Maatwerk in hoogspecialistische ggz met individuele dynamische netwerkanalyse

Abstract

BACKGROUND: Patients with mental health disorders often have difficulty perceiving associations between multiple symptoms, such as inter-relations between somatic and psychological symptoms. This difficulty may be particularly challenging in patients with complex disorders. Individual dynamic network analysis may provide novel diagnostic and treatment possibilities because it can create a starting point for a personalized approach in complex cases in tertiary mental health care expert centres, where standard protocolized interventions were insufficiently effective. AIM: To explore the possibilities provided by dynamic network technologies in the care of patients in tertiary care expert centres. METHOD: Overview of these possibilities, with a focus on somatic symptom disorder. RESULTS: Intensive longitudinal data can be obtained using a short and personalized questionnaire that is presented via a patient's smartphone a few times per day during several weeks. These data are then converted to patient-specific dynamic symptom networks using time series analysis. These networks display how variations over time in somatic and mental symptoms and other factors (such as specific situations) mutually influence each other in daily life. They also provide information about cause-effect associations. CONCLUSION: Dynamic symptom networks provide insight into the associations between symptoms and other factors and can be used to personalize treatment goals and interventions in tertiary care expert centres. Furthermore, these networks create opportunities to examine the (patient-tailored) effects of personalized interventions.