Cargando…
Factors influencing COVID-19 knowledge-gap: a cross-sectional study in China
BACKGROUND: In the face of a sudden outbreak of COVID-19, it is essential to promote health communication, especially to reduce communication inequality. The paper targeted China to investigate whether social structural factors (education level and urban-rural differences) lead to the knowledge gap...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8501927/ https://www.ncbi.nlm.nih.gov/pubmed/34627200 http://dx.doi.org/10.1186/s12889-021-11856-9 |
_version_ | 1784580774607978496 |
---|---|
author | Wang, Han Li, Lina Wu, Jing Gao, Hao |
author_facet | Wang, Han Li, Lina Wu, Jing Gao, Hao |
author_sort | Wang, Han |
collection | PubMed |
description | BACKGROUND: In the face of a sudden outbreak of COVID-19, it is essential to promote health communication, especially to reduce communication inequality. The paper targeted China to investigate whether social structural factors (education level and urban-rural differences) lead to the knowledge gap of COVID-19. Also, this paper examined whether media use, interpersonal communication, public communication, and perceived salience of information can influence the knowledge gap of COVID-19. Furthermore, this paper explored the strategies to promote communication equality. METHODS: An online survey on COVID-19 knowledge and its influencing factors was conducted in February 2020, with a valid sample of 981 participants. The dependent variable was the total score of knowledge related to COVID-19. In addition to demographic variables such as education level and residence, the main explanatory variables include four independent variables: the use of different media (print media, radio, television, Internet), interpersonal communication, public communication, and perceived salience of information. This paper utilized descriptive statistics, correlation analysis, and hierarchical multiple regression analysis for data processing. RESULTS: Descriptive statistics indicated that the Internet was the most frequent source of information for participants to obtain COVID-19 knowledge (M = 6.28, SD = 1.022). Bi-variate analysis and regression analysis presented that education level, Internet media use, and perceived salience of information predicted the difference in knowledge level. Hierarchical multiple regression showed that Internet media use significantly predicted differences in the level of knowledge related to COVID-19 among groups with different education levels. CONCLUSIONS: This study found a COVID-19 knowledge gap among the Chinese public, especially the digital knowledge gap. Education level, perceived salience of information, and internet media use can significantly predict the difference in COVID-19 knowledge level. In contrast, the use of traditional media such as newspaper, radio, and television, public communication, and interpersonal communication did not improve knowledge level. Internet media use and education level have an interactive effect on the formation of a COVID-19 knowledge gap. That is, online media use will expand the COVID-19 knowledge gap between groups with different education levels. |
format | Online Article Text |
id | pubmed-8501927 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-85019272021-10-12 Factors influencing COVID-19 knowledge-gap: a cross-sectional study in China Wang, Han Li, Lina Wu, Jing Gao, Hao BMC Public Health Research Article BACKGROUND: In the face of a sudden outbreak of COVID-19, it is essential to promote health communication, especially to reduce communication inequality. The paper targeted China to investigate whether social structural factors (education level and urban-rural differences) lead to the knowledge gap of COVID-19. Also, this paper examined whether media use, interpersonal communication, public communication, and perceived salience of information can influence the knowledge gap of COVID-19. Furthermore, this paper explored the strategies to promote communication equality. METHODS: An online survey on COVID-19 knowledge and its influencing factors was conducted in February 2020, with a valid sample of 981 participants. The dependent variable was the total score of knowledge related to COVID-19. In addition to demographic variables such as education level and residence, the main explanatory variables include four independent variables: the use of different media (print media, radio, television, Internet), interpersonal communication, public communication, and perceived salience of information. This paper utilized descriptive statistics, correlation analysis, and hierarchical multiple regression analysis for data processing. RESULTS: Descriptive statistics indicated that the Internet was the most frequent source of information for participants to obtain COVID-19 knowledge (M = 6.28, SD = 1.022). Bi-variate analysis and regression analysis presented that education level, Internet media use, and perceived salience of information predicted the difference in knowledge level. Hierarchical multiple regression showed that Internet media use significantly predicted differences in the level of knowledge related to COVID-19 among groups with different education levels. CONCLUSIONS: This study found a COVID-19 knowledge gap among the Chinese public, especially the digital knowledge gap. Education level, perceived salience of information, and internet media use can significantly predict the difference in COVID-19 knowledge level. In contrast, the use of traditional media such as newspaper, radio, and television, public communication, and interpersonal communication did not improve knowledge level. Internet media use and education level have an interactive effect on the formation of a COVID-19 knowledge gap. That is, online media use will expand the COVID-19 knowledge gap between groups with different education levels. BioMed Central 2021-10-09 /pmc/articles/PMC8501927/ /pubmed/34627200 http://dx.doi.org/10.1186/s12889-021-11856-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Wang, Han Li, Lina Wu, Jing Gao, Hao Factors influencing COVID-19 knowledge-gap: a cross-sectional study in China |
title | Factors influencing COVID-19 knowledge-gap: a cross-sectional study in China |
title_full | Factors influencing COVID-19 knowledge-gap: a cross-sectional study in China |
title_fullStr | Factors influencing COVID-19 knowledge-gap: a cross-sectional study in China |
title_full_unstemmed | Factors influencing COVID-19 knowledge-gap: a cross-sectional study in China |
title_short | Factors influencing COVID-19 knowledge-gap: a cross-sectional study in China |
title_sort | factors influencing covid-19 knowledge-gap: a cross-sectional study in china |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8501927/ https://www.ncbi.nlm.nih.gov/pubmed/34627200 http://dx.doi.org/10.1186/s12889-021-11856-9 |
work_keys_str_mv | AT wanghan factorsinfluencingcovid19knowledgegapacrosssectionalstudyinchina AT lilina factorsinfluencingcovid19knowledgegapacrosssectionalstudyinchina AT wujing factorsinfluencingcovid19knowledgegapacrosssectionalstudyinchina AT gaohao factorsinfluencingcovid19knowledgegapacrosssectionalstudyinchina |