Dissecting implicit food-related behaviors in Binge Eating Disorder and obesity: insights from a mobile approach-avoidance framework

Front Psychol. 2024 Oct 9:15:1435624. doi: 10.3389/fpsyg.2024.1435624. eCollection 2024.

Abstract

Introduction: Bulimic episodes experienced by patients with Binge Eating Disorder (BED) might be sustained by an enhanced behavioral propensity to approach food stimuli.

Methods: To test this hypothesis, automatic approach avoidance tendencies toward high-calorie foods (HCF), low-calorie foods (LCF), and neutral objects were assessed in a group of 23 patients with BED, and their performance was compared to the one of 17 patients with obesity without BED and a group of 32 normal weight participants. All participants performed a mobile approach-avoidance task in which they were required to approach and avoid different stimuli by respectively pulling their phone toward themselves or pushing it away. Reaction times were analyzed.

Results: Results showed a significant three-way interaction between group, type of movement and stimulus. Post-hoc analyses revealed that all the groups displayed an approach bias toward HCF. Patients with BED and healthy controls also displayed an approach bias toward LCF, a bias that was absent in obese individuals without BED. Moreover, patients with BED were faster in approaching food stimuli, both HCF and LCF, compared to healthy controls.

Discussion: These behavioral tendencies are quite consistent with the real-life attitudes of both BED patients and patients with obesity and might contribute to the maintenance of unhealthy eating habits such as binging in patients with BED and high-calorie diets in patients with obesity.

Keywords: Binge Eating Disorder; approach-avoidance bias; eating disorders; emotional eating; impulsivity; obesity.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the STARS@UNIPD funding program of the University of Padova, Italy, through the project: EXPLAIN_AN. Open Access funding provided by Università degli Studi di Padova, University of Padua, Open Science Committee.