The combination of network theory and network psychometric methods has opened up a variety of new ways to conceptualize and study psychological disorders. The idea of psychological disorders as dynamic systems has sparked interest in developing interventions based on results of network analytic tools. However, simply estimating a network model is not sufficient for determining which symptoms might be most effective to intervene upon, nor is it sufficient for determining the potential efficacy of any given intervention. In this paper, we attempt to remedy this gap by introducing fundamental concepts of control theory to both psychometricians and applied psychologists. We introduce two controllability statistics to the psychometric literature, average and modal controllability, to facilitate selecting the best set of intervention targets. Following this introduction, we show how intervention scientists can probe the effects of both theoretical and empirical interventions on networks derived from real data and demonstrate how simulations can account for intervention cost and the desire to reduce specific symptoms. Every step is based on rich clinical EMA data from a sample of subjects undergoing treatment for complicated grief, with a focus on the outcome suicidal ideation. All methods are implemented in an open-source R package netcontrol, and complete code for replicating the analyses in this manuscript are available online.

The network approach to psychopathology posits that mental disorders can be conceptualized and studied as causal systems of mutually reinforcing symptoms. This approach, first posited in 2008, has grown substantially over the past decade and is now a full-fledged area of psychiatric research. In this article, we provide an overview and critical analysis of 363 articles produced in the first decade of this research program, with a focus on key theoretical, methodological, and empirical contributions. In addition, we turn our attention to the next decade of the network approach and propose critical avenues for future research in each of these domains. We argue that this program of research will be best served by working toward two overarching aims: (a) the identification of robust empirical phenomena and (b) the development of formal theories that can explain those phenomena. We recommend specific steps forward within this broad framework and argue that these steps are necessary if the network approach is to develop into a progressive program of research capable of producing a cumulative body of knowledge about how specific mental disorders operate as causal systems.