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

Area of Science:

• Geriatric Health
• Artificial Intelligence
• Digital Health

Background:

• Population aging presents a global challenge requiring effective self-care and health management solutions for older adults.
• Generative artificial intelligence (GenAI) is increasingly applied in healthcare, necessitating an evaluation of its role in supporting geriatric well-being.

Purpose of the Study:

• To systematically evaluate the role, application contexts, empirical impacts, and developmental potential of diverse GenAI tools in geriatric health.

Main Methods:

• A systematic search was conducted across 11 major databases, adhering to PRISMA-S guidelines for scoping reviews.
• Included 28 studies, with 82% published between 2024-2025, focusing on GenAI applications for older adults' health.

Main Results:

• Over half of GenAI applications were text-based, but multimodal systems (audio, images, sensor data) are emerging.
• GenAI demonstrated support for cognitive function, mental health, and chronic condition management via personalized content and interaction.
• Current validation is limited to cognitively normal, low-risk older adults, with technical challenges including voice recognition and UI adaptability.

Conclusions:

• GenAI shows potential for personalized, multimodal health interventions in older adults, especially for cognitive and mental health.
• Future efforts should focus on interdisciplinary collaboration, integrating wearables and edge computing.
• Establishing robust ethical frameworks is crucial to address data privacy, bias, and the digital divide for equitable active aging.