Social anxiety disorder (SAD) constitutes an important risk factor for major depressive disorder (MDD) and women are at greater risk for both disorders and their comorbidity. Despite much research examining risk factors for MDD specifically, there is limited research evaluating how individuals with SAD transition into depressive episodes. Clinical and theoretical evidence suggests that each individual may exhibit a unique personalized pattern of risk factors. These idiographic patterns may contradict group-level findings. In this study, women (N = 35) with SAD and a current or past major depressive episode completed ecological sampling 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. A multilevel model was constructed to determine risk factors for group-level intra-daily sadness (i.e., depressed mood). Some group-level relationships were consistent with previous research; however, most women’s models demonstrated few, and differing, risk factors for intra-daily sadness. We also examined the spread of individual-level estimates taken from group and idiographic models to determine the extent to which multilevel models can estimate individual-level effects. Implications for integrating results from idiographic methodology into existing theoretical models of psychopathology and clinical practice are discussed.
Meta-analysis of virtual reality exposure therapy for social anxiety disorder
