Using the misinformation exposure-trust framework for audience segmentation: Predicting COVID-19 vaccine hesitancy...

Area of Science:

• Public Health
• Health Communication
• Social Psychology

Background:

• Misinformation regarding COVID-19 vaccines is prevalent.
• Understanding audience segmentation is crucial for effective health interventions.
• Vaccine hesitancy and health beliefs are influenced by information exposure and trust.

Purpose of the Study:

• To determine if exposure to and trust in COVID-19 vaccine misinformation can segment audiences.
• To explain variations in vaccine hesitancy and health beliefs based on misinformation exposure and trust.
• To identify distinct subgroups within a college student population based on their interaction with misinformation.

Main Methods:

• K-means clustering was employed to segment 819 U.S. college students.
• Participants were categorized based on high/low exposure and high/low trust in COVID-19 vaccine misinformation.
• Regression analyses were used to identify predictors of vaccine hesitancy.

Main Results:

• Four subgroups emerged: misinformation-shielded, misinformation-vulnerable, misinformation-resistant, and misinformation-accepting.
• Subgroups differed significantly in political ideology, vaccine hesitancy, and health beliefs.
• Perceived vaccine efficacy and safety were stable predictors of vaccine hesitancy.

Conclusions:

• The misinformation exposure-trust framework provides a theory-based approach for audience segmentation.
• Targeted health interventions can be developed based on these identified subgroups.
• Understanding misinformation dynamics is key to addressing vaccine hesitancy.