A Bayesian model of the jumping-to-conclusions bias and its relationship to psychopathology

Abstract

ABSTRACT The mechanisms by which delusion and anxiety affect the tendency to make hasty decisions (Jumping-to-Conclusions bias) remain unclear. This paper proposes a Bayesian computational model that explores the assignment of evidence weights as a potential explanation of the Jumping-to-Conclusions bias using the Beads Task. We also investigate the Beads Task as a repeated measure by varying the key aspects of the paradigm. The Bayesian model estimations from two online studies showed that higher delusional ideation promoted reduced belief updating but the impact of general and social anxiety on evidence weighting was inconsistent. The altered evidence weighting as a result of a psychopathological trait appeared insufficient in contributing to the Jumping-to-Conclusions bias. Variations in Beads Task aspects significantly affected subjective certainty at the point of decisions but not the number of draws to decisions. Repetitions of the Beads Task are feasible if one assesses the Jumping-to-Conclusions bias using number of draws to decisions.