Project Summary 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 factors 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 that may add important context to relationships demonstrated between group-level factors. Thus, it is important to pair both between and within-subjects longitudinal designs. I propose an integrated pair of studies that will evaluate risk factors among a sample of individuals vulnerable to depression. Findings from Study 1 will advance large-scale models of psychopathology and will provide evidence for the cognitive-behavioral mechanisms of the negative valence and social processing (i.e., affiliation and attachment) RDoC systems among individuals who are especially vulnerable to increases in depression. Findings from Study 2 will elucidate individual-specific patterns of risk factors measured in a high- risk sample of women enrolled in Study 1. Information from these individual risk models can be harnessed to improve the efficacy of existing treatment and prevention efforts. In Study 1, individuals who are vulnerable to increases in depression will complete two clinical diagnostic interviews and self-report assessments spaced approximately three months apart. Data from Study 1 will be evaluated using group level analyses and results will provide much needed evidence for depressogenic factors among individuals with elevated levels of social anxiety. A high-risk sample of women with SAD will be recruited from Study 1 into Study 2 that will use novel individual-specific methodology (ISM) administered via personal mobile devices, along with salivary cortisol assessment, to measure longitudinal cognitive-behavioral and physiological risk factors. ISM data from Study 2 will be evaluated using person-centered analyses to construct individual risk models (IRM) of depression for individuals with SAD. Results from Study 2 IRM will complement and provide context for Study 1 group-based findings that track longitudinal risk factors for increases in depression. Basal levels of cortisol, as well as cortisol awakening response, will be examined using multilevel modeling to determine how physiological patterns, along with cognitive-behavioral factors, predict depression. This integrated pair of studies examines group and individual-specific trends for a sample at high-risk for depression and results have important implications. As ISM methods are becoming increasingly scalable for dissemination in larger populations via the use of personal mobile technology, future work using ISM is far-reaching and can inform personalized directives for treatment, as well as advance prevention efforts for groups of individuals vulnerable to depression. !
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NIH ExPorter