老年人护理中对类人社交机器人态度的决定因素:一项互动后研究。

Sławomir Tobis, Joanna Piasek-Skupna, Agnieszka Neumann-Podczaska, Urszula Religioni, Aleksandra Suwalska
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引用次数: 0

摘要

虽然越来越多的研究调查了老年人护理中社交机器人的观点,但缺乏对影响这些观点的潜在因素的全面研究。Godspeed问卷系列(GQS)测量与人机交互(HRIs)相关的感知。综合老年评估(Comprehensive Geriatric Assessment, CGA)被广泛用于评估老年患者的身体、认知和社会功能。EASYCare 2010标准(EC)是评估老年人未满足需求的工具。TIAGo是一款集感知、导航和HRI功能于一体的社交类人机器人。本研究旨在利用GQS、选定的CGA项目和EC,确定老年人与TIAGo相互作用后感知的决定因素。材料和方法基于用户需求、要求和能力问卷,我们分析了与TIAGo互动的老年人的意见数据库。我们研究了机器人的角色(同伴/助手/有用设备)、辅助/社交功能以及老年参与者的各种特征之间的关系。结果本研究纳入161名参与者(平均年龄:75.2±9.8岁),其中女性89名,住院患者113名。机器人的角色、功能和参与者之间存在正相关关系;对大多数评估参数(拟人化、Animacy、受欢迎程度、感知智力、感知安全性)的感知。在其他参数中只发现了很少的个别相关性。结论老年人意见的主要决定因素是他们对机器人的感知。因此,让老年人参与此类机器人的协同设计过程至关重要。此外,在类人社交机器人的研究中,需要进行范式转变,将重点放在成功的衰老上,而不是与衰老相关的缺陷上。
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Determinants of Attitude to a Humanoid Social Robot in Care for Older Adults: A Post-Interaction Study.

BACKGROUND While there is a growing body of research examining opinions on social robots in elderly care, there is a lack of comprehensive studies investigating the underlying factors influencing these opinions. The Godspeed Questionnaire Series (GQS) measures perceptions related to human-robot interactions (HRIs). The Comprehensive Geriatric Assessment (CGA) is widely used to evaluate physical, cognitive, and social functions of older patients. The EASYCare 2010 Standard (EC) is a tool for assessing unmet needs in older individuals. TIAGo, a social humanoid robot, integrates perception, navigation, and HRI capabilities. This study aimed to identify the determinants of perception following interactions between older individuals and TIAGo, utilizing the GQS, selected CGA items, and EC. MATERIAL AND METHODS We analyzed a database of opinions from older individuals who interacted with TIAGo, based on the Users' Needs, Requirements, and Abilities Questionnaire. We examined the relationships between the robot's roles (companion/assistant/useful device), its assistive/social functions, and various characteristics of the older participants. RESULTS The study included 161 participants (mean age: 75.2±9.8 years), comprising 89 women and 113 institutionalized individuals. Positive correlations were observed between the robot's role, its functions, and the participants'; perceptions across most evaluated parameters (Anthropomorphism, Animacy, Likeability, Perceived intelligence, Perceived safety). Only a few individual correlations were found for other parameters. CONCLUSIONS The primary determinant of older individuals' opinions was their perception of the robot. Therefore, involving older adults in the co-design process of such robots is crucial. Additionally, a paradigm shift is needed in the study of humanoid social robots, focusing on successful aging rather than deficits associated with aging.

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