Bouncing back from life’s perturbations: Formalizing psychological resilience from a complex systems perspective

Resilience refers to the ability to return to normal psychological functioning despite facing adversity. It remains an open question how to anticipate and study resilience, due to its dynamic and multifactorial nature. This paper presents a novel formalized simulation framework for studying resilience from a complex systems perspective. From this view, resilience is a property of a system that arises if a system is located in a stable and healthy state despite facing adversity. We use the network theory of psychopathology, which states that mental disorders are self-sustaining endpoints of direct symptom-symptom interactions organized in a network system. The internal structure of the network determines the most likely trajectory of symptom development. We introduce the resilience quadrant, which organizes the state of symptom networks on two domains: 1) healthy versus disordered, and 2) stable versus unstable. The quadrant captures different behaviors along those dimensions: resilient trajectories in the face of adversity, as well as persistent symptoms despite treatment interventions. Subsequently, we introduce a systematic methodology, using simulated perturbations, to determine where in the resilience quadrant an observed network is currently located. As such, we present a novel outlook on resilience by combining existing statistical symptom network models with simulation techniques.