Mapping artificial intelligence in older adult care: A bibliometric analysis - Report - MDSpire

Mapping artificial intelligence in older adult care: A bibliometric analysis

  • By

  • Zhiming Wei

  • Walton Wider

  • Changhe Wu

  • Choon Kit Chan

  • Yong Xu

  • Hao Wu

  • July 5, 2026

  • 0 min

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Clinical Report: Analyzing the Role of Artificial Intelligence in Geriatric Care

Background

As the global population ages, healthcare systems face significant challenges, including workforce shortages and rising demand for long-term care. Technological innovations, particularly AI, are being explored to enhance care delivery and improve quality of life for older adults. Understanding the dynamics of AI adoption in geriatric care is crucial for addressing these challenges effectively.

Data Highlights

No numerical data or trial results were provided in the source material.

Key Findings

  • AI technologies can assist in health monitoring, fall detection, cognitive assessment, and rehabilitation for older adults.
  • User acceptance of AI in geriatric care is influenced by perceived usefulness, ease of use, trust, and privacy concerns.
  • Successful implementation of AI requires consideration of ethical governance, user autonomy, and integration into existing care practices.
  • Cultural norms significantly affect attitudes toward AI-enabled care among older adults and caregivers.
  • Concerns regarding surveillance and the potential loss of human contact may hinder the adoption of AI technologies.

Clinical Implications

Healthcare professionals should be aware of the socio-technical factors that influence the acceptance of AI technologies among older adults.

Conclusion

AI has the potential to transform geriatric care, but its success relies on understanding and addressing the complex interactions between technology, users, and care systems.

Related Resources & Content

  1. World Health Organization, WHO, 2024 -- Ethics and governance of artificial intelligence for health: large multi-modal models
  2. Frontiers in Digital Health, 2026 -- Stakeholder experience with artificial intelligence in healthcare: a bibliometric study of satisfaction, trust, acceptance, and patient engagement
  3. British Journal of Biomedical Science, 2026 -- Artificial intelligence approaches in biological age prediction: current status and challenges
  4. DIGITAL HEALTH, 2024 -- Artificial intelligence in primary health care: A bibliometric analysis of publications from 2015 to 2024
  5. DIGITAL HEALTH — Global trends and hotspots of artificial intelligence in pain management: A bibliometric analysis
  6. Ethics and governance of artificial intelligence for health: large multi-modal models. WHO guidance
  7. Machine Learning and Deep Learning Models for Predicting Future Falls in Community-Dwelling Older Adults: Systematic Review and Meta-Analysis of Longitudinal Evidence - PMC
  8. Frontiers | AI-driven telerehabilitation for older adults with mild cognitive impairment: a randomized controlled trial

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