Volume 16, Issue 3 (Autumn 2024)
2024, 16(3): 1-12 |
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moravejjifar M, nasrabadi M, Khandehroo M, hassannia R, Peyman N. A Systematic Review of the Use of Health-oriented Models and Theories in Predicting the Acceptance of the COVID-19 Vaccination. North Khorasan University of Medical Sciences 2024; 16 (3) :1-12
URL: http://journal.nkums.ac.ir/article-1-3056-en.html
URL: http://journal.nkums.ac.ir/article-1-3056-en.html
Mahin Moravejjifar1 
, Maryam Nasrabadi1 , Mansooreh Khandehroo1 , Reza Hassannia2 , Nooshin Peyman *3
, Maryam Nasrabadi1 , Mansooreh Khandehroo1 , Reza Hassannia2 , Nooshin Peyman *3
1- Ph.D. Candidate of Health Education& Health Promotion, Student Research Committee, Mashhad University of Medical Sciences, Iran
2- Master of Medical-Surgical Nursing, School of Nursing, Gonabad University of Medical Sciences, Gonabad, Iran
3- Social Determinants of Health Research Center, Mashhad University of Medical Sciences. Mashhad, Iran ,Peymann@mums.ac.ir
2- Master of Medical-Surgical Nursing, School of Nursing, Gonabad University of Medical Sciences, Gonabad, Iran
3- Social Determinants of Health Research Center, Mashhad University of Medical Sciences. Mashhad, Iran ,
Abstract: (625 Views)
Introduction: Understanding behavioral factors affecting vaccine acceptance using health-oriented models/theories as a practical and structured model helps to design appropriate interventions for better disease management. It provides a better understanding of the application and capacity of models and theories in the prediction of behavioral intention. Therefore, the present study aimed to assess studies based on health-oriented model/theories in predicting the acceptance of COVID-19 vaccination in a systematic way.
Method: In this systematic review study, the keywords related to the aims of the study were searched in databases, such as PubMed, Scopus, and Google Scholar, without a time limit and until February 2022, based on the PRISMA statement. To prevent bias, two researchers independently performed a search and screening.
Results: Finally, 32 articles that met the inclusion criteria were examined. The predictability of the models varied from 39%-76%, and this was not reported in some studies. The most widely used models, respectively, were the health belief model and the theory of planned behavior, which were used alone or in combination in some studies. In a study comparing these two models, the theory of planned behavior was more predictive.
Conclusion: Health-oriented models/theories, especially the health belief model and the theory of planned behavior, have been able to play a critical role in predicting willingness to be vaccinated against COVID-19 in different populations. Therefore, it is necessary to use a suitable and efficient strategy to develop the structures of these models or combine them with other patterns and models
Method: In this systematic review study, the keywords related to the aims of the study were searched in databases, such as PubMed, Scopus, and Google Scholar, without a time limit and until February 2022, based on the PRISMA statement. To prevent bias, two researchers independently performed a search and screening.
Results: Finally, 32 articles that met the inclusion criteria were examined. The predictability of the models varied from 39%-76%, and this was not reported in some studies. The most widely used models, respectively, were the health belief model and the theory of planned behavior, which were used alone or in combination in some studies. In a study comparing these two models, the theory of planned behavior was more predictive.
Conclusion: Health-oriented models/theories, especially the health belief model and the theory of planned behavior, have been able to play a critical role in predicting willingness to be vaccinated against COVID-19 in different populations. Therefore, it is necessary to use a suitable and efficient strategy to develop the structures of these models or combine them with other patterns and models
Type of Study: Review Article |
Subject:
Basic Sciences
Received: 2023/09/5 | Accepted: 2024/01/6 | Published: 2024/09/24
Received: 2023/09/5 | Accepted: 2024/01/6 | Published: 2024/09/24
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