Using the Misinformation Exposure-Trust Framework for Audience Segmentation: Predicting COVID-19 Vaccine Hesitancy Among U.S.

This study examines whether individuals’ exposure to and trust in COVID-19 vaccine misinformation can be used to segment audiences and explain variations in vaccine hesitancy and health beliefs. Using k-means clustering, a survey of 819 U.S. college students (March–May 2021) identifies four subgroups based on combinations of high or low misinformation exposure and trust: misinformation-shielded (low exposure, low trust), misinformation-vulnerable (low exposure, high trust), misinformation-resistant (high exposure, low trust), and misinformation-accepting (high exposure, high trust). These subgroups differ significantly in political ideology, vaccine hesitancy, and health beliefs. The misinformation-shielded subgroup reports more liberal views, lower hesitancy, and higher perceived efficacy, whereas the misinformation-vulnerable and misinformation-accepting subgroups perceive lower vaccine safety. Regression analyses show that perceived vaccine efficacy and perceived vaccine safety are relatively stable predictors of vaccine hesitancy. The misinformation exposure-trust framework offers a theory-based strategy for segmenting audiences and informs more targeted health interventions.