TY - JOUR
T1 - Predicting Intention to Take a COVID-19 Vaccine in the United States
T2 - Application and Extension of Theory of Planned Behavior
AU - Hayashi, Yusuke
AU - Romanowich, Paul
AU - Hantula, Donald A.
N1 - Funding Information:
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by a Research Development Grant from Office of Academic Affairs at Pennsylvania State University, Hazleton.
Publisher Copyright:
© The Author(s) 2022.
PY - 2022/5
Y1 - 2022/5
N2 - 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 <.001), with perceived behavioral control (β =.29, p <.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.
AB - 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 <.001), with perceived behavioral control (β =.29, p <.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.
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U2 - 10.1177/08901171211062584
DO - 10.1177/08901171211062584
M3 - Article
C2 - 35041541
AN - SCOPUS:85123346775
SN - 0890-1171
VL - 36
SP - 710
EP - 713
JO - American Journal of Health Promotion
JF - American Journal of Health Promotion
IS - 4
ER -