Reimagining Resilience in Aging: Leveraging AI/ML, Big Data Analytics, and Systems Innovation.
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| Titel: | Reimagining Resilience in Aging: Leveraging AI/ML, Big Data Analytics, and Systems Innovation. |
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| Autoren: | Chen J; 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., Maguire TK; 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)., McCoy RG; 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., Thomas S; 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., Reynolds CF 3rd; Geriatric Psychiatry (CFR), University of Pittsburgh School of Medicine, Emeritus Faculty, Pittsburgh, PA. |
| Quelle: | The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry [Am J Geriatr Psychiatry] 2025 Sep; Vol. 33 (9), pp. 1005-1017. Date of Electronic Publication: 2025 May 18. |
| Publikationsart: | Journal Article |
| Sprache: | English |
| Info zur Zeitschrift: | Publisher: Elsevier Country of Publication: England NLM ID: 9309609 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1545-7214 (Electronic) Linking ISSN: 10647481 NLM ISO Abbreviation: Am J Geriatr Psychiatry Subsets: MEDLINE |
| Imprint Name(s): | Publication: Jan. 2013- : London : Elsevier Original Publication: Washington, DC : American Psychiatry Press |
| MeSH-Schlagworte: | Resilience, Psychological* , Aging*/psychology , Artificial Intelligence* , Big Data*, Humans ; Aged ; United States ; Data Science ; Data Analytics |
| Abstract: | Competing Interests: DISCLOSURES No conflicts of interest. Jie Chen and Teagan Maguire are supported by theNational Institute on Aging(R01AG062315andRF1AG083175). Jie Chen and Rozalina G. McCoy are investigators at the University of Maryland-Institute for Health Computing, which is supported by funding from Montgomery County, Maryland and The University of Maryland Strategic Partnership: MPowering the State, a formal collaboration between the University of Maryland, College Park and the University of Maryland, Baltimore. 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. (Copyright © 2025 The Authors. Published by Elsevier Inc. All rights reserved.) |
| Contributed Indexing: | Keywords: AI/ML; Aging health; Collaboration; Depression; Health disparities; Integration; Resilience |
| Entry Date(s): | Date Created: 20250608 Date Completed: 20250707 Latest Revision: 20250707 |
| Update Code: | 20250708 |
| DOI: | 10.1016/j.jagp.2025.05.007 |
| PMID: | 40484798 |
| Datenbank: | MEDLINE |
Nájsť tento článok vo Web of Science | Abstract: | Competing Interests: DISCLOSURES No conflicts of interest. Jie Chen and Teagan Maguire are supported by theNational Institute on Aging(R01AG062315andRF1AG083175). Jie Chen and Rozalina G. McCoy are investigators at the University of Maryland-Institute for Health Computing, which is supported by funding from Montgomery County, Maryland and The University of Maryland Strategic Partnership: MPowering the State, a formal collaboration between the University of Maryland, College Park and the University of Maryland, Baltimore.<br />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.<br /> (Copyright © 2025 The Authors. Published by Elsevier Inc. All rights reserved.) |
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| ISSN: | 1545-7214 |
| DOI: | 10.1016/j.jagp.2025.05.007 |