Igarashi Toshiharu, Iijima Katsuya, Nitta Kunio, Chen Yu
Simulation of Complex Systems Laboratory, Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 277-8563, Japan.
AI-UX Design Research Institution, Advanced Institute of Industrial Technology, 10-40 Higashi-Oi 1-Chome, Shinagawa, Tokyo 140-0011, Japan.
Healthcare (Basel). 2024 Sep 11;12(18):1821. doi: 10.3390/healthcare12181821.
In recent years, an increasing number of studies have begun to use conversational data in spontaneous speech to estimate cognitive function in older people. The targets of spontaneous speech with older people used to be physicians and licensed psychologists, but it is now possible to have conversations with fully automatic AI agents. However, it has not yet been clarified what difference there is in conversational communication with older people when the examiner is a human or an AI agent. This study explored the psychological burden experienced by elderly participants during cognitive function assessments, comparing interactions with human and AI conversational partners. Thirty-four participants, averaging 78.71 years of age, were evaluated using the Mini-Mental State Examination (MMSE), the Visual Analogue Scale (VAS), and the State-Trait Anxiety Inventory (STAI). The objective was to assess the psychological impact of different conversational formats on the participants. The results indicated that the mental strain, as measured by VAS and STAI scores, was significantly higher during the MMSE sessions compared to other conversational interactions ( < 0.01). Notably, there was no significant difference in the mental burden between conversations with humans and AI agents, suggesting that AI-based systems could be as effective as human interaction in cognitive assessments.
近年来，越来越多的研究开始使用自然语言中的对话数据来评估老年人的认知功能。过去与老年人进行自然语言交流的对象是医生和有执照的心理学家，但现在已经可以与全自动人工智能代理进行对话。然而，当考官是人类或人工智能代理时，与老年人进行对话交流有何不同尚未明确。本研究通过比较与人类和人工智能对话伙伴的互动，探讨了老年参与者在认知功能评估过程中所经历的心理负担。使用简易精神状态检查表（MMSE）、视觉模拟量表（VAS）和状态-特质焦虑量表（STAI）对34名平均年龄为78.71岁的参与者进行了评估。目的是评估不同对话形式对参与者的心理影响。结果表明，与其他对话互动相比，MMSE测试期间通过VAS和STAI分数衡量的精神压力显著更高（<0.01）。值得注意的是，与人类和人工智能代理对话时的心理负担没有显著差异，这表明基于人工智能的系统在认知评估中可能与人际互动一样有效。
