Predicting Intention to Take a COVID-19 Vaccine in the United States: Application and Extension of Theory of Planned Behavior.
Am J Health Promot
; 36(4): 710-713, 2022 05.
Article
in English
| MEDLINE | ID: covidwho-1625274
ABSTRACT
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 (ß = .29, p < .001), attitude (ß = .23, p = .043), and perceived community benefit (ß = .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.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
COVID-19 Vaccines
/
COVID-19
Type of study:
Observational study
/
Prognostic study
/
Randomized controlled trials
Topics:
Vaccines
Limits:
Adult
/
Humans
Country/Region as subject:
North America
Language:
English
Journal:
Am J Health Promot
Journal subject:
Public Health
Year:
2022
Document Type:
Article
Affiliation country:
08901171211062584
Similar
MEDLINE
...
LILACS
LIS