A Network Analysis of the Association Between Depressive Symptoms and Patient Activation Among Those With Elevated Cardiovascular Risk

Abstract

Background: Network analysis provides a new method for conceptualizing interconnections among psychological and behavioral constructs. Objective: We used network analysis to investigate the complex associations between depressive symptoms and patient activation dimensions among patients at elevated risk of cardiovascular disease. Methods: This secondary analysis included 200 patients seen in primary care clinics. Depressive symptoms were assessed using the 21-item Beck Depression Inventory. Patient activation was measured using the 13-item Patient Activation Measure. Glasso networks were constructed to identify symptoms/traits that bridge depressive symptoms and patient activation and those that are central within the network. Results: “Self-dislike” and “confidence to maintain lifestyle changes during times of stress” were identified as important bridge pathways. In addition, depressive symptoms such as “punishment feelings,” “loss of satisfaction,” “self-dislike,” and “loss of interest in people” were central in the depressive symptom–patient activation network, meaning that they were most strongly connected to all other symptoms. Conclusions: Bridge pathways identified in the network may be reasonable targets for clinical intervention aimed at disrupting the association between depressive symptoms and patient activation. Further research is warranted to assess whether targeting interventions to these central symptoms may help resolve other symptoms within the network.