Faculty of Psychology, UniDistance Suisse, Ueberlandstrasse 12, 3900, Brig, Switzerland.
Department of Psychology, University of Bern, Bern, Switzerland.
Psychol Res. 2023 Feb;87(1):59-83. doi: 10.1007/s00426-022-01661-3. Epub 2022 Feb 28.
Bodily sensation mapping (BSM) is a recently developed self-report tool for the assessment of emotions in which people draw their sensations of activation in a body silhouette. Following the circumplex model of affect, activity and valence are the underling dimensions of every emotional experience. The aim of this study was to introduce the neglected valence dimension in BSM. We found that participants systematically report valence-related sensations of bodily lightness for positive emotions (happiness, love, pride), and sensations of bodily heaviness in response to negative emotions (e.g., anger, fear, sadness, depression) with specific body topography (Experiment 1). Further experiments showed that both computers (using a machine learning approach) and humans recognize emotions better when classification is based on the combined activity- and valence-related BSMs compared to either type of BSM alone (Experiments 2 and 3), suggesting that both types of bodily sensations reflect distinct parts of emotion knowledge. Importantly, participants found it clearer to indicate their bodily sensations induced by sadness and depression in terms of bodily weight than bodily activity (Experiment 2 and 4), suggesting that the added value of valence-related BSMs is particularly relevant for the assessment of emotions at the negative end of the valence spectrum.
躯体感觉映射(BSM)是一种最近开发的自我报告工具,用于评估情绪,人们在身体轮廓上画出自己的激活感觉。根据情感的双因素模型,活动和效价是每种情绪体验的基础维度。本研究的目的是在 BSM 中引入被忽视的效价维度。我们发现参与者系统地报告与正性情绪(如幸福、爱、自豪)相关的躯体轻盈感觉,以及与负性情绪(如愤怒、恐惧、悲伤、抑郁)相关的躯体沉重感觉,并且具有特定的身体拓扑结构(实验 1)。进一步的实验表明,当分类基于与活动和效价相关的 BSM 的组合时,计算机(使用机器学习方法)和人类对情绪的识别效果更好,而不是仅基于任一种类型的 BSM(实验 2 和 3),这表明两种类型的躯体感觉都反映了情绪知识的不同部分。重要的是,与躯体活动相比,参与者发现以躯体重量来表示悲伤和抑郁引起的躯体感觉更为清晰(实验 2 和 4),这表明效价相关 BSM 的附加价值对于评估效价谱负端的情绪特别相关。