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Using the integrative model of behavioural prediction to understand COVID-19 vaccine hesitancy behaviour
The officials realized that the vaccination drive alone would not be sufficient, but the individual's response towards getting vaccinated needs to be assessed and addressed, especially in India, where the diverse culture could widely affect the population's vaccination behaviour. The stud...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9166190/ https://www.ncbi.nlm.nih.gov/pubmed/35661762 http://dx.doi.org/10.1038/s41598-022-12466-0 |
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author | Romate, John Rajkumar, Eslavath Greeshma, Rajgopal |
author_facet | Romate, John Rajkumar, Eslavath Greeshma, Rajgopal |
author_sort | Romate, John |
collection | PubMed |
description | The officials realized that the vaccination drive alone would not be sufficient, but the individual's response towards getting vaccinated needs to be assessed and addressed, especially in India, where the diverse culture could widely affect the population's vaccination behaviour. The study aimed to identify the predictors of vaccine hesitancy behaviour using the health belief model and theory of planned behaviour and understand mediating and moderating influence of knowledge and social support on the relationship between the predictors and vaccine hesitancy behaviours among the Indian population. Data was collected from 1006 samples. Regression analysis was performed to assess the variances exerted on vaccine hesitancy behaviours. Also, SEM AMOS was employed to examine the mediation and moderation effects of knowledge about vaccines and social support. The findings indicated that around 11% of the respondents were hesitant to get vaccinated. The combined models of HBM and TPB provide high predictive power. The analysis also revealed that knowledge about vaccine significantly mediates partially between a few constructs of HBM and TPB concerning hesitancy. This study provides the theoretical framework and suggests that the health belief model and the theory of planned behaviour model could explain the psychological influences of vaccine hesitancy in India. |
format | Online Article Text |
id | pubmed-9166190 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-91661902022-06-06 Using the integrative model of behavioural prediction to understand COVID-19 vaccine hesitancy behaviour Romate, John Rajkumar, Eslavath Greeshma, Rajgopal Sci Rep Article The officials realized that the vaccination drive alone would not be sufficient, but the individual's response towards getting vaccinated needs to be assessed and addressed, especially in India, where the diverse culture could widely affect the population's vaccination behaviour. The study aimed to identify the predictors of vaccine hesitancy behaviour using the health belief model and theory of planned behaviour and understand mediating and moderating influence of knowledge and social support on the relationship between the predictors and vaccine hesitancy behaviours among the Indian population. Data was collected from 1006 samples. Regression analysis was performed to assess the variances exerted on vaccine hesitancy behaviours. Also, SEM AMOS was employed to examine the mediation and moderation effects of knowledge about vaccines and social support. The findings indicated that around 11% of the respondents were hesitant to get vaccinated. The combined models of HBM and TPB provide high predictive power. The analysis also revealed that knowledge about vaccine significantly mediates partially between a few constructs of HBM and TPB concerning hesitancy. This study provides the theoretical framework and suggests that the health belief model and the theory of planned behaviour model could explain the psychological influences of vaccine hesitancy in India. Nature Publishing Group UK 2022-06-04 /pmc/articles/PMC9166190/ /pubmed/35661762 http://dx.doi.org/10.1038/s41598-022-12466-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Romate, John Rajkumar, Eslavath Greeshma, Rajgopal Using the integrative model of behavioural prediction to understand COVID-19 vaccine hesitancy behaviour |
title | Using the integrative model of behavioural prediction to understand COVID-19 vaccine hesitancy behaviour |
title_full | Using the integrative model of behavioural prediction to understand COVID-19 vaccine hesitancy behaviour |
title_fullStr | Using the integrative model of behavioural prediction to understand COVID-19 vaccine hesitancy behaviour |
title_full_unstemmed | Using the integrative model of behavioural prediction to understand COVID-19 vaccine hesitancy behaviour |
title_short | Using the integrative model of behavioural prediction to understand COVID-19 vaccine hesitancy behaviour |
title_sort | using the integrative model of behavioural prediction to understand covid-19 vaccine hesitancy behaviour |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9166190/ https://www.ncbi.nlm.nih.gov/pubmed/35661762 http://dx.doi.org/10.1038/s41598-022-12466-0 |
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