What are the benefits of network analysis in health psychology? The example of post-stroke depression

Abstract

Background: Network perspective is a recent conceptual approach in psychopathology which understands mental disorders as complex networks of interacting symptoms. Network analysis could have a great impact for the knowledge and treatment of depression after a minor stroke. Whereas non-specific depression symptoms (e.g. fatigue, concentration problems) could have a central influence in the emergence of more specific depression symptoms (e.g. sadness, anhedonia, negative thoughts), those symptoms are generally considered as potential side-effects belonging to the neurological impairments and thereby excluded from the post-stroke depression assessment. The aim of this study is to present the evolution of the network organization of depression symptoms in two patients and its potential benefit in clinical care. Method: We performed network and centrality analysis (with qgraph and bootnet R packages) of depression symptoms (sadness, anhedonia, fatigue, concentration problems, negative thoughts on oneself, pessimism, anxiety, retardation, physical tension, irritability) daily repeated reports from two minor stroke patients at home-return, at 2-month and at 4-month after stroke. Findings: Network’s central depression symptoms are different for the two participants and at the different times of the study. Non-specific depression symptoms (e.g. psychomotor agitation) are more central in their networks at home-return than later. Discussion: It appears essential to reconsider non-specific symptoms in the assessment of depression after a minor stroke. More efficient interventions on post-stroke depression should be individually designed considering two points: estimating the network of depression symptoms for each patient and focusing on their central symptoms, whether or not those symptoms are specific of depression.