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In the face of a rapidly aging population and the increasing demand for elderly care, the adoption of artificial intelligence (AI) in healthcare products has emerged as a promising solution to enhance service delivery. This paper investigates the behavioral evolution of multiple stakeholders-namely, government entities, AI healthcare enterprises, and medical professionals-in the adoption process of AI-enabled elderly care products. By employing an evolutionary game theory model, we analyze the stability strategies of these stakeholders under varying initial conditions. Our findings reveal that government subsidies and regulatory measures play a crucial role in promoting the adoption of these technologies, while the attitudes of enterprises and medical professionals are significantly influenced by perceived costs and benefits. Simulation analyses were conducted using MATLAB 2019a to validate the model, providing insights into optimizing stakeholder engagement and enhancing the adoption of AI in elderly care. We propose actionable recommendations for policymakers and industry leaders to foster the integration of AI into elderly care services, addressing critical challenges and leveraging opportunities in this evolving landscape.
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http://dx.doi.org/10.1177/00469580241282050 | DOI Listing |
Respir Med
September 2025
Department of Pulmonary Medicine, Allergology and Clinical Immunology, Inselspital, Bern University Hospital, University of Bern, Switzerland. Electronic address:
Background: Patients with pulmonary hypertension (PH) experience reduced physical capacity, which affects daily life functionality. Frailty signifies increased vulnerability due to diminished physiological reserves and is common in the elderly and those with chronic diseases, but has not been investigated in PH. This study aimed to create a frailty index for PH, to assess the prevalence of frailty, to determine frailty severity and progression over time and to establish a potential association between frailty and mortality in patients with PH.
View Article and Find Full Text PDFJMIR Aging
September 2025
Division of Community Health, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer- Sheva, Israel.
Background: Frailty is a common issue among hospitalized older adult patients and is associated with numerous adverse health outcomes. Assessing frailty facilitates better decision-making for treatment plans, patient placement, and discharge planning. Approximately a decade ago, the frailty index based on laboratory tests (FI-Lab) metric was introduced.
View Article and Find Full Text PDFJMIR Rehabil Assist Technol
September 2025
Department of Computer Science, Faculty of Technology, Art and Design, OsloMet - Oslo Metropolitan University, Oslo, Norway.
Background: Over the past decade, the proportion of the world's population aged ≥65 years has grown exponentially, presenting significant challenges, such as social isolation and loneliness among this population. Assistive technologies have shown potential in enhancing the quality of life for older adults by improving their physical, cognitive, and communication abilities. Research has shown that smart televisions are user-friendly and commonly used among older adults.
View Article and Find Full Text PDFEpidemiol Serv Saude
September 2025
Universidade Federal da Bahia, Programa de Pós-Graduação em Saúde, Ambiente e Trabalho, Salvador, BA, Brazil.
Objective: Estimate mortality indicators and impact of COVID-19 on healthcare workers in Bahia in the period 2020-2022.
Methods: This is a descriptive study, with death data extracted from the Brazilian Mortality Information System. Population data were obtained from professional councils, the National Registry of Health Establishments and the Brazilian National Immunization Program Information System.
Epidemiol Serv Saude
September 2025
Universidade Federal de Minas Gerais, Escola de Enfermagem,Departamento de Gestão em Saúde, Belo Horizonte, MG, Brasil.
Objective: To analyze the sociodemographic profile of elderly individuals hospitalized in a medium and high complexity hospital in Belo Horizonte, with emphasis on reasons for hospitalization, length of hospital stay, and factors associated with risk of death.
Methods: This is a descriptive, quantitative, cross-sectional study based on data from electronic medical records of elderly individuals (≥60 years) treated between 2015 and 2019 at a referral hospital for multiple trauma in Belo Horizonte. The variables investigated included age, sex, marital status, municipality of origin, reason for hospitalization, and length of stay.