Acceptance of AI-Based Assistive Technologies for Autonomy Support Among Older Adults: A Scoping Review.

Sekou Oumarou Thera, Ali Ben Charif, Jeanne Bertona, Patrick Villani, Sébastien Lechevallier, Marc-Karim Bendiane, Anne-Laure Couderc
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Abstract

Background: Population aging is leading to increased demand for health and long-term care. AI-based assistive technologies have been developed to support autonomy and care for older adults, yet real‑world adoption remains limited. We review evidence on acceptance and determinants of acceptance of AI‑based assistive technologies among older adults.

Methods: We conducted a scoping review using the JBI methodology and followed PRISMA‑ScR guidelines for reporting. Four databases (PubMed, Embase, Web of Science, Cochrane) were searched for studies published from January 2010 to June 2025, initially in any language. We included studies examining acceptance and determinants of acceptance of AI-based assistive technologies among adults aged 65 years and older. We synthesized data using inductive thematic analysis.

Results: Twenty‑nine studies met the inclusion criteria, with over one-third conducted in Europe (n = 10). Overall attitudes toward AI‑based assistive technologies were generally favorable when technologies were perceived as useful, easy to use, and tailored to needs. However, actual use was low. Acceptance was associated with socio‑demographic (e.g., age, residence), medical (e.g., frailty, self‑rated health), psychosocial (e.g., stigma), and structural (e.g., cost, accessibility) determinants, as well as with institutional and relational factors (e.g., preservation of human contact).

Conclusions: While older adults have generally positive views of AI‑based assistive technologies, adoption is slow because of intersecting psychosocial, economic, technical, and organizational barriers. User‑centered design, care-led innovation approaches, and implementation strategies that complement-rather than replace-human support may facilitate uptake and sustained use. Development of standardized assessment tools is needed to enable cross-study comparability and guide future research.

接受基于人工智能的辅助技术为老年人的自主支持:范围审查。
背景:人口老龄化导致对健康和长期护理的需求增加。基于人工智能的辅助技术已经被开发出来,以支持老年人的自主和护理,但现实世界的采用仍然有限。我们回顾了老年人接受基于人工智能的辅助技术的证据和决定因素。方法:我们使用JBI方法进行了范围审查,并遵循PRISMA - ScR报告指南。四个数据库(PubMed, Embase, Web of Science, Cochrane)检索了从2010年1月到2025年6月发表的研究,最初以任何语言发表。我们纳入了调查65岁及以上成年人对基于人工智能的辅助技术的接受程度和决定因素的研究。我们使用归纳主题分析来综合数据。结果:29项研究符合纳入标准,其中超过三分之一在欧洲进行(n = 10)。当人们认为基于人工智能的辅助技术有用、易于使用并能满足需求时,人们对这些技术的总体态度通常是有利的。然而,实际使用量很低。接受与社会人口因素(如年龄、居住地)、医疗因素(如虚弱、自我评估的健康状况)、心理社会因素(如耻辱)和结构因素(如成本、可及性)以及体制和关系因素(如保持人际接触)有关。结论:虽然老年人普遍对基于人工智能的辅助技术持积极态度,但由于交叉的社会心理、经济、技术和组织障碍,采用速度缓慢。以用户为中心的设计、以护理为主导的创新方法以及补充(而不是取代)人力支持的实施战略,可能促进吸收和持续使用。需要开发标准化的评估工具,以实现交叉研究的可比性并指导未来的研究。
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