Computational Mechanisms of Self-Enhancement During Social Comparison and Their Relationship to Internalizing Symptoms
Abstract
Internalizing disorders, such as anxiety and depression, commonly feature cognitive biases in self-evaluation, particularly in the context of social comparison. Despite the role of such biases in the severity and prognosis of internalizing disorders, limited work has identified computational mechanisms underlying self-evaluative biases in social contexts. In a sample of N = 292 participants, in the present study, we applied hierarchical Bayesian computational modeling to a trait-evaluation task in which individuals choose whether positive and negative traits better describe themselves or a close friend. We found that individuals generally engage in self-enhancement during this task, more efficiently processing information that supports positive self-schema. However, this effect flips as individuals report more symptoms such that it becomes more difficult to integrate evidence in support of a positive self-concept. These findings suggest that altered processing of both positive and negative self-referential information is a transdiagnostic mechanism driving aberrant self-evaluation in internalizing disorders.
