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Mapping artificial intelligence in older adult care: A bibliometric analysis
Zhiming Wei1, Walton Wider2, Changhe Wu2
1Jiangsu Medical College, Yancheng, China.
Objective:
This study aimed to map the intellectual structure and conceptual development of artificial intelligence (AI) research in older adult care by identifying current research fronts and emerging thematic priorities.
Methods:
A bibliometric analysis was conducted using 5,214 English-language journal articles indexed in the Web of Science Core Collection between 2004 and 2025. Bibliographic records were analysed using VOSviewer. Bibliographic coupling was employed to identify contemporary research fronts based on shared reference patterns, while co-word analysis examined conceptual structures and emerging research themes through keyword co-occurrence.
Results:
The field demonstrated substantial scholarly growth and influence, accumulating 79,858 citations, 74,375 non-self-citations, and an h-index of 102. Bibliographic coupling analysis identified five major research fronts: predictive health intelligence and assistive support; assistive robotics, cognitive support, and ageing-in-place technologies; fall detection, cognitive ageing, and assistive technologies for functional independence; service robots, smart environments, and human-AI acceptance; and rehabilitation, fall prevention, and age-friendly mobility environments. Co-word analysis revealed four dominant conceptual themes: health risk, frailty, and population-level ageing outcomes; AI-enabled care technologies and human-robot interaction; mobility, physical activity, and functional ageing; and machine learning, dementia, and cognitive impairment prediction.
Conclusions:
AI research in older adult care has evolved from isolated technological applications toward integrated socio-technical care ecosystems that support prevention, monitoring, diagnosis, rehabilitation, mobility, and quality-of-life enhancement. Future advances will depend on the development of human-centred, clinically meaningful, ethically governed, and socially sustainable AI-enabled care systems that address the multidimensional needs of ageing populations.
