The effect of body image dissatisfaction on goal-directed decision making in a population marked by negative appearance beliefs and disordered eating

Abstract

Eating disorders are associated with one of the highest mortality rates among all mental disorders, yet there is very little research about them within the newly emerging and promising field of computational psychiatry. As such, we focus on investigating a previously unexplored, yet a core aspect of eating disorders – body image preoccupation. We continue a freshly opened debate about model-based learning in eating disorders and perform a study that utilises a two-step decision-making task and a reinforcement learning model to understand the effect of body image preoccupation on model-based learning in a subclinical eating disorder population, as recruited using Prolific. We find a significantly reduced model-based contribution in the body image disturbance task condition in the eating disorder group as compared to a healthy control. We propose a new digital biomarker that significantly predicts disordered eating, and body image issues.