Universal Predictors of Dental Students' Attitudes towards COVID-19 Vaccination: Machine Learning-Based Approach
Status PubMed-not-MEDLINE Language English Country Switzerland Media electronic
Document type Journal Article
Grant support
MUNI/A/1608/2020
Masaryk University
MUNI/IGA/1543/2020
Masaryk University
LTC20031
Ministry of Education Youth and Sports
PubMed
34696266
PubMed Central
PMC8539257
DOI
10.3390/vaccines9101158
PII: vaccines9101158
Knihovny.cz E-resources
- Keywords
- COVID-19 vaccines, decision making, decision trees, dental education, international association of dental students, machine learning, mass vaccination, regression analysis,
- Publication type
- Journal Article MeSH
BACKGROUND: young adults represent a critical target for mass-vaccination strategies of COVID-19 that aim to achieve herd immunity. Healthcare students, including dental students, are perceived as the upper echelon of health literacy; therefore, their health-related beliefs, attitudes and behaviors influence their peers and communities. The main aim of this study was to synthesize a data-driven model for the predictors of COVID-19 vaccine willingness among dental students. METHODS: a secondary analysis of data extracted from a recently conducted multi-center and multi-national cross-sectional study of dental students' attitudes towards COVID-19 vaccination in 22 countries was carried out utilizing decision tree and regression analyses. Based on previous literature, a proposed conceptual model was developed and tested through a machine learning approach to elicit factors related to dental students' willingness to get the COVID-19 vaccine. RESULTS: machine learning analysis suggested five important predictors of COVID-19 vaccination willingness among dental students globally, i.e., the economic level of the country where the student lives and studies, the individual's trust of the pharmaceutical industry, the individual's misconception of natural immunity, the individual's belief of vaccines risk-benefit-ratio, and the individual's attitudes toward novel vaccines. CONCLUSIONS: according to the socio-ecological theory, the country's economic level was the only contextual predictor, while the rest were individual predictors. Future research is recommended to be designed in a longitudinal fashion to facilitate evaluating the proposed model. The interventions of controlling vaccine hesitancy among the youth population may benefit from improving their views of the risk-benefit ratio of COVID-19 vaccines. Moreover, healthcare students, including dental students, will likely benefit from increasing their awareness of immunization and infectious diseases through curricular amendments.
Clinical Research Unit Egas Moniz Cooperativa de Ensino Superior 2829 511 Almada Portugal
Department of Psychology Faculty of Social Studies Masaryk University 602 00 Brno Czech Republic
Department of Public Health Faculty of Medicine Masaryk University 625 00 Brno Czech Republic
International Association of Dental Students 1216 Geneva Switzerland
Public Health Committee World Dental Federation 1216 Geneva Switzerland
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Nuclear Anxiety Amid the Russian-Ukrainian War 2022 (RUW-22): Descriptive Cross-Sectional Study
