Facemask-wearing behavior to prevent COVID-19 and associated factors among public and private bank workers in Ethiopia

Given widespread vulnerability to COVID-19 infection in areas with low vaccination rates, facemask wearing is repeatedly emphasized for the general population including bank workers, who have contact with many customers each day. Over the first year of the COVID-19 pandemic, studies focused on facem...

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Bibliographic Details
Published in:PloS one 2021-12, Vol.16 (12), p.e0259659
Main Authors: Hassen, Seada, Adane, Metadel
Format: Article
Language:English
Subjects:
Attitudes
Bankers
Banks
Behavior
Biology and Life Sciences
Chronic illnesses
Confidence intervals
Coronaviruses
COVID-19
Data analysis
Data collection
Health aspects
Health care
Health risks
Infection control
Masks
Medical personnel
Medicine and Health Sciences
Methods
Pandemics
People and Places
Random sampling
Regression models
Research and Analysis Methods
Sampling techniques
Social aspects
Social Sciences
Statistical analysis
Statistical sampling
Vaccination
Viral diseases
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Summary:Given widespread vulnerability to COVID-19 infection in areas with low vaccination rates, facemask wearing is repeatedly emphasized for the general population including bank workers, who have contact with many customers each day. Over the first year of the COVID-19 pandemic, studies focused on facemask wearing among healthcare workers but not among bank workers, who are also at risk of COVID-19. To address this gap and to consider intervention measures that encourage the wearing of facemasks, this study was conducted to identify behaviors of facemask wearing and associated factors among bank workers in Dessie City, Ethiopia. An institution-based cross-sectional study was conducted among 413 bank workers who were selected using a simple random sampling technique from January 1.sup.st to 30.sup.th, 2021 in Dessie City, Ethiopia. Data were collected using a structured questionnaire and on-the-spot observational checklist. The collected data were checked, coded and entered to EpiData version 4.6 and exported to Statistical Package for Social Sciences (SPSS) version 25.0 for data cleaning and analysis. Data were analyzed using bivariable (crude odds ratio [COR]) and multivariable (adjusted odds ratio [AOR]) logistic regression model at 95% confidence interval (CI). Variables from the bivariable analysis with a p-value
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0259659