Examining Cognitive Bias Modification interventions for reducing food value and choice: Two pre-registered, online studies.

Abstract

There is considerable interest in Cognitive Bias Modification (CBM) as a potential treatment for overweight / obesity. Inhibitory Control Training (ICT) and Evaluative Conditioning (EC) are two popular paradigms which rely on associatively learned responses (unhealthy food -> inhibition, or unhealthy food-> negative stimulus, respectively) through repeated cue-response contingencies. Both ICT and EC have demonstrated some effectiveness for reducing food intake, value and / or choice, when administered in the laboratory and online. However, studies have been criticised for inconsistencies in design (e.g. use of inadequate control groups) which makes it difficult to draw robust conclusions. In two pre-registered, online studies our aim was to examine active ICT (study 1) and EC (study 2) in multiple groups where the cue->response contingencies were systematically varied (100%, 75%, 50%, 25%), before examining food-cue valuations and hypothetical food choice. In both studies varying the cue-> response contingencies did not lead to significant changes in food-cue devaluation following training. ICT did not substantially influence hypothetical food choice, whereas there was weak evidence that EC reduced choice for unhealthy foods, compared to a control group with 50% cue-response contingencies. Taken together both studies provide limited evidence for online CBM as a viable psychological treatment – at least through the mechanism of food-cue devaluation or changes in healthy and unhealthy food choice. Future research is needed to investigate the factors that contribute towards successful CBM training to critically evaluate the potential for these strategies within health interventions.

The evidential value of research on cognitive training to change food‐related biases and unhealthy eating behavior: A systematic review and p‐curve analysis

“…After screening the titles and abstracts of all the entries, 38 full texts were examined, but 17 were excluded because they did not meet the inclusion criteria. Thus, 21 articles were added for analyses to those already identified by Forcano et al 23 Among the 45 selected articles, 13,17,19,20,21,30–69 12 included multiple studies, we therefore considered the results of 61 studies, (mean sample size = 115.84, SD = 109.53; range = 18–561).…”

Are commonly used lab‐based measures of food value and choice predictive of self‐reported real‐world snacking? An ecological momentary assessment study

“…Participants were presented with 10 images of snack food items (5 unhealthy, 5 healthy) and asked to rate each item on a Visual Analogue Scale (VAS) ranging from −100 (not at all appealing) to +100 (extremely appealing) to assess image appeal (‘How appealing do you find this image’) (e.g. Burger et al, 2011; Masterton et al, 2021). To avoid habituation, the 5 images presented for each category during the task were randomly selected from a possible 12 snack food items.…”

The Restrain Food Database: validation of an open-source database of foods that should be eaten more or less as part of a healthy diet

“…However, collections of images are typically non-standardized and often collated by researchers on a study-by-study basis. This is labour intensive and inefficient at a community level, and thus represents a constraint for many investigations [16].…”