Systems all the way down: embracing complexity in mental health research

Abstract

[...]the authors emphasize the dynamic nature of mental health and the need to understand how psychopathology unfolds over time, most saliently over the course of childhood and adolescence. Hayes and Andrews [13] provide an introduction of basic principles from complexity science relevant to mental health, such as attractor states (i.e., states to which the mental health system will gravitate), early warning signals that indicate increased potential for a transition to an alternative attractor state, and network destabilization: the disruption of a system stuck in a harmful state to facilitate transitions to a new state of mental health. Burger and colleagues propose to extend this approach, using computational models as a thinking tool to aid case conceptualizations, a didactic tool for helping patients understand the factors giving rise to their distress, a prediction tool for anticipating treatment outcomes, and a treatment selection tool that can guide the selection of interventions most likely to lead to change in psychotherapy. [...]the task of understanding the systems that