covid vaccine

information seeking

regarding covid

health behavior

physical distancing

vaccination intentions

preventive behaviors

theory planned

vaccine hesitancy

American Journal of Health Promotion

Purpose This study aims to apply and extend the theory of planned behavior (TPB) to predict intention to take a COVID-19 vaccine. Design Cross-sectional. Setting Online. Sample Adult US residents recruited from Amazon Mechanical Turk ( n = 172). Measures Intention to take a COVID-19 vaccine (outcome variable), demographic variables (predictors), standard TPB variables (perceived behavioral control, attitude, and subjective norm; predictors), and non-TPB variables (anticipated regret, health locus of control, and perceived community benefit; predictors). Analysis Hierarchical linear regression predicting intention to take a COVID-19 vaccine, with demographic, standard TPB, and non-TPB variables entered in regression models 1, 2, and 3, respectively. Results The extended TPB model accounted for 72.5% of the variance in vaccination intention ( p &lt; .001), with perceived behavioral control ( β = .29, p &lt; .001), attitude ( β = .23, p = .043), and perceived community benefit ( β = .23, p = .020) being significant unique predictors. Conclusion Despite the relatively small and non-representative sample, this study, conducted after COVID-19 vaccines were widely available in the USA, demonstrated that perceived behavioral control was the most robust predictor of intention to take a COVID-19 vaccine, suggesting that the TPB is a useful theoretical framework that can inform effective strategies to promote vaccine acceptance.

Predicting Intention to Take a COVID-19 Vaccine in the United States: Application and Extension of Theory of Planned Behavior