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Induction and profiling of strong multi-componential emotions in virtual reality
IEEE Transactions on Affective Computing ( IF 11.2 ) Pub Date : 2018-01-01 , DOI: 10.1109/taffc.2018.2864730
Ben Meuleman , David Rudrauf

Psychological theories of emotion have often defined an emotion as simultaneous changes in several mental and bodily components. In addition, appraisal theories assume that an appraisal component elicits changes in the other emotion components (e.g., motivational, behavioural, experiential). Neither the componential definition of emotion nor appraisal theory have been systematically translated to paradigms for emotion induction, many of which rely on passive emotion induction without a clear theoretical framework. As a result, the observed emotions are often weak. This study explored the potential of virtual reality (VR) to evoke strong emotions in ecologically valid scenarios that fully engaged the mental and bodily components of the participant. Participants played several VR games and reported on their emotions. Multivariate analyses using hierarchical clustering and multilevel linear modelling showed that participants experienced intense, multi-componential emotions in VR. We identified joy and fear clusters of responses, each involving changes in appraisal, motivation, physiology, feeling, and regulation. Appraisal variables were found to be the most predictive for fear and joy intensities, compared to other emotion components, and were found to explain individual differences in VR scenarios, as predicted by appraisal theory. The results advocate upgraded methodologies for the induction and analysis of emotion processes.

中文翻译:

虚拟现实中强烈的多成分情绪的归纳和分析

情绪的心理学理论通常将情绪定义为几种心理和身体成分的同时变化。此外,评估理论假设评估成分会引起其他情绪成分(例如,动机、行为、体验)的变化。情绪的成分定义和评价理论都没有系统地转化为情绪诱导的范式,其中许多依赖于被动的情绪诱导,没有明确的理论框架。因此,观察到的情绪往往很弱。本研究探索了虚拟现实 (VR) 在生态有效场景中唤起强烈情绪的潜力,这些场景充分调动了参与者的心理和身体成分。参与者玩了几个 VR 游戏并报告了他们的情绪。使用层次聚类和多级线性建模的多变量分析表明,参与者在 VR 中体验到强烈的、多成分的情绪。我们确定了快乐和恐惧的反应群,每一个都涉及评价、动机、生理、感觉和调节的变化。与其他情绪成分相比,评估变量被发现最能预测恐惧和快乐的强度,并且发现评估变量可以解释 VR 场景中的个体差异,正如评估理论所预测的那样。结果提倡对情绪过程的归纳和分析进行升级的方法。生理、感觉和调节。与其他情绪成分相比,评估变量被发现最能预测恐惧和快乐的强度,并且发现评估变量可以解释 VR 场景中的个体差异,正如评估理论所预测的那样。结果提倡对情绪过程的归纳和分析进行升级的方法。生理、感觉和调节。与其他情绪成分相比,评估变量被发现最能预测恐惧和快乐的强度,并且发现评估变量可以解释 VR 场景中的个体差异,正如评估理论所预测的那样。结果提倡对情绪过程的归纳和分析进行升级的方法。
更新日期:2018-01-01
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