(PS3-20) Interpersonal Dynamics in Depression: Examining Variability in Perceived Social Support

Background: Improving relationships (including one’s perceived sense of social support) is a common treatment goal for clients with depression (Whisman et al., 2017). Therefore, it is necessary for researchers to better understand the dynamic interpersonal processes in individuals with depression, as this could play a critical role in decisions around best treatment approaches. However, the body of research investigating social support has primarily relied on measuring it as a static variable. Recent work suggests that social support may be better conceptualized as a dynamic variable that fluctuates over time (Coppersmith et al., 2019; Kellerman et al, 2022). Given this newfound understanding, this study aims to examine variability in social support with the goal of disentangling the reciprocal relationship between social support and depression symptoms day-to-day both within and outside treatment contexts.

Methods: We are recruiting 60 participants with depression symptoms, evenly split between those currently receiving a cognitive behavioral therapy and those not receiving therapy. Recruitment methods are specifically designed to capture a diverse population representative of the state of California (for those receiving therapy), and the United States’ demographics (for those not receiving therapy). Participants will be asked to complete ecological momentary assessments of perceived social support and depression symptoms three times a day for 14 days. Data collection is currently in progress. Data analysis and a discussion of the findings will be completed by the date of the conference. Planned Analyses: We will use intraclass correlations (ICC) and root mean square successive difference (RMSSD) to examine variability in social support. ICC analyses will examine variability at the between-person level while RMSSD examines variability within individual participants. We will then examine how within-person social support variability predicts next-day depression symptoms while controlling for same-day depression symptoms using multi-level modeling in R. We hypothesize that greater social support variability will predict greater depression symptom change. We will also explore moderating effects of concurrent cognitive behavioral therapy between these variables. Future directions and clinical implications for this work will also be discussed.

 
Coppersmith, D. D., Kleiman, E. M., Glenn, C. R., Millner, A. J., & Nock, M. K. (2019). The dynamics of social support among suicide attempters: A smartphone-based daily diary study. Behaviour research and therapy, 120, 103348.

Kellerman, J. K., Millner, A. J., Joyce, V. W., Nash, C. C., Buonopane, R., Nock, M. K., & Kleiman, E. M. (2022). Social support and nonsuicidal self-injury among adolescent psychiatric inpatients. Research on child and adolescent psychopathology, 50(10), 1351-1361.

Whisman, M. A. (2017). Interpersonal perspectives on depression. The Oxford handbook of mood disorders, 167-178.