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Content Analysis of Idiopathic Pulmonary Fibrosis-related Information on Twitter

BACKGROUND: Information regarding idiopathic pulmonary fibrosis (IPF) on the internet is often outdated, inaccurate, and potentially harmful. Twitter is a social media platform that allows users to post content in the form of “tweets”. OBJECTIVE: We sought to assess the prevalence of inaccurate info...

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Autores principales: Ong, Shaun, Koo, John, Johannson, Kerri A., Ryerson, Christopher J., Goobie, Gillian C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Thoracic Society 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9886131/
https://www.ncbi.nlm.nih.gov/pubmed/36726707
http://dx.doi.org/10.34197/ats-scholar.2022-0054OC
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author Ong, Shaun
Koo, John
Johannson, Kerri A.
Ryerson, Christopher J.
Goobie, Gillian C.
author_facet Ong, Shaun
Koo, John
Johannson, Kerri A.
Ryerson, Christopher J.
Goobie, Gillian C.
author_sort Ong, Shaun
collection PubMed
description BACKGROUND: Information regarding idiopathic pulmonary fibrosis (IPF) on the internet is often outdated, inaccurate, and potentially harmful. Twitter is a social media platform that allows users to post content in the form of “tweets”. OBJECTIVE: We sought to assess the prevalence of inaccurate information regarding IPF on Twitter. We hypothesized that foundations and medical organizations would be the least likely to post inaccurate information and that inaccurate tweets would have higher user engagement. METHODS: All tweets posted between 2011 and 2019 were gathered using “snscrape” on Python 3.8 while searching for the phrase “idiopathic pulmonary fibrosis”. Quantitative analysis was performed to describe trends in IPF-related tweet frequency over time. A subset of tweets made between 2018 and 2019 was screened for verifiable medical statements, which were then analyzed for accuracy compared with contemporary clinical practice guidelines, with descriptive statistics reported. Logistic regression was used to compare tweet accuracy and recommendation of nonindicated therapies across sources, with adjustment for tweet age and character count. Wilcoxon rank-sum tests were used to determine if user engagement (favorites, retweets, and replies) differed between accurate and inaccurate tweets. RESULTS: A total of 16,787 tweets were identified between 2011 and 2019. Between 2018 and 2019, 4,861 tweets were included, of which 1,612 (33%) contained verifiable medical statements. Tweets from sources other than foundations or medical organizations were more likely to contain inaccurate information and to recommend nonindicated therapies in both unadjusted and adjusted analyses. News and media sources had the highest odds of communicating potentially harmful information in both adjusted (odds ratio [OR], 12.00; 95% confidence interval [CI], 5.87–27.16) and unadjusted (OR, 11.62; 95% CI, 5.70–26.21) analyses when compared with foundations and medical organizations. Tweets containing inaccurate information had significantly lower numbers of favorites and retweets (P < 0.001 for both). CONCLUSION: Misinformation regarding IPF is present on Twitter and is more often presented by news and media sources. Medically inaccurate tweets displayed less user engagement than accurate tweets. This differs from findings on IPF-related information on YouTube and Facebook, which may reflect differences in both author and consumer qualities across social media platforms.
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spelling pubmed-98861312023-01-31 Content Analysis of Idiopathic Pulmonary Fibrosis-related Information on Twitter Ong, Shaun Koo, John Johannson, Kerri A. Ryerson, Christopher J. Goobie, Gillian C. ATS Sch Original Research BACKGROUND: Information regarding idiopathic pulmonary fibrosis (IPF) on the internet is often outdated, inaccurate, and potentially harmful. Twitter is a social media platform that allows users to post content in the form of “tweets”. OBJECTIVE: We sought to assess the prevalence of inaccurate information regarding IPF on Twitter. We hypothesized that foundations and medical organizations would be the least likely to post inaccurate information and that inaccurate tweets would have higher user engagement. METHODS: All tweets posted between 2011 and 2019 were gathered using “snscrape” on Python 3.8 while searching for the phrase “idiopathic pulmonary fibrosis”. Quantitative analysis was performed to describe trends in IPF-related tweet frequency over time. A subset of tweets made between 2018 and 2019 was screened for verifiable medical statements, which were then analyzed for accuracy compared with contemporary clinical practice guidelines, with descriptive statistics reported. Logistic regression was used to compare tweet accuracy and recommendation of nonindicated therapies across sources, with adjustment for tweet age and character count. Wilcoxon rank-sum tests were used to determine if user engagement (favorites, retweets, and replies) differed between accurate and inaccurate tweets. RESULTS: A total of 16,787 tweets were identified between 2011 and 2019. Between 2018 and 2019, 4,861 tweets were included, of which 1,612 (33%) contained verifiable medical statements. Tweets from sources other than foundations or medical organizations were more likely to contain inaccurate information and to recommend nonindicated therapies in both unadjusted and adjusted analyses. News and media sources had the highest odds of communicating potentially harmful information in both adjusted (odds ratio [OR], 12.00; 95% confidence interval [CI], 5.87–27.16) and unadjusted (OR, 11.62; 95% CI, 5.70–26.21) analyses when compared with foundations and medical organizations. Tweets containing inaccurate information had significantly lower numbers of favorites and retweets (P < 0.001 for both). CONCLUSION: Misinformation regarding IPF is present on Twitter and is more often presented by news and media sources. Medically inaccurate tweets displayed less user engagement than accurate tweets. This differs from findings on IPF-related information on YouTube and Facebook, which may reflect differences in both author and consumer qualities across social media platforms. American Thoracic Society 2022-11-15 /pmc/articles/PMC9886131/ /pubmed/36726707 http://dx.doi.org/10.34197/ats-scholar.2022-0054OC Text en Copyright © 2022 by the American Thoracic Society https://creativecommons.org/licenses/by-nc-nd/4.0/This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . For commercial usage and reprints, please e-mail Diane Gern.
spellingShingle Original Research
Ong, Shaun
Koo, John
Johannson, Kerri A.
Ryerson, Christopher J.
Goobie, Gillian C.
Content Analysis of Idiopathic Pulmonary Fibrosis-related Information on Twitter
title Content Analysis of Idiopathic Pulmonary Fibrosis-related Information on Twitter
title_full Content Analysis of Idiopathic Pulmonary Fibrosis-related Information on Twitter
title_fullStr Content Analysis of Idiopathic Pulmonary Fibrosis-related Information on Twitter
title_full_unstemmed Content Analysis of Idiopathic Pulmonary Fibrosis-related Information on Twitter
title_short Content Analysis of Idiopathic Pulmonary Fibrosis-related Information on Twitter
title_sort content analysis of idiopathic pulmonary fibrosis-related information on twitter
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9886131/
https://www.ncbi.nlm.nih.gov/pubmed/36726707
http://dx.doi.org/10.34197/ats-scholar.2022-0054OC
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