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

Authors

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

Published in

The journals of gerontology. Series A, Biological sciences and medical sciences. Sep 21, 2026. Epub Sep 21, 2026.

Abstract

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.
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.
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).
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.

PMID:
42765524
Bibliographic data and abstract were imported from PubMed on 21 Sep 2026.

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