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Socioeconomic Disparities in eHealth Literacy and Preventive Behaviors During the COVID-19 Pandemic in Hong Kong: Cross-sectional Study

BACKGROUND: eHealth literacy can potentially facilitate web-based information seeking and taking informed measures. OBJECTIVE: This study aimed to evaluate socioeconomic disparities in eHealth literacy and seeking of web-based information on COVID-19, and their associations with COVID-19 preventive...

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Autores principales: Guo, Ziqiu, Zhao, Sheng Zhi, Guo, Ningyuan, Wu, Yongda, Weng, Xue, Wong, Janet Yuen-Ha, Lam, Tai Hing, Wang, Man Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8048711/
https://www.ncbi.nlm.nih.gov/pubmed/33784240
http://dx.doi.org/10.2196/24577
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author Guo, Ziqiu
Zhao, Sheng Zhi
Guo, Ningyuan
Wu, Yongda
Weng, Xue
Wong, Janet Yuen-Ha
Lam, Tai Hing
Wang, Man Ping
author_facet Guo, Ziqiu
Zhao, Sheng Zhi
Guo, Ningyuan
Wu, Yongda
Weng, Xue
Wong, Janet Yuen-Ha
Lam, Tai Hing
Wang, Man Ping
author_sort Guo, Ziqiu
collection PubMed
description BACKGROUND: eHealth literacy can potentially facilitate web-based information seeking and taking informed measures. OBJECTIVE: This study aimed to evaluate socioeconomic disparities in eHealth literacy and seeking of web-based information on COVID-19, and their associations with COVID-19 preventive behaviors. METHODS: The COVID-19 Health Information Survey (CoVHIns), using telephonic (n=500) and web-based surveys (n=1001), was conducted among adults in Hong Kong in April 2020. The Chinese eHealth literacy scale (eHEALS; score range 8-40) was used to measure eHealth literacy. COVID-19 preventive behaviors included wearing surgical masks, wearing fabric masks, washing hands, social distancing, and adding water or bleach to the household drainage system. Adjusted beta coefficients and the slope indices of inequality for the eHEALS score by socioeconomic status, adjusted odds ratios (aORs) for seeking of web-based information on COVID-19 by socioeconomic status, and aORs for the high adherence to preventive behaviors by the eHEALS score and seeking of web-based information on COVID-19 were calculated. RESULTS: The mean eHEALS score was 26.10 (SD 7.70). Age was inversely associated with the eHEALS score, but education and personal income were positively associated with the eHEALS score and seeking of web-based information on COVID-19 (for all, P for trend<.05). Participants who sought web-based information on COVID-19 showed high adherence to the practice of wearing surgical masks (aOR 1.56, 95% CI 1.15-2.13), washing hands (aOR 1.33, 95% CI 1.05-1.71), social distancing (aOR 1.48, 95% CI 1.14-1.93), and adding water or bleach to the household drainage system (aOR 1.67, 95% CI 1.28-2.18). Those with the highest eHEALS score displayed high adherence to the practice of wearing surgical masks (aOR 3.84, 95% CI 1.63-9.05), washing hands (aOR 4.14, 95% CI 2.46-6.96), social distancing (aOR 2.25, 95% CI 1.39-3.65), and adding water or bleach to the household drainage system (aOR 1.94, 95% CI 1.19-3.16), compared to those with the lowest eHEALS score. CONCLUSIONS: Chinese adults with a higher socioeconomic status had higher eHealth literacy and sought more web-based information on COVID-19; both these factors were associated with a high adherence to the guidelines for preventive behaviors during the COVID-19 pandemic.
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spelling pubmed-80487112021-04-22 Socioeconomic Disparities in eHealth Literacy and Preventive Behaviors During the COVID-19 Pandemic in Hong Kong: Cross-sectional Study Guo, Ziqiu Zhao, Sheng Zhi Guo, Ningyuan Wu, Yongda Weng, Xue Wong, Janet Yuen-Ha Lam, Tai Hing Wang, Man Ping J Med Internet Res Original Paper BACKGROUND: eHealth literacy can potentially facilitate web-based information seeking and taking informed measures. OBJECTIVE: This study aimed to evaluate socioeconomic disparities in eHealth literacy and seeking of web-based information on COVID-19, and their associations with COVID-19 preventive behaviors. METHODS: The COVID-19 Health Information Survey (CoVHIns), using telephonic (n=500) and web-based surveys (n=1001), was conducted among adults in Hong Kong in April 2020. The Chinese eHealth literacy scale (eHEALS; score range 8-40) was used to measure eHealth literacy. COVID-19 preventive behaviors included wearing surgical masks, wearing fabric masks, washing hands, social distancing, and adding water or bleach to the household drainage system. Adjusted beta coefficients and the slope indices of inequality for the eHEALS score by socioeconomic status, adjusted odds ratios (aORs) for seeking of web-based information on COVID-19 by socioeconomic status, and aORs for the high adherence to preventive behaviors by the eHEALS score and seeking of web-based information on COVID-19 were calculated. RESULTS: The mean eHEALS score was 26.10 (SD 7.70). Age was inversely associated with the eHEALS score, but education and personal income were positively associated with the eHEALS score and seeking of web-based information on COVID-19 (for all, P for trend<.05). Participants who sought web-based information on COVID-19 showed high adherence to the practice of wearing surgical masks (aOR 1.56, 95% CI 1.15-2.13), washing hands (aOR 1.33, 95% CI 1.05-1.71), social distancing (aOR 1.48, 95% CI 1.14-1.93), and adding water or bleach to the household drainage system (aOR 1.67, 95% CI 1.28-2.18). Those with the highest eHEALS score displayed high adherence to the practice of wearing surgical masks (aOR 3.84, 95% CI 1.63-9.05), washing hands (aOR 4.14, 95% CI 2.46-6.96), social distancing (aOR 2.25, 95% CI 1.39-3.65), and adding water or bleach to the household drainage system (aOR 1.94, 95% CI 1.19-3.16), compared to those with the lowest eHEALS score. CONCLUSIONS: Chinese adults with a higher socioeconomic status had higher eHealth literacy and sought more web-based information on COVID-19; both these factors were associated with a high adherence to the guidelines for preventive behaviors during the COVID-19 pandemic. JMIR Publications 2021-04-14 /pmc/articles/PMC8048711/ /pubmed/33784240 http://dx.doi.org/10.2196/24577 Text en ©Ziqiu Guo, Sheng Zhi Zhao, Ningyuan Guo, Yongda Wu, Xue Weng, Janet Yuen-Ha Wong, Tai Hing Lam, Man Ping Wang. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 14.04.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Guo, Ziqiu
Zhao, Sheng Zhi
Guo, Ningyuan
Wu, Yongda
Weng, Xue
Wong, Janet Yuen-Ha
Lam, Tai Hing
Wang, Man Ping
Socioeconomic Disparities in eHealth Literacy and Preventive Behaviors During the COVID-19 Pandemic in Hong Kong: Cross-sectional Study
title Socioeconomic Disparities in eHealth Literacy and Preventive Behaviors During the COVID-19 Pandemic in Hong Kong: Cross-sectional Study
title_full Socioeconomic Disparities in eHealth Literacy and Preventive Behaviors During the COVID-19 Pandemic in Hong Kong: Cross-sectional Study
title_fullStr Socioeconomic Disparities in eHealth Literacy and Preventive Behaviors During the COVID-19 Pandemic in Hong Kong: Cross-sectional Study
title_full_unstemmed Socioeconomic Disparities in eHealth Literacy and Preventive Behaviors During the COVID-19 Pandemic in Hong Kong: Cross-sectional Study
title_short Socioeconomic Disparities in eHealth Literacy and Preventive Behaviors During the COVID-19 Pandemic in Hong Kong: Cross-sectional Study
title_sort socioeconomic disparities in ehealth literacy and preventive behaviors during the covid-19 pandemic in hong kong: cross-sectional study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8048711/
https://www.ncbi.nlm.nih.gov/pubmed/33784240
http://dx.doi.org/10.2196/24577
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