Retraining of automatic action tendencies in individuals with obesity: A randomized controlled trial.

Hannah Ferentzi, Hannah Scheibner, Reinout Wiers, Eni S Becker, Johannes Lindenmeyer, Sylvia Beisel, Mike Rinck

Journal: Appetite 2019;126():66-72

PMID: 29596869

Abstract

Obesity is a major health concern, characterized by an automatically activated tendency to (over)-eat. Recent research suggests that an effective way to counteract automatic approach tendencies in unhealthy consumption behavior might be approach bias modification. Therefore, we investigated an approach-avoidance training for unhealthy food cues in 189 patients with obesity of a psychosomatic inpatient clinic who were participating in a nutrition advice program. Patients in the active training group were trained to make avoidance movements (pushing a joystick) in response to unhealthy food pictures and approach movements (pulling the joystick) in response to positive pictures, while the control group received sham training (approaching and avoiding both picture types). Approach-avoidance bias, body mass index, eating pathology and food-specific implicit associations were assessed before and after the training. In line with our hypothesis, approach-avoidance bias improved in the active training group after the training, in comparison to the sham training group. Moreover, this effect generalized to new, untrained stimuli. However, no effects of the training were found in a food-specific Single-Target Implicit Association Test, or on eating pathology questionnaires or body mass index. While the training results are promising, the effect of approach-avoidance bias modification on relevant behavior in obesity has yet to be established before it may be implemented as an add-on treatment.

Copyright © 2018 Elsevier Ltd. All rights reserved.

Address: Behavioural Science Institute, Radboud University Nijmegen, The Netherlands.; University of Amsterdam, The Netherlands.; Salus Clinic Lindow, Germany.; Behavioural Science Institute, Radboud University Nijmegen, The Netherlands. Electronic address: [email protected].

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