Keywords: Comorbidity | Assessment | Research Methods
Presentation Type: Symposium
A network analysis of time series data for an individual can provide an understanding of which symptoms or behaviors are more central to an individual’s distress or dysfunction as the symptoms influence each other over time. Intraindividual network analysis provides the opportunity to model idiosyncratic symptom presentation in comorbid cases and may be particularly useful in the development of clinical case formulations. Multiple studies utilizing a network analysis approach have examined comorbidity using between-subjects cross-sectional data; however, until now, a direct application of the network analysis approach to intraindividual and dynamic relations in a complex, comorbid case has not been achieved. The current study utilized multivariate time series data to create and examine intraindividual networks of symptoms in an individual with comorbid mood and anxiety disorders. The participant was a 44-year-old female diagnosed with major depressive disorder, dysthymia, and social anxiety disorder. The participant completed 90 daily questionnaires collected over the course of 123 days. This presentation will outline the procedure used to create each type of intraindividual network, interpret the empirically-derived network relations, and discuss implications for personalized treatment planning. Intraindividual network analysis represents a new methodology for analyzing psychopathology with person-specific dynamic analyses.
Clinical Psychology Doctoral Student
Texas Tech University
Saturday, November 18
1:45 PM – 3:15 PM
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