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Lookup NU author(s): Professor Matthew Prina
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© 2022 World Health OrganizationArtificial intelligence (AI)-enhanced interventions show promise for improving the delivery of long-term care (LTC) services for older people. However, the research field is developmental and has yet to be systematically synthesised. This systematic review aimed to synthesise the literature on the acceptability and effectiveness of AI-enhanced interventions for older people receiving LTC services. We conducted a systematic search that identified 2720 records from Embase, Ovid, Global Health, PsycINFO, and Web of Science. 31 articles were included in the review that evaluated AI-enhanced social robots (n=22), environmental sensors (n=6), and wearable sensors (n=5) with older people receiving LTC services across 15 controlled and 14 non-controlled trials in high-income countries. Risk of bias was evaluated using the RoB 2, RoB 2 CRT, and ROBINS-I tools. Overall, AI-enhanced interventions were found to be somewhat acceptable to users with mixed evidence for their effectiveness across different health outcomes. The included studies were found to have high risk of bias which reduced confidence in the results. AI-enhanced interventions are promising innovations that could reshape the landscape of LTC globally. However, more trials are required to support their widespread implementation. Pathways are needed to support more high-quality trials, including in low-income and middle-income countries.
Author(s): Loveys K, Prina M, Axford C, Domenec OR, Weng W, Broadbent E, Pujari S, Jang H, Han ZA, Thiyagarajan JA
Publication type: Review
Publication status: Published
Journal: The Lancet Healthy Longevity
Year: 2022
Volume: 3
Issue: 4
Pages: e286-e297
Print publication date: 01/04/2022
Online publication date: 04/04/2022
Acceptance date: 02/04/2022
ISSN (electronic): 2666-7568
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/S2666-7568(22)00034-4
DOI: 10.1016/S2666-7568(22)00034-4
