Social Media Use and Rejection Sensitivity: Impact of the menstrual cycle, social reward neurophysiology and online experiences

About This Grant

PROJECT SUMMARY Social media use is associated with increased risk of psychopathology in adolescents, yet the underlying mechanisms linking social media use with mental illness are poorly understood. Social media use facilitates near constant peer evaluation and social feedback, which amplifies the potential for rejection sensitivity, the heightened physiological and emotional responses to social loss or rejection. Rejection sensitivity is of particular importance given that it is a transdiagnostic prodromal symptom of severe psychopathology (e.g., depression), that emerges during adolescence. Social media use engages social reward neural circuitry, which is altered in depression and modified by estradiol (E2), making it a promising neurophysiological candidate linking social media use and female adolescent depression. There is limited data on what makes an individual more sensitive to the impact of social media use, and what neurophysiological and psychological factors contribute to increased risk of depression linked to online experiences. To address this gap and extend the research in an innovative new direction, the primary objective of this project is to elucidate the social media characteristics (network features and positive/negative online experiences) and endocrine contexts in which online experiences have the largest impact on rejection sensitivity and depressive symptoms. We will focus on the perimenstrual window of the menstrual cycle as a vulnerable or “risky” context that contributes to disruptions in social reward neurophysiology, rejection sensitivity related to online experiences, and depressive symptoms in female adolescents. Two counterbalanced neurobehavioral testing sessions with EEG during perimenstrual E2 change and stable, mid-follicular E2 change will probe the cycle-related neurophysiological indices of social media- related reward responsiveness and how they relate to rejection sensitivity. Further, we will use data donation packages to code for online positive and negative experiences and conduct network analyses grounded in graph theory to characterize social media networks to determine the impact of network density (i.e., number of online connections), clustering, and communities (social groups), perceived and extracted online experiences on rejection sensitivity and depressive symptoms. This multimodal design will allow us to address the following specific aims: determine the extent to which rejection sensitivity is characterized by perceived social media experiences and neurophysiology of reward responsiveness, particularly during perimenstrual E2 change (Aim 1), and social media network characteristics (Aim 2), to determine how these measures may interact to predict depressive symptoms (Aim 3). Our central hypothesis is that greater rejection sensitivity will be associated with disrupted social reward responsiveness and greater perceived negative social media interactions, particularly during perimenstrual E2 change and in the context of high-density social media networks with fewer defined social groups. This research will help identify neurophysiological indices of social reward responsiveness and social media network characteristics that precipitate rejection sensitivity and susceptibility to depression.