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The psychometric properties of motors of COVID-19 vaccination acceptance scale (MoVac-COVID19S): A dataset across five regions
The novel coronavirus disease 2019 (COVID-19) continues to plague the world. Hence, there is been an effort to mitigate this virus and its effects with several means including vaccination which is one of the most effective ways of controlling the virus. However, efforts at getting people to vaccinat...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8957882/ https://www.ncbi.nlm.nih.gov/pubmed/35372646 http://dx.doi.org/10.1016/j.dib.2022.108103 |
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author | Ahorsu, Daniel Kwasi Lin, Chung-Ying Chen, I-Hua Ullah, Irfan Shoib, Sheikh Zahid, Shafi Ullah Adjaottor, Emma Sethina Addo, Frimpong-Manso Pakpour, Amir H |
author_facet | Ahorsu, Daniel Kwasi Lin, Chung-Ying Chen, I-Hua Ullah, Irfan Shoib, Sheikh Zahid, Shafi Ullah Adjaottor, Emma Sethina Addo, Frimpong-Manso Pakpour, Amir H |
author_sort | Ahorsu, Daniel Kwasi |
collection | PubMed |
description | The novel coronavirus disease 2019 (COVID-19) continues to plague the world. Hence, there is been an effort to mitigate this virus and its effects with several means including vaccination which is one of the most effective ways of controlling the virus. However, efforts at getting people to vaccinate have met several challenges. To help with understanding the reasons underlying an individual's willingness to take COVID-19 vaccine or not, a scale called Motors of COVID-19 Vaccination Acceptance Scale (MoVac-COVID19S) was developed. To expand its usability worldwide (as it has currently been limited to only China and Taiwan), data were collected in other countries (regions) too. Therefore, this MoVac-COVID19S data is from five countries (that is, India, Ghana, Afghanistan, Taiwan, and mainland China) which cut across five regions. A total of 6053 participants across the stated countries completed the survey between January and March 2021 using a cross-sectional survey design. The different sections of the survey solicited sociodemographic information (e.g., country, age, gender, educational level, and profession) and the MoVac-COVID19S data from the participants. The data collected from this survey were analyzed using descriptive statistics, which were carried out using the IBM SPSS version 22.0. |
format | Online Article Text |
id | pubmed-8957882 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-89578822022-03-28 The psychometric properties of motors of COVID-19 vaccination acceptance scale (MoVac-COVID19S): A dataset across five regions Ahorsu, Daniel Kwasi Lin, Chung-Ying Chen, I-Hua Ullah, Irfan Shoib, Sheikh Zahid, Shafi Ullah Adjaottor, Emma Sethina Addo, Frimpong-Manso Pakpour, Amir H Data Brief Data Article The novel coronavirus disease 2019 (COVID-19) continues to plague the world. Hence, there is been an effort to mitigate this virus and its effects with several means including vaccination which is one of the most effective ways of controlling the virus. However, efforts at getting people to vaccinate have met several challenges. To help with understanding the reasons underlying an individual's willingness to take COVID-19 vaccine or not, a scale called Motors of COVID-19 Vaccination Acceptance Scale (MoVac-COVID19S) was developed. To expand its usability worldwide (as it has currently been limited to only China and Taiwan), data were collected in other countries (regions) too. Therefore, this MoVac-COVID19S data is from five countries (that is, India, Ghana, Afghanistan, Taiwan, and mainland China) which cut across five regions. A total of 6053 participants across the stated countries completed the survey between January and March 2021 using a cross-sectional survey design. The different sections of the survey solicited sociodemographic information (e.g., country, age, gender, educational level, and profession) and the MoVac-COVID19S data from the participants. The data collected from this survey were analyzed using descriptive statistics, which were carried out using the IBM SPSS version 22.0. Elsevier 2022-03-27 /pmc/articles/PMC8957882/ /pubmed/35372646 http://dx.doi.org/10.1016/j.dib.2022.108103 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Ahorsu, Daniel Kwasi Lin, Chung-Ying Chen, I-Hua Ullah, Irfan Shoib, Sheikh Zahid, Shafi Ullah Adjaottor, Emma Sethina Addo, Frimpong-Manso Pakpour, Amir H The psychometric properties of motors of COVID-19 vaccination acceptance scale (MoVac-COVID19S): A dataset across five regions |
title | The psychometric properties of motors of COVID-19 vaccination acceptance scale (MoVac-COVID19S): A dataset across five regions |
title_full | The psychometric properties of motors of COVID-19 vaccination acceptance scale (MoVac-COVID19S): A dataset across five regions |
title_fullStr | The psychometric properties of motors of COVID-19 vaccination acceptance scale (MoVac-COVID19S): A dataset across five regions |
title_full_unstemmed | The psychometric properties of motors of COVID-19 vaccination acceptance scale (MoVac-COVID19S): A dataset across five regions |
title_short | The psychometric properties of motors of COVID-19 vaccination acceptance scale (MoVac-COVID19S): A dataset across five regions |
title_sort | psychometric properties of motors of covid-19 vaccination acceptance scale (movac-covid19s): a dataset across five regions |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8957882/ https://www.ncbi.nlm.nih.gov/pubmed/35372646 http://dx.doi.org/10.1016/j.dib.2022.108103 |
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