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Application of health belief model to predict COVID-19-preventive behaviors among a sample of Iranian adult population

BACKGROUND: The novel coronavirus (COVID-19) has infected nearly 9.5 million people in 216 countries, areas, or territories in the world. The fight against the COVID-19 has become a very serious international challenge. The aim of this study was to determine the predictors of COVID-19-preventive beh...

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Autores principales: Mirzaei, Amin, Kazembeigi, Farogh, Kakaei, Hojatollah, Jalilian, Mohsen, Mazloomi, Sajad, Nourmoradi, Heshmatollah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8057168/
https://www.ncbi.nlm.nih.gov/pubmed/34084816
http://dx.doi.org/10.4103/jehp.jehp_747_20
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author Mirzaei, Amin
Kazembeigi, Farogh
Kakaei, Hojatollah
Jalilian, Mohsen
Mazloomi, Sajad
Nourmoradi, Heshmatollah
author_facet Mirzaei, Amin
Kazembeigi, Farogh
Kakaei, Hojatollah
Jalilian, Mohsen
Mazloomi, Sajad
Nourmoradi, Heshmatollah
author_sort Mirzaei, Amin
collection PubMed
description BACKGROUND: The novel coronavirus (COVID-19) has infected nearly 9.5 million people in 216 countries, areas, or territories in the world. The fight against the COVID-19 has become a very serious international challenge. The aim of this study was to determine the predictors of COVID-19-preventive behaviors using the health belief model (HBM). MATERIALS AND METHODS: This cross-sectional study was conducted with the participation of 558 samples from the adult population of Iran. The online convenience sampling was conducted in this research. The online 68-item questionnaire link was published all over Iran through social networks including Telegram and WhatsApp, which are common in Iran. The data were analyzed using SPSS software version 19. Descriptive statistics, bivariate Pearson's correlation test, and multiple linear regression were used to analyze the data. RESULTS: The mean age of the subjects was 33.3 ± 10.01 years. The participants were often female (61.3%), married (57.9%), and resident of the city (81.0%) with university educational level (78.8%). The results showed that the HBM structures predicted 29.3% of the preventive behaviors of COVID-19 in the subjects. The perceived benefits, perceived barriers, and self-efficacy significantly predicted the preventive behaviors, but the perceived susceptibility and perceived severity were not significant in the regression model. The internet and virtual social networks (49.8%), broadcast (33.5%), and healthcare providers (15.8%) were the most important sources of information related with COVID-19. In response to COVID-19-related internal cues to action, 36.6% did not pay attention and 34.7% tried to self-medicate. Only 28.5% of the subjects referred to the hospital, healthcare center, or physician. CONCLUSION: Self-efficacy, perceived barriers, and perceived benefits were the key determinants of COVID-19-preventive behaviors in the subjects. It can be concluded that the HBM is a good tool to predict COVID-19-preventive behaviors in Iranian population.
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spelling pubmed-80571682021-06-02 Application of health belief model to predict COVID-19-preventive behaviors among a sample of Iranian adult population Mirzaei, Amin Kazembeigi, Farogh Kakaei, Hojatollah Jalilian, Mohsen Mazloomi, Sajad Nourmoradi, Heshmatollah J Educ Health Promot Original Article BACKGROUND: The novel coronavirus (COVID-19) has infected nearly 9.5 million people in 216 countries, areas, or territories in the world. The fight against the COVID-19 has become a very serious international challenge. The aim of this study was to determine the predictors of COVID-19-preventive behaviors using the health belief model (HBM). MATERIALS AND METHODS: This cross-sectional study was conducted with the participation of 558 samples from the adult population of Iran. The online convenience sampling was conducted in this research. The online 68-item questionnaire link was published all over Iran through social networks including Telegram and WhatsApp, which are common in Iran. The data were analyzed using SPSS software version 19. Descriptive statistics, bivariate Pearson's correlation test, and multiple linear regression were used to analyze the data. RESULTS: The mean age of the subjects was 33.3 ± 10.01 years. The participants were often female (61.3%), married (57.9%), and resident of the city (81.0%) with university educational level (78.8%). The results showed that the HBM structures predicted 29.3% of the preventive behaviors of COVID-19 in the subjects. The perceived benefits, perceived barriers, and self-efficacy significantly predicted the preventive behaviors, but the perceived susceptibility and perceived severity were not significant in the regression model. The internet and virtual social networks (49.8%), broadcast (33.5%), and healthcare providers (15.8%) were the most important sources of information related with COVID-19. In response to COVID-19-related internal cues to action, 36.6% did not pay attention and 34.7% tried to self-medicate. Only 28.5% of the subjects referred to the hospital, healthcare center, or physician. CONCLUSION: Self-efficacy, perceived barriers, and perceived benefits were the key determinants of COVID-19-preventive behaviors in the subjects. It can be concluded that the HBM is a good tool to predict COVID-19-preventive behaviors in Iranian population. Wolters Kluwer - Medknow 2021-02-27 /pmc/articles/PMC8057168/ /pubmed/34084816 http://dx.doi.org/10.4103/jehp.jehp_747_20 Text en Copyright: © 2021 Journal of Education and Health Promotion https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Mirzaei, Amin
Kazembeigi, Farogh
Kakaei, Hojatollah
Jalilian, Mohsen
Mazloomi, Sajad
Nourmoradi, Heshmatollah
Application of health belief model to predict COVID-19-preventive behaviors among a sample of Iranian adult population
title Application of health belief model to predict COVID-19-preventive behaviors among a sample of Iranian adult population
title_full Application of health belief model to predict COVID-19-preventive behaviors among a sample of Iranian adult population
title_fullStr Application of health belief model to predict COVID-19-preventive behaviors among a sample of Iranian adult population
title_full_unstemmed Application of health belief model to predict COVID-19-preventive behaviors among a sample of Iranian adult population
title_short Application of health belief model to predict COVID-19-preventive behaviors among a sample of Iranian adult population
title_sort application of health belief model to predict covid-19-preventive behaviors among a sample of iranian adult population
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8057168/
https://www.ncbi.nlm.nih.gov/pubmed/34084816
http://dx.doi.org/10.4103/jehp.jehp_747_20
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