目的:本研究重新概念化了特质弹性,将其定义为系统网络;利用直接弹性评估-工程,生态,适应能力,社会凝聚力和代理弹性评估-人格,认知,情感,eudaimonia,和健康。
背景:研究背景通过提出基于生态系统理论的统一网络模型,解决了特质弹性的零散概念化,说明了弹性因素在不同干扰水平下的动态相互作用。
方法:在研究一,使用四个美国或英国样本(总共n=2396)来描绘特质弹性网络。研究二(n=1091)在两个时间点检查了网络与干扰之间的关系,使用心理健康水平作为干扰指标。
结果:研究发现,适应能力,有时是积极的情绪过程,是网络的中心变量。研究二发现,在低干扰组,适应能力仍然很重要,而在较高的干扰群体中,一组更广泛的变量成为网络的核心。
结论:研究一提出了一种扩展和构建方法,适应能力是一种基本的复原能力,与积极情绪机制相互关联。研究二提出了一种新的动态弹性谱理论,“提出增加的干扰需要使用更多样化的弹性特征。
OBJECTIVE: This study reconceptualized trait resilience, defining it as a network of
systems; utilizing direct resilience assessments-engineering, ecological, adaptive capacity, social cohesion-and proxy resilience assessments-personality, cognitive, emotional, eudaimonia, and health.
BACKGROUND: The background of the study addresses the fragmented conceptualization of trait resilience by proposing a unifying network model based on ecological
systems theory, illustrating the dynamic interplay of resilience factors across varying levels of disturbance.
METHODS: In Study One, four USA or UK samples (total n = 2396) were used to depict the trait resilience network. Study Two (n = 1091) examined the relationship between the network and disturbance at two time-points, using mental health levels as a disturbance metric.
RESULTS: Study One found that adaptive capacity, and sometimes positive emotional processes, were central variables to the network. Study Two found that in lower disturbance groups, adaptive capacity remained important, while in higher disturbance groups, a broader set of variables became central to the network.
CONCLUSIONS: Study One suggests a Broaden-and-Build approach, where adaptive capacity is a foundational resilience capability, reciprocally associated with positive emotional mechanisms. Study Two suggests a new \"Dynamic Resilience Spectrum Theory,\" proposing that increased disturbances necessitate the use of a more diverse set of resilience traits.