Bouncing back from adversity: A novel outlook on psychological resilience and its indicators from a complex systems perspective

The question of why some people develop psychopathology following adversity while others do not, has been extensively investigated in the psychological literature. A pressing yet unanswered question is what makes the latter group of people resilient in that they are seemingly able to withstand the ‘attack’ that adverse events launch on their health and well-being. To date, there is no consensus on what resilience exactly is conceptually, which seriously hampers progress as various definitions and operationalizations abound. Resilience is a concept that has been extensively studied in dynamical systems such as the growth of a bacteria population and the turbidity of a lake. A relatively new modeling approach conceptualizes mental disorders as a dynamical system in which the dynamics are driven by a network that consists of symptoms of a disorder that stand in certain direct relations to one another. Based on such a dynamical systems perspective, this paper presents a novel, framework for studying psychological resilience. With a simulation study, we show how the architecture of psychopathological networks relates to its dynamics. As a means to facilitate further study, we also introduce a Shiny application in which researchers can study these resilience indicators on their own data.