A network analysis of symptoms of obsessive compulsive disorder and depression in a clinical sample

Abstract

McNally, Mair, Mugno, and Riemann (2017) provide preliminary evidence for the hypothesis that obsessive compulsive disorder (OCD) and depression symptoms co-occur because they create a network of interacting symptoms. Given the need to understand comorbidity between these symptoms and replicating network models, the aim of the current study was to examine a cross-sectional network of OCD and depression symptoms in an adult clinical sample diagnosed with OCD (n = 290). Participants completed self-report measures of OCD and depression symptoms. A network of regularized partial correlation coefficients was estimated using the graphical least absolute shrinkage and selection operator (GLASSO) with the Extended Bayesian Information Criterion (EBIC). Parameter estimates were also compared between McNally and colleagues’ (2017) results and the current findings to determine the consistency of trends. OCD and depression symptom clusters were bridged by an association between interference from obsessions and low energy, suggesting this is a key feature in the development of comorbidity. Distress related to obsessions emerged as the most highly central node in the network. Low energy, interference from compulsions, and resisting compulsions were also central to the network. These symptoms may be important targets for treatment. Overall, the majority of comparable parameters were consistent with previous work.