Abstract
Purpose: To clarify the concept of older population-base resilience to support nursing research, public health planning, and healthy aging strategies.
Background: Older population-based resilience is an important concept for facilitating the adaptation of aging populations to multifaceted adversity networks. While extensive studies has examined resilience among older adults across diverse systems, hierarchical levels, and dimensional perspectives, the conceptual discourse has focused mainly on the individual level. A comprehensive articulation of population-level resilience attributes has been notably absent from the literature. Consequently, establishing a precise conceptualization of Older Population-Based Resilience constitutes an imperative scholarly endeavor.
Methods: A systematic literature search was implemented across principal academic databases, encompassing MEDLINE (Ovid), Embase, Scopus, JBI EBP (Ovid), PsycINFO, CINAHL, CENTRAL, Web of Science, ProQuest, Airiti Library, NCL Taiwan Periodical Literature, and WANFANG. Rodgers’ evolutionary concept analysis method was applied to identify attributes, antecedents, consequences. The theoretical architecture was subsequently elaborated through the integration of aging Social-Ecological Systems and Complex Adaptive Systems paradigms.
Results: Three core attributes of older population-based resilience were identified: (1) a multi-interactive network composed of interdependent units across levels; (2) a dynamic and continuously evolving adaptive trajectory; and (3) the emergence and accumulation of mutually reinforcing adaptive behaviors. Antecedents include systemic adversity patterns, multilevel protective resources, and structural vulnerability factors. The primary consequence is enhanced population-level healthy aging, contributing to improved public health outcomes and reduced susceptibility to age-related risks.
Conclusion: Conceptualizing Older Population-Based Resilience through the Complex Adaptive Systems theoretical lens demonstrates congruence with the foundational logic underlying artificial neural networks within machine learning paradigms. This theoretical convergence illuminates substantive opportunities for computational modeling utilizing empirical datasets, thereby facilitating the progression of systematic nursing assessment protocols, evidence-based interventions, and strategic policy formulation.
Notes
References:
Eidelson, R. J. (1997). Complex adaptive systems in the behavioral and social sciences. Review of General Psychology, 1(1), 42-71. https://doi.org/10.1037/1089-2680.1.1.42 (Original work published 1997)
Holland, J.H. (1992) Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial Intelligence. The MIT Press. https://doi.org/10.7551/mitpress/1090.001.0001
Klasa, K., Galaitsi, S., Wister, A., & Linkov, I. (2021). System models for resilience in gerontology: Application to the COVID-19 pandemic. BMC Geriatrics, 21(1), 51. https://doi.org/10.1186/s12877-020-01965-2
Rodgers, B. L., & Knafl, K. A. (2000). Concept development in nursing: Foundations. Techniques, and Applications: Saunders Philadelphia, PA.
Sievers, B., & Thornton, M. A. (2024). Deep social neuroscience: the promise and peril of using artificial neural networks to study the social brain. Social cognitive and affective neuroscience, 19(1), nsae014. https://doi.org/10.1093/scan/nsae014
Wister, A., Klasa, K., & Linkov, I. (2022). A Unified Model of Resilience and Aging: Applications to COVID-19. Frontiers in public health, 10, 865459. https://doi.org/10.3389/fpubh.2022.865459
Sigma Membership
Non-member
Type
Presentation
Format Type
Text-based Document
Study Design/Type
Systematic Review
Research Approach
Qualitative Research
Keywords:
Public and Community Health, Policy and Advocacy, Sustainable Development Goals, Older People, Psychological Resilience
Recommended Citation
Feng, Po-Chung, "Older Population-Based Resilience: An Evolutionary Analysis via Complex Adaptive Systems" (2026). International Nursing Research Congress (INRC). 313.
https://www.sigmarepository.org/inrc/2026/presentations_2026/313
Conference Name
37th International Nursing Research Congress
Conference Host
Sigma Theta Tau International
Conference Location
Toronto, Ontario, Canada
Conference Year
2026
Rights Holder
All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record. All permission requests should be directed accordingly and not to the Sigma Repository. All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.
Review Type
Abstract Review Only: Reviewed by Event Host
Acquisition
Proxy-submission
Date of Issue
2026-09-26
Older Population-Based Resilience: An Evolutionary Analysis via Complex Adaptive Systems
Toronto, Ontario, Canada
Purpose: To clarify the concept of older population-base resilience to support nursing research, public health planning, and healthy aging strategies.
Background: Older population-based resilience is an important concept for facilitating the adaptation of aging populations to multifaceted adversity networks. While extensive studies has examined resilience among older adults across diverse systems, hierarchical levels, and dimensional perspectives, the conceptual discourse has focused mainly on the individual level. A comprehensive articulation of population-level resilience attributes has been notably absent from the literature. Consequently, establishing a precise conceptualization of Older Population-Based Resilience constitutes an imperative scholarly endeavor.
Methods: A systematic literature search was implemented across principal academic databases, encompassing MEDLINE (Ovid), Embase, Scopus, JBI EBP (Ovid), PsycINFO, CINAHL, CENTRAL, Web of Science, ProQuest, Airiti Library, NCL Taiwan Periodical Literature, and WANFANG. Rodgers’ evolutionary concept analysis method was applied to identify attributes, antecedents, consequences. The theoretical architecture was subsequently elaborated through the integration of aging Social-Ecological Systems and Complex Adaptive Systems paradigms.
Results: Three core attributes of older population-based resilience were identified: (1) a multi-interactive network composed of interdependent units across levels; (2) a dynamic and continuously evolving adaptive trajectory; and (3) the emergence and accumulation of mutually reinforcing adaptive behaviors. Antecedents include systemic adversity patterns, multilevel protective resources, and structural vulnerability factors. The primary consequence is enhanced population-level healthy aging, contributing to improved public health outcomes and reduced susceptibility to age-related risks.
Conclusion: Conceptualizing Older Population-Based Resilience through the Complex Adaptive Systems theoretical lens demonstrates congruence with the foundational logic underlying artificial neural networks within machine learning paradigms. This theoretical convergence illuminates substantive opportunities for computational modeling utilizing empirical datasets, thereby facilitating the progression of systematic nursing assessment protocols, evidence-based interventions, and strategic policy formulation.
Description
This concept analysis clarified older population-based resilience using Rodgers’ method and systems theories. Three attributes emerged: a multi-interactive network of units, a dynamic adaptive evolution, and collective emergent reinforcing behaviors. Antecedents include systemic adversity and multiple factors, while consequences encompass population-level healthy aging. This concept enables computational modeling via machine learning to advance nursing interventions and policy development.