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Accepted for/Published in: JMIR AI

Date Submitted: Sep 23, 2025
Date Accepted: Mar 28, 2026

The final, peer-reviewed published version of this preprint can be found here:

The Role of Multimodal Generative AI in Older Adults’ Health Management: Systematic Scoping Review

Liu T, Luo YT, Pang PCI, Zhang H, Xiang A, Yang Q

The Role of Multimodal Generative AI in Older Adults’ Health Management: Systematic Scoping Review

JMIR AI 2026;5:e84695

DOI: 10.2196/84695

PMID: 42213458

The Role of Multi-modal Generative AI in Older Adults' Health Management: A Systematic Scoping Review

  • Ting Liu; 
  • Yiming Taclis Luo; 
  • Patrick Cheong-Iao Pang; 
  • Haopeng Zhang; 
  • Ao Xiang; 
  • Qin Yang

ABSTRACT

Background:

The issue of population aging has emerged as a critical global challenge, with effective self-care and health management for older adults representing a pivotal solution to addressing geriatric health concerns. Against the backdrop of the widespread application of generative artificial intelligence (GenAI) in healthcare and management, it is imperative to investigate how Multi-modal GenAI can support older adults in maintaining health and managing well-being.

Objective:

This study aims to systematically evaluate the role of GenAI in assisting older adults with health maintenance and management, comprehensively analyzing the application contexts, impacts, and developmental potential of diverse GAI tools across various health domains.

Methods:

This study followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. A comprehensive search was conducted across eleven databases (Web of Science, Scopus, PubMed, Medline, CINAHL, Cochrane, ACM Digital Library, IEEE Xplore, ScienceDirect, APA PsycInfo, and Google Scholar). A total of 26 articles were ultimately included in the study.

Results:

GenAI tools effectively contribute to cognitive function maintenance, mental health support, and health condition management through personalized content generation and multimodal interaction. However, current applications are predominantly limited to cognitively normal, low-risk elderly populations, with insufficient coverage of high-risk groups and marginalized populations. Technical challenges persist, including over-reliance on text-based interaction, barriers in voice recognition, and suboptimal interface adaptability for elderly users. Ethical concerns such as data privacy risks and algorithmic bias remain under-addressed.

Conclusions:

GenAI’s promising role in enhancing older adults’ health self-management through personalized and multimodal interventions, particularly in cognitive and mental health support. Strengthening interdisciplinary collaboration to integrate wearable technologies and edge computing, while establishing robust ethical frameworks for data privacy and fairness, will be critical to building a safe, equitable, and effective environment for active aging.


 Citation

Please cite as:

Liu T, Luo YT, Pang PCI, Zhang H, Xiang A, Yang Q

The Role of Multimodal Generative AI in Older Adults’ Health Management: Systematic Scoping Review

JMIR AI 2026;5:e84695

DOI: 10.2196/84695

PMID: 42213458

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