Please use this identifier to cite or link to this item:
Title: A Predictive Model of Pandemic Disaster Fear Caused by Coronavirus (COVID-19): Implications for Decision-Makers
Authors: M. Cvetković, Vladimir
Nikolic, Neda
ÖCAL, Adem
Martinovic J.
Dragasevic, Aleksandar
Journal: International Journal of Environmental Research and Public Health
Issue Date: 1-Jan-2022
Abstract: This paper presents quantitative research results regarding a predictive model of pandemic disaster fear caused by the coronavirus disease (COVİD-19). The aim of this paper was to establish the level and impact of certain demographic and socioeconomic characteristics on pandemic disaster fear caused by the coronavirus (COVID-19). The research was conducted using a questionnaire that was provided and then collected online for 1226 respondents during May 2021. A closed, five-point Likert scale was used to create the structured questionnaire. The first section of the questionnaire included research questions about the participants’ socioeconomic and demographic characteristics, while the second section included issue questions about fear caused by COVID-19. The results of multivariate regression analyses showed the most important predictor for fear of COVID-19 to be gender, followed by age and education level. Furthermore, the results of t-tests showed statistically significant differences between men and women in terms of different aspects of pandemic disaster fear caused by the coronavirus disease. Our results have several significant public health implications. Women who were more educated and knowledgeable, married, and older, reported a greater fear of the outbreak at various levels. Decision-makers can use these findings to identify better strategic opportunities for pandemic disaster risk management.
Type: Article
DOI: 10.3390/ijerph19020652
ISSN: 16617827
SCOPUS: 85122204917
Appears in Collections:Faculty of Technical Sciences, Čačak
[ Google Scholar ]

Page views(s)




Files in This Item:
File Description SizeFormat 
10.3390-ijerph19020652.pdf3.91 MBAdobe PDFThumbnail

Items in SCIDAR are protected by copyright, with all rights reserved, unless otherwise indicated.