文 (Conference Papers)
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| H-KANAI-K-0823.pdf | | 886Kb | Adobe PDF | View/Open |
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