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Caregiving Artificial Intelligence Chatbot for Older Adults: A Mixed-Methods Study on Their Preferences, Well-Being, and Social Connectivity (Preprint)

预印本 聊天机器人 心理学 社会支持 计算机科学 应用心理学 互联网隐私 万维网 老年学 社会心理学 医学
作者
Brooke H. Wolfe,Yoo Jung Oh,Hyesun Choung,Xiaoran Cui,Joshua Weinzapfel,R. Amanda Cooper,Hae-Na Lee,Rebecca H. Lehto
出处
期刊:Journal of Medical Internet Research [JMIR Publications]
标识
DOI:10.2196/65776
摘要

The increasing number of older adults who are living alone poses challenges for maintaining their well-being, as they often need support with daily tasks, health care services, and social connections. However, advancements in artificial intelligence (AI) technologies have revolutionized health care and caregiving through their capacity to monitor health, provide medication and appointment reminders, and provide companionship to older adults. Nevertheless, the adaptability of these technologies for older adults is stymied by usability issues. This study explores how older adults use and adapt to AI technologies, highlighting both the persistent barriers and opportunities for potential enhancements. This study aimed to provide deeper insights into older adults' engagement with technology and AI. The technologies currently used, potential technologies desired for daily life integration, personal technology concerns faced, and overall attitudes toward technology and AI are explored. Using mixed methods, participants (N=28) completed both a semistructured interview and surveys consisting of health and well-being measures. Participants then participated in a research team-facilitated interaction with an AI chatbot, Amazon Alexa. Interview transcripts were analyzed using thematic analysis, and surveys were evaluated using descriptive statistics. Participants' average age was 71 years (ranged from 65 years to 84 years). Most participants were familiar with technology use, especially using smartphones (26/28, 93%) and desktops and laptops (21/28, 75%). Participants rated appointment reminders (25/28, 89%), emergency assistance (22/28, 79%), and health monitoring (21/28, 75%). Participants rated appointment reminders (25/28, 89.3%), emergency assistance (22/28, 78.6%), and health monitoring (21/28, 75%) as the most desirable features of AI chatbots for adoption. Digital devices were commonly used for entertainment, health management, professional productivity, and social connectivity. Participants were most interested in integrating technology into their personal lives for scheduling reminders, chore assistance, and providing care to others. Challenges in using new technology included a commitment to learning new technologies, concerns about lack of privacy, and worries about future technology dependence. Overall, older adults' attitudes coalesced into 3 orientations, which we label as technology adapters, technologically wary, and technology resisters. These results illustrate that not all older adults were resistant to technology and AI. Instead, older adults are aligned with categories on a spectrum between willing, hesitant but willing, and unwilling to use technology and AI. Researchers can use these findings by asking older adults about their orientation toward technology to facilitate the integration of new technologies with each person's comfortability and preferences. To ensure that AI technologies effectively support older adults, it is essential to foster an ongoing dialogue among developers, older adults, families, and their caregivers, focusing on inclusive designs to meet older adults' needs.
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