Depression symptoms and core affect: Results from network and regression analyses

Abstract

AbstractDepression is measured in most studies by surveys that sum individual symptom scores into one common variable. Given the high heterogeneity of depressive disorders and the diversity of symptom profiles at the same levels of depression, a significant amount of information is, therefore, not evaluated. In this study, we aimed to investigate how distinct depression symptoms from the tripartite model of anxiety and depression relate to the dimensions of core affect. The study included N = 1102 individuals who completed depression, anxiety and stress, and core affect scales. Participants were recruited from the convenience sample and were aged between 18 and 59 years (M = 39.70; SD = 12.03) with 38.2% men and 61.8% women, whose average number of years spent in education was M = 14.17; SD = 3.63. Correlation and regression analysis with JASP and R software showed that all depressive symptoms were significantly related to the core affect dimensions (valence and activation), and network analysis indicated which symptoms formed undirected interrelationships and what their possible roles were in the model. We concluded that not all depression symptoms in the network model formed similar relationships with the dimensions of core affect, which may be explained through both validity and nonclinical sampling aspects.