AI in Home Care-Evaluation of Large Language Models for Future Training of Informal Caregivers: Observational Comparative Case Study.

Journal: Journal of medical Internet research
PMID:

Abstract

BACKGROUND: The aging population presents an accomplishment for society but also poses significant challenges for governments, health care systems, and caregivers. Elevated rates of functional limitations among older adults, primarily caused by chronic conditions, necessitate adequate and safe care, including in-home settings. Traditionally, informal caregiver training has relied on verbal and written instructions. However, the advent of digital resources has introduced videos and interactive platforms, offering more accessible and effective training. Large language models (LLMs) have emerged as potential tools for personalized information delivery. While LLMs exhibit the capacity to mimic clinical reasoning and support decision-making, their potential to serve as alternatives to evidence-based professional instruction remains unexplored.

Authors

  • Clara Pérez-Esteve
    Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana, Centro de Salud Hospital-Plá, Alicante, Spain.
  • Mercedes Guilabert
    Health Psychology Department, Miguel Hernandez University, Elche, Spain.
  • Valerie Matarredona
    Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana, Alicante, Spain.
  • Einav Srulovici
    Department of Nursing, University of Haifa, Haifa, Israel.
  • Susanna Tella
    Health and Wellbeing Department, LAB University of Applied Sciences, Lappeenranta, Finland.
  • Reinhard Strametz
    Wiesbaden Institute for Healthcare Economics and Patient Safety, RheinMain University of Applied Sciences, Wiesbaden, Germany.
  • José Joaquín Mira
    Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana, Centro de Salud Hospital-Plá, Alicante, Spain.