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Validating an Efficient Method to Quantify Motion Sickness

机译:验证量化晕动病的有效方法

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Objective: Motion sickness (MS) can be a debilitating side effect associated with motion in real or virtual environments. We analyzed the effect of expectancy on MS and propose and validate a fast and simple MS measure. Background: Several questionnaires measure MS before or after stimulus presentation, but no satisfactory tool has been established to quickly capture MS data during exposure. To fill this gap, we introduce the Fast MS Scale (FMS), a verbal rating scale ranging from zero (no sickness at all) to 20 (frank sickness). Also, little is known about the role of expectancy effects in MS studies. We conducted an experiment that addressed this issue. Method: For this study, 126 volunteers participated in two experiments. During stimulus presentation, participants had to verbally rate the severity of MS every minute before filling in the Simulator Sickness Questionnaire (SSQ). To measure expectancy effects, participants were separated into three groups with either positive, negative, or neutral expectations. Results: We compared the verbal ratings with the SSQ scores. Pearson correlations were high for both the SSQ total score (r = .785) and the nausea subscore (r = .828). No expectancy effects were found. Conclusion: The FMS is a fast and valid method to obtain MS data. It offers the possibility to record MS during stimulus presentation and to capture its time course. We found expectancy not to play a crucial role in MS. However, the FMS has some limitations. Application: The FMS offers improved MS measurement. It is fast and efficient and can be performed online in environments such as virtual reality.
机译:目的:晕车(MS)可能是与真实或虚拟环境中的运动相关的令人衰弱的副作用。我们分析了预期对MS的影响,并提出并验证了一种快速,简单的MS测量方法。背景:几份问卷在刺激出现之前或之后测量MS,但尚未建立令人满意的工具来在暴露期间快速捕获MS数据。为了填补这一空白,我们引入了快速MS量表(FMS),这是一种口头评价量表,范围从零(根本没有疾病)到20(坦率疾病)。同样,对于MS研究中预期效应的作用了解甚少。我们进行了解决此问题的实验。方法:本研究共有126名志愿者参加了两个实验。在进行刺激刺激期间,参与者必须在填写《模拟病态问卷》(SSQ)之前,每分钟对MS的严重程度进行口头评估。为了衡量预期效果,将参与者分为积极,消极或中立的三组。结果:我们将口头评价与SSQ得分进行了比较。 SSQ总分(r = .785)和恶心评分(r = .828)的Pearson相关性都很高。未发现预期效果。结论:FMS是一种快速有效的获取MS数据的方法。它提供了在刺激提示过程中记录MS并捕获其时程的可能性。我们发现期望值在MS中不发挥关键作用。但是,FMS有一些限制。应用:FMS提供改进的MS测量。它快速有效,可以在虚拟现实等环境中在线执行。

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