Virtual reality and neuropsychological assessment: an analysis of human factors influencing performance and perceived mental effort

虚拟现实 模态(人机交互) 模式 计算机科学 威斯康星卡片分类测试 心理学 应用心理学 认知心理学 神经心理学 刺激形态 认知 人机交互 感觉系统 社会科学 社会学 神经科学
作者
Arthur Maneuvrier,Hadrien Ceyte,P. Renaud,Rémy Morello,Philippe Fleury,Leslie M. Decker
出处
期刊:Virtual Reality [Springer Nature]
卷期号:27 (2): 849-861 被引量:5
标识
DOI:10.1007/s10055-022-00698-4
摘要

This study aimed to compare a neuropsychological test tapping into executive control function, the Wisconsin Card Sorting Test (WCST), performed in either traditional paper-and-pencil (PP) or virtual reality (VR) modality, and to determine the role of human factors (i.e., sense of presence, cybersickness, field (in)dependence and video game experience) as contributors to performance and perceived mental effort. Indeed, if virtual assessment might bring the ecological dimension to controlled laboratory research, it is often suggested that human factors might bias performance. WCST performance and its associated perceived mental effort were compared between the two modalities (N = 107). In the VR modality (N = 52), a correlation matrix was conducted as well as a cluster analysis in order to build two experimental groups, or profiles, based on their subjective experience of VR. WCST performance and perceived mental effort were then compared between these two groups while controlling for age and education. Results outlined a similar WCST performance and perceived mental effort between the PP and VR modalities. However, when comparing the two VR groups, results suggest that an unfavorable profile for VR, i.e., less sense of presence, more cybersickness, more visual field dependence and less video game experience, is associated with greater perceived mental effort. These experimental findings enable outlining a new conceptual and methodological framework for the assessment of executive control task performance in VR. Results could help users to take human factors into consideration in order to fully exploit or predict the benefits of this tool.

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