From Features to Goals: Shaping Food Utility Through Shared Features and Goal-Directed Inference

When people encounter a new stimulus, they may draw on their knowledge of similar stimuli to make inferences. This mechanism is captured by the Shared Features Principles (SFP, https://doi.org/10.1037/xge0000777). However, while SFP facilitates attribute transfer between stimuli, it does not inherently predict behavior. This research integrates SFP with the Goal-Directed Perspective (GDP), which posits that individuals choose actions based on the perceived utility of achieving specific goals. We propose that feature sharing can influence goal-relevant attributes of novel foods, thereby altering their expected utility and shaping food-related behaviors. Across two pre-registered experimental studies (total N = 340), we investigated whether pairing novel foods with either tasty or healthy products via a shared, non-diagnostic feature (a colored frame) could enhance their perceived tastiness or healthiness, respectively. Study 1 employed unfamiliar food items, while Study 2 replicated the procedure using insect-based foods—a particularly challenging case due to the possibility of pre-existing negative associations. In both studies, participants attributed greater expected utility (assessed via implicit and explicit measures) to target foods paired with goal-relevant sources. Data were analyzed using both frequentist and Bayesian methods. These findings suggest that SFP-based interventions can systematically modify the perceived utility of foods in serving taste or health goals, including products that may elicit negative reactions, like insect-based foods. This novel integration of SFP and GDP opens promising avenues for promoting sustainable food choices through non-invasive and scalable interventions.