背景(考古学)
本体论
压力源
适应(眼睛)
心理学
计算机科学
概念框架
期限(时间)
认知
弹性(材料科学)
心理弹性
连贯性(哲学赌博策略)
认知科学
认知心理学
概念模型
数据科学
实证研究
形式本体论
管理科学
知识管理
认识论
理论定义
社会心理学
实证检验
心理学理论
作者
John Manning,Breanna Morales,Jennifer M. Yentes
标识
DOI:10.1016/j.arr.2026.103155
摘要
Physical resilience is a term used to describe an individual's response to physical and physiological stressors across the fields of gerontology and rehabilitation sciences. However, the term has not yet undergone a rigorous examination of its underlying assumptions, which has hindered its theoretical development and empirical measurement. This paper reviews the existing definitions of physical resilience in the context of human physical and psychological systems to examine its underlying, implicit assumptions. The aim is to clarify the conceptual foundations of physical resilience, identify its necessary components, and propose a formal ontological framework based on them. We conducted a scoping review of peer-reviewed literature using databases including PubMed and Web of Science. Definitions were extracted from experimental and conceptual papers and analyzed for shared themes and implicit assumptions. These ranged from general notions of recovery or adaptation to specific models of post-perturbation performance trajectories. Across studies, outcomes included whole-body, physiological, and occasional psychological or cognitive measures. However, the term physical was rarely explicitly defined, making it unclear how it modifies the term resilience. Only two studies referenced formal models of resilience, and few distinguished resilience from related constructs like adaptation or robustness. Findings revealed a lack of conceptual coherence in the current literature. We propose that physical resilience may be understood as an emergent, time-dependent disposition at the whole-body level involving interactions across multiple biological systems and scales. We suggest that a formal ontological framework of resilience can help clarify perturbation, recovery, and domain-specific contributions to support consistent measurement and interdisciplinary integration.
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