选择性列举任务中面部表情的影响:以悲伤表情为中心的研究

Kei Kobayashi, T. Kasai
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引用次数: 0

摘要

当与多人交流时,在评估情况时,了解具有特定面部表情的人数是至关重要的。之前的一项关于情绪面孔数量估计的研究发现,与中性面孔相比,愤怒面孔的准确性较低,并且被低估(Baker, Rodzon, & Jordan, 2013)。然而,本研究中使用的任务是对相同的面部图像(即相同的个体和表情)进行简单的枚举;在现实生活中不常发生的情况。此外,之前的研究只考虑了愤怒的表情,但不同的面部表情有特定的功能。因此,本研究将重点放在悲伤表达上,以探讨其对枚举的影响。悲伤表达传达了失落,并引起他人的同情和亲社会行为。参与者的任务是从微笑和中性或悲伤和中性的面部表情组合中列举出特定的面部表情,这些表情的显示时间为500毫秒。当出现多个目标时,与微笑的脸相比,悲伤脸的准确率更低,计数被低估了。这些结果表明,带有悲伤情绪的面孔在简短呈现时会阻碍计数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effects of facial expressions in selective enumeration tasks: A study focusing on sad expressions
Effects When communicating with multiple others, it is vital to understand the approximate number of people with a particular facial expression when assessing a situation. A previous study of numerosity estimations for emotional faces observed lower accuracy and underestimations for angry faces compared to neutral faces ( Baker, Rodzon, & Jordan, 2013 ) . However, the task used in this study was a simple enumeration for an iden-tical face image ( i.e., same individual and expression ) ; a situation that does not usually occur in real life. Moreover, the previous research only considered angry faces, but different facial expressions have specific functions. Accordingly, the present study focuses on sad expressions, which convey losses and elicit empathy and prosocial behavior from others, to investigate their effects on enumeration. The participants ’ task was to enumerate only certain facial expressions, from among combinations of smiling and neutral or sad and neutral faces, which were displayed for 500 milliseconds. When multiple targets were presented, accuracy for sad faces was lower compared to smiling faces and counts were underestimated. These results suggest that faces with sad emotions hinder enumeration when briefly presented.
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