Knowledge, Attitude, and Perception of Health and Non-Healthcare Workers Towards COVID-19 Vaccination: Machine Learning Approach
International Journal of Sustainable Development and Planning
; 17(7):2015-2021, 2022.
Article
in English
| Scopus | ID: covidwho-2204532
ABSTRACT
There have been concerns globally as to whether taking COVID-19 vaccination is harmful or not. In this study, we conducted an online survey to measure the knowledge and attitude of people, first about COVID-19, and second about COVID-19 vaccination—various analyses such as descriptive statistics, logistic regression, and support vector regression with k-fold cross-validation. The support vector machine and tuned support vector machine suggest a better fit based on cross-validation error. The results show that immigration requirements significantly explain why an individual would accept the COVID-19 vaccine. This study suggests that people in authority should look into people's concerns regarding taking the COVID-19 vaccine and address them accordingly. The study aims to draw the attention of the people to the concern that surrounds taking COVID-19 vaccination and explored various statistical techniques to draw inference. © 2022 WITPress. All rights reserved.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Topics:
Vaccines
Language:
English
Journal:
International Journal of Sustainable Development and Planning
Year:
2022
Document Type:
Article
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