Mapping artificial intelligence in older adult care: A bibliometric analysis

Area of Science:

• Gerontology
• Artificial Intelligence
• Health Informatics

Background:

• The field of artificial intelligence (AI) in older adult care is rapidly expanding.
• Understanding the intellectual structure and development trends is crucial for future research and application.

Purpose of the Study:

• To map the intellectual structure and conceptual development of AI research in older adult care.
• To identify current research fronts and emerging thematic priorities in this domain.

Main Methods:

• Bibliometric analysis of 5,214 articles from 2004-2025 in Web of Science Core Collection.
• VOSviewer software used for analysis, employing bibliographic coupling and co-word analysis.
• Bibliographic coupling identified research fronts; co-word analysis revealed conceptual themes.

Main Results:

• The field shows significant growth, with 79,858 citations and an h-index of 102.
• Five major research fronts identified, including predictive health intelligence, assistive robotics, fall detection, service robots, and rehabilitation technologies.
• Four dominant conceptual themes emerged: health risk and aging outcomes, AI-enabled care technologies, mobility and functional aging, and machine learning for cognitive impairment prediction.

Conclusions:

• AI research in older adult care has evolved towards integrated socio-technical ecosystems.
• Future AI systems should be human-centered, clinically meaningful, ethically governed, and socially sustainable.
• Addressing the multidimensional needs of aging populations is key for advancing AI-enabled care.