Bridging the gaps: Comparing structural equation models to network analysis models of depression, anxiety, and perfectionism

Abstract

Network models of psychopathology can identify specific items/symptoms that explain the connections among broader constructs such as depression, anxiety, and perfectionism. In two studies, we examine the dynamic interplay between depression, anxiety, and perfectionism symptoms among undergraduates using structural equation modeling (SEM) and network analysis. Participants in two independent samples (N = 774 and N = 759) completed online, cross-sectional questionnaires including measures of anxiety, depressive symptoms, and perfectionism (i.e., concerns over mistakes, doubts about actions, and personal standards). When analyzing data in the traditional fashion using SEM as a point of comparison, results from both samples were consistent with the existing literature. After controlling for all other perfectionism variables in the model, concerns over mistakes and doubts about actions were positively associated with depressive and anxiety symptoms (βs from .21 to .46), while personal standards showed negative associations with depressive symptoms (β = -.20 both samples) and non-significant associations with anxiety symptoms (βs from -.09. to -.03). Nonetheless, model fit for the confirmatory factor model was below ideal cutoffs in the second sample, suggesting other structures (e.g., a network model) might better represent the data. Network analyses revealed associations between constructs at the item level across both samples. Four key symptoms emerged as central nodes linking depression, anxiety, and perfectionism: difficulty taking initiative to do activities, feeling worthless, feeling close to panic, and doubts about simple everyday activities. This study underscores the importance of investigating item-level associations for a nuanced interpretation of these constructs.