Skip to main content

A reliable and robust online validation method for creating a novel 3D Affective Virtual Environment and Event Library (AVEL).

Mavridou, I., Balaguer-Ballester, E., Nduka, C. and Seiss, E., 2023. A reliable and robust online validation method for creating a novel 3D Affective Virtual Environment and Event Library (AVEL). PLoS ONE, 18 (4), e0278065.

Full text available as:

[img]
Preview
PDF (OPEN ACCESS ARTICLE)
Mavridou_2023.pdf - Published Version
Available under License Creative Commons Attribution.

1MB

DOI: 10.1371/journal.pone.0278065

Abstract

This paper describes the development and validation of 3D Affective Virtual environments and Event Library (AVEL) for affect induction in Virtual Reality (VR) settings with an online survey; a cost-effective method for remote stimuli validation which has not been sufficiently explored. Three virtual office-replica environments were designed to induce negative, neutral and positive valence. Each virtual environment also had several affect inducing events/objects. The environments were validated using an online survey containing videos of the virtual environments and pictures of the events/objects. They survey was conducted with 67 participants. Participants were instructed to rate their perceived levels of valence and arousal for each virtual environment (VE), and separately for each event/object. They also rated their perceived levels of presence for each VE, and they were asked how well they remembered the events/objects presented in each VE. Finally, an alexithymia questionnaire was administered at the end of the survey. User ratings were analysed and successfully validated the expected affect and presence levels of each VE and affect ratings for each event/object. Our results demonstrate the effectiveness of the online validation of VE material in affective and cognitive neuroscience and wider research settings as a good scientific practice for future affect induction VR studies.

Item Type:Article
Group:Faculty of Science & Technology
ID Code:38441
Deposited By: Symplectic RT2
Deposited On:18 Apr 2023 12:13
Last Modified:18 Apr 2023 12:13

Downloads

Downloads per month over past year

More statistics for this item...
Repository Staff Only -