Predicting the Avoidance of Body Weight Information Using Novel Measures of Trait Information Avoidance

Abstract

Information avoidance is a growing topic of study in the field of behavioral economics. It has been conceptualized as a form of psychological threat management, is suggested to be a generally stable trait. Moreover, trait information avoidance has been shown to predict real-world information decisions. This study aims to explore the phenomenon of body weight information avoidance, which remains poorly understood. 836 participants completed an online survey containing measures of constructs related to suggested information avoidance mechanisms. Notably, this survey included two measures of trait information avoidance, the Information Avoidance Scale and the recently-developed Information Preferences Scale, that previously demonstrated predictive abilities. Participants later chose between obtaining or avoiding weight information in the form of a body fat percentage estimate. Using a series of logistic regression and Lasso regularization models, this study finds a strong effect for predicting information avoidance using the Information Avoidance Scale, and a moderate effect for predicting information avoidance using the Information Preferences Scale

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