A comparative investigation of interventions to reduce anti-fat prejudice across five implicit measures.

Abstract

The severity and pervasiveness of anti-fat prejudice and discrimination have led to calls for interventions to address them. However, intervention studies to combat anti-fat prejudice have often been stymied by ineffective approaches, small sample sizes, and the lack of standardization in measurement. To that end, we conducted two mega-experiments totaling 27,726 participants and 50 conditions where we tested five intervention approaches to reduce implicit anti-fat prejudice across five implicit measures. We found that interventions were most effective at reducing implicit weight biases when they instructed people to practice an explicit rule linking fat people with good things and thin people with bad things. Interventions that were more indirect or relied on associative learning tended to be ineffective. We also found that change in implicit bias on one implicit measure often generalized to other implicit measures. However, the Evaluative Priming Task and single-target measures of implicit bias like the Single-Target Implicit Association Test were much less sensitive to change. These findings illuminate promising approaches to combating implicit anti-fat prejudice and advance understanding of how implicit bias change generalizes across measures. (PsycInfo Database Record (c) 2025 APA, all rights reserved).