Specificity of the jumping-to-conclusion bias in social anxiety: An account using the Bayesian computational modeling approach

To date, little is known about the role of social anxiety in the assignment of evidence weights which could contribute to the jumping-to-conclusion bias. The present study used a Bayesian computational method to understand the mechanism of jumping-to-conclusion bias in social anxiety, specifically through the assignment of weights to information sampled. The present study also investigated the specificity of the jumping-to-conclusion bias in social anxiety using three variations of beads tasks that consisted of neutral and socially threatening situations. A sample of 210 participants was recruited from online communities to complete the beads tasks and a set of questionnaires measuring the trait variables including social anxiety and the fears of positive and negative evaluation. The Bayesian model estimations indicated that social anxiety and fears of evaluation significantly biased the assignment of evidence weights to information received in certain conditions of the beads tasks. Our results indicated that social anxiety and fear of evaluation could influence belief updating depending on situations. However, the influences from these trait variables seemed to be insufficient in contributing to the jumping-to-conclusion bias.