The role of stabilizing and communicating symptoms given overlapping communities in psychopathology networks

Abstract

Network theory, as a theoretical and methodological framework, is energizing many research fields, among which clinical psychology and psychiatry. Fundamental to the network theory of psychopathology is the role of specific symptoms and their interactions. Current statistical tools, however, fail to fully capture this constitutional property. We propose community detection tools as a means to evaluate the complex network structure of psychopathology, free from its original boundaries of distinct disorders. Unique to this approach is that symptoms can belong to multiple communities. Using a large community sample and spanning a broad range of symptoms (Symptom Checklist-90-Revised), we identified 18 communities of interconnected symptoms. The differential role of symptoms within and between communities offers a framework to study the clinical concepts of comorbidity, heterogeneity and hallmark symptoms. Symptoms with many and strong connections within a community, defined as stabilizing symptoms, could be thought of as the core of a community, whereas symptoms that belong to multiple communities, defined as communicating symptoms, facilitate the communication between problem areas. We propose that defining symptoms on their stabilizing and/or communicating role within and across communities accelerates our understanding of these clinical phenomena, central to research and treatment of psychopathology.

Personality, resilience, and psychopathology: A model for the interaction between slow and fast network processes in the context of mental health

“…(Fried, 2017). In addition, different symptoms may have distinct roles in the network, such as stabilizing the disorder state or communicating between various disorders (Blanken et al, 2018). Therefore, the impact of altering the thresholds of one mental disorder symptom will vary depending on the symptomatology of the individual and the network architecture.…”

Problems with Centrality Measures in Psychopathology Symptom Networks: Why Network Psychometrics Cannot Escape Psychometric Theory

“…Failing to do so risks identifying spurious relationships or failing to detect causally important effects. In this vein, one recent study contextualized nodal metrics vis-à-vis symptom modules that may represent latent variables, rather than emphasizing metrics such as closeness that are blind to subgraph structure (Blanken et al, 2018).…”

NetworkToolbox: Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis in R

“…Meso-scale features of networks are becoming increasing popular in network analysis (Blanken et al, 2018;Giscard and Wilson, 2018;Golino and Epskamp, 2017;Golino and Demetriou, 2017;Golino et al, 2018). Meso-scale network characteristics evaluate the sub-network structure of the network or how the entire network can be summarized into smaller components (i.e., communities).…”