Deighan, Mairi Therese;
Ayobi, Amid;
O'Kane, Aisling Ann;
(2023)
Social Virtual Reality as a Mental Health Tool: How People Use VRChat to Support Social Connectedness and Wellbeing.
In:
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems.
(pp. pp. 1-13).
ACM
(In press).
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Abstract
Social virtual reality (VR) platforms have increased in popularity with many people turning to these platforms to experience social connection, including a rapid influx of users during the COVID-19 pandemic. However, there is limited understanding of how people appropriate and use emerging social VR applications to actively support their mental health and wellbeing in daily life. Through an online questionnaire and exploratory interviews conducted within the social VR app VRChat during the COVID-19 pandemic, we document how social VR is being used explicitly as a mental health support tool. Participants reported positive wellbeing benefits, mostly attributed to the anonymity provided by avatars and perceived safety within digital worlds and communities of practice. We also report how people use social VR to practice social interaction, reduce negative thoughts and form strong social bonds and connections with others.
| Type: | Proceedings paper |
|---|---|
| Title: | Social Virtual Reality as a Mental Health Tool: How People Use VRChat to Support Social Connectedness and Wellbeing |
| Event: | CHI '23: CHI Conference on Human Factors in Computing Systems |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3544548.3581103 |
| Publisher version: | https://doi.org/10.1145/3544548.3581103 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10172071 |
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