Mind the Gap: The Underrepresentation of Female Participants and Authors in Virtual Reality Research

虚拟现实 模拟病 人口 计算机科学 应用心理学 样品(材料) 心理学 主题(文档) 人机交互 医学 化学 环境卫生 色谱法 图书馆学
作者
Tabitha C. Peck,Laura E. Sockol,Sarah Hancock
出处
期刊:IEEE Transactions on Visualization and Computer Graphics [Institute of Electrical and Electronics Engineers]
卷期号:26 (5): 1945-1954 被引量:115
标识
DOI:10.1109/tvcg.2020.2973498
摘要

A common goal of human-subject experiments in virtual reality (VR) research is evaluating VR hardware and software for use by the general public. A core principle of human-subject research is that the sample included in a given study should be representative of the target population; otherwise, the conclusions drawn from the findings may be biased and may not generalize to the population of interest. In order to assess whether characteristics of participants in VR research are representative of the general public, we investigated participant demographic characteristics from human-subject experiments in the Proceedings of the IEEE Virtual Reality Conferences from 2015-2019. We also assessed the representation of female authors. In the 325 eligible manuscripts, which presented results from 365 human-subject experiments, we found evidence of significant underrepresentation of women as both participants and authors. To investigate whether this underrepresentation may bias researchers' findings, we then conducted a meta-analysis and meta-regression to assess whether demographic characteristics of study participants were associated with a common outcome evaluated in VR research: the change in simulator sickness following head-mounted display VR exposure. As expected, participants in VR studies using HMDs experienced small but significant increases in simulator sickness. However, across the included studies, the change in simulator sickness was systematically associated with the proportion of female participants. We discuss the negative implications of conducting experiments on non-representative samples and provide methodological recommendations for mitigating bias in future VR research.
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