Abstract: Psychological resilience, as a crucial capacity for maintaining mental health, has long faced challenges in its conceptual definition and operationalization. Drawing on complex dynamic systems theory, it can be defined as the stability and tendency toward health exhibited by the mental health state system under the drive of an influencing factors system. Network analysis is a powerful tool for characterizing this framework. Current research often focuses the mental health state system on psychopathological symptoms, mapping the spontaneous activation tendency (threshold) of symptom networks onto health tendency and edge weights onto stability, thereby forming a “symptom network resilience” paradigm. Based on the centrality hypothesis, key mental health state indicators that determine symptom network resilience are identified, and influencing factors of resilience are further incorporated into the psychopathological symptom network to examine their circular interactions. However, this field is still in its initial stage, with limitations in the quantitative accuracy of theoretical constructs, paradigm validity verification, and individualized applications—yet these limitations also point the way for future research.

Key words: psychological resilience, complex dynamic systems, psychopathological symptoms, network theory