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应用数据挖掘技术预测非裔美国家庭在家中使用机器人进行痴呆症护理的感知收益与风险

Applying Data Mining to Predict Perceived Benefits Risks of Robotics at Home for Dementia Caregiving Among African American Families.

作者信息

Yoon Sunmoo, Sun Frederick, Patterson Melissa, Crupi Robert, Broadwell Peter, Pottinger Tess, Kim Milea, Davis Nicole

机构信息

General Medicine, Columbia University, New York, NY.

New York Presbyterian Hospital, New York, NY.

出版信息

Stud Health Technol Inform. 2025 Apr 8;323:61-65. doi: 10.3233/SHTI250049.

Abstract

We used data mining to predict the attitudes of 527 caregivers towards the pros and cons of using robotics and artificial intelligence (AI) for dementia care in African American families, with a focus on family-level factors. African American family caregivers would prefer using AI home attendant for caregiving, even though there are associated costs, and see the benefits of using AI robots to improve family dynamics, despite the need for the AI to collect sensitive data. In contrast, white family caregivers aged 25-34 are more likely to perceive the risks of using AI robots for this purpose. The proposed AI smart home system evaluates care quality and assists families in nursing home decisions. However, specific groups are hesitant to embrace its benefits. This highlights the need for in-depth research to address concerns and communicate potential advantages effectively.

摘要

我们运用数据挖掘技术,预测了527名护理人员对非裔美国家庭中使用机器人技术和人工智能(AI)进行痴呆症护理的利弊的态度,重点关注家庭层面的因素。非裔美国家庭护理人员更倾向于使用人工智能家庭护理助手进行护理,尽管存在相关成本,并且认为使用人工智能机器人有助于改善家庭关系,尽管人工智能需要收集敏感数据。相比之下,年龄在25 - 34岁的白人家庭护理人员更有可能察觉到为此目的使用人工智能机器人的风险。所提议的人工智能智能家居系统可评估护理质量,并协助家庭做出养老院决策。然而,特定群体对接受其益处持犹豫态度。这凸显了进行深入研究以解决相关担忧并有效传达潜在优势的必要性。

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Experiences and Learning Needs of African American Family Dementia Caregivers.非裔美国家庭痴呆症护理者的经历与学习需求
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