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Quality of Novel Coronavirus Related Health Information over the Internet: An Evaluation Study

BACKGROUND: The novel coronavirus disease (COVID-19) has spread globally from its epicenter in Hubei, China, and was declared a pandemic by the World Health Organization (WHO) on March 11, 2020. The most popular search engine worldwide is Google, and since March 2020, COVID-19 has been a global tren...

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Autores principales: Joshi, Ashish, Kajal, Fnu, Bhuyan, Soumitra S., Sharma, Priya, Bhatt, Ashruti, Kumar, Kanishk, Kaur, Mahima, Arora, Arushi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7411495/
https://www.ncbi.nlm.nih.gov/pubmed/32802003
http://dx.doi.org/10.1155/2020/1562028
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author Joshi, Ashish
Kajal, Fnu
Bhuyan, Soumitra S.
Sharma, Priya
Bhatt, Ashruti
Kumar, Kanishk
Kaur, Mahima
Arora, Arushi
author_facet Joshi, Ashish
Kajal, Fnu
Bhuyan, Soumitra S.
Sharma, Priya
Bhatt, Ashruti
Kumar, Kanishk
Kaur, Mahima
Arora, Arushi
author_sort Joshi, Ashish
collection PubMed
description BACKGROUND: The novel coronavirus disease (COVID-19) has spread globally from its epicenter in Hubei, China, and was declared a pandemic by the World Health Organization (WHO) on March 11, 2020. The most popular search engine worldwide is Google, and since March 2020, COVID-19 has been a global trending search term. Misinformation related to COVID-19 from these searches is a problem, and hence, it is of high importance to assess the quality of health information over the internet related to COVID-19. The objective of our study is to examine the quality of COVID-19 related health information over the internet using the DISCERN tool. METHODS: The keywords included in assessment of COVID-19 related information using Google's search engine were “Coronavirus,” “Coronavirus causes,” “Coronavirus diagnosis,” “Coronavirus prevention,” and “Coronavirus management”. The first 20 websites from each search term were gathered to generate a list of 100 URLs. Duplicate sites were excluded from this search, allowing analysis of unique sites only. Additional exclusion criteria included scientific journals, nonoperational links, nonfunctional websites (where the page was not loading, was not found, or was inactive), and websites in languages other than English. This resulted in a unique list of 48 websites. Four independent raters evaluated the websites using a 16-item DISCERN tool to assess the quality of novel coronavirus related information available on the internet. The interrater reliability agreement was calculated using the intracluster correlation coefficient. RESULTS: Results showed variation in how the raters assigned scores to different website categories. The .com websites received the lowest scores. Results showed that .edu and .org website category sites were excellent in communicating coronavirus related health information; however, they received lower scores for treatment effect and treatment choices. CONCLUSION: This study highlights the gaps in the quality of information that is available on the websites related to COVID-19 and study emphasizes the need for verified websites that provide evidence-based health information related to the novel coronavirus pandemic.
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spelling pubmed-74114952020-08-13 Quality of Novel Coronavirus Related Health Information over the Internet: An Evaluation Study Joshi, Ashish Kajal, Fnu Bhuyan, Soumitra S. Sharma, Priya Bhatt, Ashruti Kumar, Kanishk Kaur, Mahima Arora, Arushi ScientificWorldJournal Research Article BACKGROUND: The novel coronavirus disease (COVID-19) has spread globally from its epicenter in Hubei, China, and was declared a pandemic by the World Health Organization (WHO) on March 11, 2020. The most popular search engine worldwide is Google, and since March 2020, COVID-19 has been a global trending search term. Misinformation related to COVID-19 from these searches is a problem, and hence, it is of high importance to assess the quality of health information over the internet related to COVID-19. The objective of our study is to examine the quality of COVID-19 related health information over the internet using the DISCERN tool. METHODS: The keywords included in assessment of COVID-19 related information using Google's search engine were “Coronavirus,” “Coronavirus causes,” “Coronavirus diagnosis,” “Coronavirus prevention,” and “Coronavirus management”. The first 20 websites from each search term were gathered to generate a list of 100 URLs. Duplicate sites were excluded from this search, allowing analysis of unique sites only. Additional exclusion criteria included scientific journals, nonoperational links, nonfunctional websites (where the page was not loading, was not found, or was inactive), and websites in languages other than English. This resulted in a unique list of 48 websites. Four independent raters evaluated the websites using a 16-item DISCERN tool to assess the quality of novel coronavirus related information available on the internet. The interrater reliability agreement was calculated using the intracluster correlation coefficient. RESULTS: Results showed variation in how the raters assigned scores to different website categories. The .com websites received the lowest scores. Results showed that .edu and .org website category sites were excellent in communicating coronavirus related health information; however, they received lower scores for treatment effect and treatment choices. CONCLUSION: This study highlights the gaps in the quality of information that is available on the websites related to COVID-19 and study emphasizes the need for verified websites that provide evidence-based health information related to the novel coronavirus pandemic. Hindawi 2020-08-06 /pmc/articles/PMC7411495/ /pubmed/32802003 http://dx.doi.org/10.1155/2020/1562028 Text en Copyright © 2020 Ashish Joshi et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Joshi, Ashish
Kajal, Fnu
Bhuyan, Soumitra S.
Sharma, Priya
Bhatt, Ashruti
Kumar, Kanishk
Kaur, Mahima
Arora, Arushi
Quality of Novel Coronavirus Related Health Information over the Internet: An Evaluation Study
title Quality of Novel Coronavirus Related Health Information over the Internet: An Evaluation Study
title_full Quality of Novel Coronavirus Related Health Information over the Internet: An Evaluation Study
title_fullStr Quality of Novel Coronavirus Related Health Information over the Internet: An Evaluation Study
title_full_unstemmed Quality of Novel Coronavirus Related Health Information over the Internet: An Evaluation Study
title_short Quality of Novel Coronavirus Related Health Information over the Internet: An Evaluation Study
title_sort quality of novel coronavirus related health information over the internet: an evaluation study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7411495/
https://www.ncbi.nlm.nih.gov/pubmed/32802003
http://dx.doi.org/10.1155/2020/1562028
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