Conceptualizing anxiety and depression in children and adolescents: a latent factor and network analysis

Abstract

The objective of this study is to gain insight into the inherent structure of anxiety and depressive symptoms by combining the strengths of latent factor analysis and network analysis. The sample comprised 743 children and adolescents aged 4–18 years (M = 11.64, SD = 3.66, 61% males) who sought routine care outpatient psychotherapy. Parents or primary caregivers rated anxiety and depressive symptoms of their children on a DSM-5-/ICD-10-based symptom checklist. First, we analyzed the factor structure of the internalizing symptoms using exploratory factor analysis (EFA). Next, we conducted a network analysis and identified central and bridge symptoms that may explain comorbidity between anxiety disorders and depression. We then employed exploratory graph analysis (EGA) as an alternative tool within the framework of network psychometrics to estimate the number of dimensions (i.e., communities within a network). Finally, we tested a model based on these results using confirmatory factor analysis. The results demonstrate a complex interplay between anxiety and depressive symptom domains. Four factors/communities were identified by EFA and EGA, but the item-community allocation differed, and the interpretation of factors/communities was unclear. A clear distinction between these domains could not be supported. However, associations within a domain were stronger than associations between the two domains. We identified pain, suicidal, irritable, and afraid of adults as bridge items between the symptom domains. In conclusion, our findings further advance the general understanding of the frequently reported co-occurrence of anxiety and depressive symptoms and diagnoses in clinical practice. Identifying bridge symptoms may inform intervention practices by targeting specific symptoms that contribute to the maintenance of anxious and depressive behaviors.