ORCID

http://orcid.org/0000-0002-4616-5180

Date of Award

Summer 8-15-2020

Author's School

Graduate School of Arts and Sciences

Author's Department

Psychology

Degree Name

Doctor of Philosophy (PhD)

Degree Type

Dissertation

Abstract

Social anxiety disorder (SAD) is an important risk factor for major depressive disorder (MDD) and together this comorbidity constitutes a highly impairing syndrome and vicious cycle of symptomatology, associated with tremendous health costs and societal burden. Despite much group-level research examining risk factor for MDD specifically, there is limited group and individual-level research evaluating how individuals with SAD transition into depressive episodes. Clinical and theoretical evidence suggests that each patient may exhibit a unique personalized pattern of risk factors. These idiographic patterns may contradict relationships seen at the group level. In this dissertation, women (N = 35) with SAD and a current or past major depressive episode were asked to complete brief surveys of their mood and emotional experience five times a day for a month via a smartphone application. These data were analyzed using idiographic analyses to construct individual-level models of each woman’s mood. Additionally, a multilevel model was constructed to determine risk factors for daily levels of sadness on the group level. Overall, results largely supported study hypotheses. Most women’s models demonstrated few statistically significant directed pathways predicting sadness, although the directed pathways that existed were different between women. Additionally, there was minimal overlap between the multilevel model and each individual-level model, providing evidence that relationships reflected in the individual-level models differed from the relationships elucidated at the group-level. Differences between the multilevel and individual-level models highlight the potential integration of idiographic methodology into clinical practice. Furthermore, nuances related to the multilevel methodology used here provide evidence as to how intensive longitudinal data can be used to improve upon group-level models of psychopathology. Implications for the use of intensive longitudinal data and idiographic analyses in clinical assessment and intervention are discussed.

Language

English (en)

Chair and Committee

Thomas L. Rodebaugh

Committee Members

Eric J. Lenze, Joshua J. Jackson, Renee J. Thompson, Richard G. Heimberg,

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