Reimagining Resilience in Aging: Leveraging AI/ML, Big Data Analytics, and Systems Innovation

Jie Chen; Teagan K Maguire; Rozalina G McCoy; Stephen Thomas; Charles F Reynolds 3rd

doi:10.1016/j.jagp.2025.05.007

Reimagining Resilience in Aging: Leveraging AI/ML, Big Data Analytics, and Systems Innovation

Am J Geriatr Psychiatry. 2025 May 18:S1064-7481(25)00352-5. doi: 10.1016/j.jagp.2025.05.007. Online ahead of print.

Authors

Jie Chen¹, Teagan K Maguire², Rozalina G McCoy³, Stephen Thomas⁴, Charles F Reynolds 3rd⁵

Affiliations

¹ Department of Health Policy and Management (JC, TKM, RGM, ST), School of Public Health, University of Maryland, College Park, MD; School of Public Health (JC, TKM), The Hospital And Public Health InterdisciPlinarY Research (HAPPY) Lab, University of Maryland, College Park, MD; University of Maryland Center on Aging (JC, TKM, RGM); University of Maryland Institute for Health Computing (RGM), North Bethesda, MD. Electronic address: jichen@umd.edu.
² Department of Health Policy and Management (JC, TKM, RGM, ST), School of Public Health, University of Maryland, College Park, MD; School of Public Health (JC, TKM), The Hospital And Public Health InterdisciPlinarY Research (HAPPY) Lab, University of Maryland, College Park, MD; University of Maryland Center on Aging (JC, TKM, RGM).
³ Department of Health Policy and Management (JC, TKM, RGM, ST), School of Public Health, University of Maryland, College Park, MD; University of Maryland Center on Aging (JC, TKM, RGM); Division of Endocrinology (RGM), Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD; University of Maryland Institute for Health Computing (RGM), North Bethesda, MD.
⁴ Department of Health Policy and Management (JC, TKM, RGM, ST), School of Public Health, University of Maryland, College Park, MD; Center for Health Equity (ST), University of Maryland School of Public Health, College Park, MD.
⁵ Geriatric Psychiatry (CFR), University of Pittsburgh School of Medicine, Emeritus Faculty, Pittsburgh, PA.

PMID: 40484798
DOI: 10.1016/j.jagp.2025.05.007

Abstract

As the aging population in the United States grows, the need for an integrated approach to support older adults has become increasingly urgent. The SUNSHINE framework, Seniors Uniting Nationwide to Support Health, INtegrated Care, and Evolution, offers a model for advancing resilience, defined as the capacity of individuals, families, systems, and communities to adapt and thrive in the face of adversity. SUNSHINE promotes this goal through the alignment of older and aging adults, families, healthcare systems, public health agencies, social services, and community resources. Using the Theory of Change modeling, SUNSHINE emphasizes whole-person health, interdisciplinary collaboration, and the strategic use of technology to address the evolving needs of aging populations. The framework promotes systems integration supported by research infrastructure and multi-sector collaboration to enhance the well-being of older adults and family caregivers. SUNSHINE places a strong emphasis on mental health, particularly depression, and highlights the importance of social connection and prevention in addressing health disparities and care gaps associated with aging. It conceptualizes resilience as both a desired outcome and a driver of transformation, guiding the redesign and evaluation of health and social systems. The framework also identifies opportunities to leverage artificial intelligence and machine learning (AI/ML) technologies, grounded in scientific evidence, to support personalized prevention, treatment, and care strategies. These technologies are critical for optimizing decision-making, improving care delivery, and enhancing system flexibility. Finally, SUNSHINE aspires to advance a future of aging that is healthy, resilient, and fair, guided by principles of equity, defined as fairness and impartiality in health opportunities and outcomes.

Keywords: AI/ML; Aging health; Collaboration; Depression; Health disparities; Integration; Resilience.