To explore the role of artificial intelligence (AI) in geriatric care and understand its implications within a socio-technical framework.
Approach:
Socio-Technical Systems Theory: The study employs Socio-Technical Systems Theory to analyze the interactions among technological systems, human actors, and organizational structures in AI-enabled care for older adults.
Key Findings:
AI technologies can enhance health monitoring, fall detection, cognitive assessment, and care coordination for older adults.
User acceptance of AI in geriatric care is influenced by perceived usefulness, ease of use, trust, privacy, and cultural expectations.
Concerns about surveillance, algorithmic decision-making, and loss of human contact affect the willingness of older adults to adopt AI technologies.
Cultural contexts significantly shape attitudes toward AI-enabled care, influencing perceptions of trustworthiness and autonomy.
Interpretation:
The effectiveness of AI in geriatric care relies on both technological performance and the socio-cultural environment, including trust and ethical considerations.
Limitations:
Existing bibliometric studies often focus narrowly on publication metrics or specific technologies, lacking a comprehensive view of the AI-enabled care ecosystem.
Many studies do not adequately differentiate between established knowledge and emerging trends in AI research for older adults.
Conclusion:
Understanding AI in geriatric care requires a holistic view that incorporates technological, clinical, behavioral, environmental, and ethical dimensions.
