Personalized networks of social anxiety disorder and depression and implications for treatment

Abstract

IntroductionSocial anxiety disorder (SAD) and major depressive disorder (MDD) often co-occur; however, there is limited research evaluating how cognitive-affective and behavioral factors maintain SAD and MDD for specific individuals. Evidence suggests that individuals exhibit symptom-level heterogeneity, necessitating a person-specific approach to assessment and intervention. We compared group and person-specific models of SAD-MDD comorbidity and hypothesized that individuals would demonstrate person-specific patterns of comorbidity factors that differed from the group. MethodsCisgender women (N = 35) with SAD and a current or past major depressive episode were recruited. Ages ranged from 18 to 37 years old and a majority of women were White (n = 18; 51.43%). Brief ecological momentary assessment surveys related to SAD-MDD comorbidity were administered five times a day for a month (T = 4,357). ResultsMultilevel and person-specific network analyses were used to examine between-, within-, and person-specific patterns. Intra-daily depressed mood demonstrated the strongest connections to other variables and exhibited additional, unexpected temporal effects. All models demonstrated person-specific patterns relevant to SAD-MDD comorbidity. LimitationsThese results are descriptive in nature from women with a similar psychiatric profile. Future research integrating intensive EMA and personalized modeling within the context of experimental design is needed to determine the extent to which individuals truly differ from the group. ConclusionsPatterns of SAD-MDD comorbidity varied substantially across women, underscoring the potential for results from person-specific (idiographic) networks to inform the development and implementation of personalized directives for clinical assessment and intervention.