面部情绪识别在衰老和痴呆中的评估。新工具的开发

Cátia Carvalho , Manuela Páris , Miguel Lemos , Bruno Peixoto
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引用次数: 9

摘要

从面部表情中识别情绪是人类的基本能力。衰老过程与这种能力的下降有关,尤其是在识别负面情绪方面。这种减少在痴呆症的情况下更为突出。尽管对情绪识别的研究越来越多,但缺乏能够识别衰老和痴呆的个体差异的工具。这项工作旨在确定面部情绪识别任务(Gandra-BARTA)的心理测量特性。样本由三组组成:青年(YA)组(n = 12);老年组(OA) 17例;阿尔茨海默病(AD)组(n = 26),由诊断可能为AD的受试者组成。Gandra-BARTA表现出良好的内部一致性。与YA相比,OA组花了更多的时间来完成Gandra-BARTA,正确的情绪识别较少,并且他们对愤怒和中性情绪的面部表情的识别不足。另一方面,与OA组相比,AD组在Gandra-BARTA的各个方面都表现最差,除了悲伤和恐惧的识别。在Gandra-BARTA上,正确识别的临界值为24分,区分OA和AD的敏感性为100%,特异性为88.5%。Gandra-BARTA显示出良好的内部一致性,使其成为评估从面部表情中识别情绪能力的可靠工具。它也被证明对衰老和痴呆的变化敏感,对AD有很高的判别效度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessment of facial emotions recognition in aging and dementia. The development of a new tool

The recognition of emotions from facial expressions is a basic human aptitude. The aging process is related with a decrease of this ability, particularly in the recognition of negative emotions. This decrease is more prominent in the context of dementia. Despite the growing of researches on emotion recognition, there is a lack of instruments capable of identifying individual differences regarding aging and dementia. This work aims to determine the psychometric properties of a facial emotion recognition task (Gandra-BARTA). The sample is composed by three groups: Young Adults (YA) group (n = 12); Old Adults (OA) group (n = 17); Alzheimer's Disease (AD) group (n = 26), made up of subjects with diagnosis of probable AD. The Gandra-BARTA showed good internal consistency. In comparison to the YA, the OA group took more time to complete Gandra-BARTA, had less correct emotional identifications and they have under-recognized facial expressions of rage and neutral emotions. On the other hand, the AD group showed worst performance on every aspect of the Gandra-BARTA when compared to the OA group, except in the identification of sadness and fear. A cutoff score of 24 correct recognitions on Gandra-BARTA differentiate OA from AD subjects with a sensibility of 100% and a specificity of 88.5%. The Gandra-BARTA revealed good internal consistency making it a reliable instrument to assess the ability to recognize emotions from facial expressions. It also proved to be sensitive to changes in aging and dementia with high discriminant validity for AD.

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