Nudging Healthy Choices in Food Search through List Re-Ranking

As the Internet is becoming a popular source of food recipes, studies show that they also contribute to health problems. A particular problem is that personalized food platforms promote recipes that contain large amounts of fat, sodium, and sugar. Filtering recipes on their health content would be possible, but this might lead to dissatisfaction among users, as unhealthy recipes tend to be popular. As a new contribution, we propose to not change the presented content but how it is presented: the decision context. We present a work-in-progress that aims to steer users of a recipe search portal towards healthier choices through the serial-position effect, which predicts that users are biased towards higher-ranked items. We report a 2x2-within-subjects experiment, in which 17 participants searched for four different recipes and were asked to choose one recipe they liked the most from each list. Search results were either presented from high (low) to low (sodium) content and were personalized or not. Our analysis suggested that matching the content towards the user's eating goals might overcome the effectiveness of serial-position nudges, while we found no average differences in user satisfaction levels across the two ranking scenarios.