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Potential Impact of a Paper About COVID-19 and Smoking on Twitter Users’ Attitudes Toward Smoking: Observational Study
BACKGROUND: A cross-sectional study (Miyara et al, 2020) conducted by French researchers showed that the rate of current daily smoking was significantly lower in patients with COVID-19 than in the French general population, implying a potentially protective effect of smoking. OBJECTIVE: We aimed to...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8208470/ https://www.ncbi.nlm.nih.gov/pubmed/33939624 http://dx.doi.org/10.2196/25010 |
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author | Tao, Chunliang Diaz, Destiny Xie, Zidian Chen, Long Li, Dongmei O’Connor, Richard |
author_facet | Tao, Chunliang Diaz, Destiny Xie, Zidian Chen, Long Li, Dongmei O’Connor, Richard |
author_sort | Tao, Chunliang |
collection | PubMed |
description | BACKGROUND: A cross-sectional study (Miyara et al, 2020) conducted by French researchers showed that the rate of current daily smoking was significantly lower in patients with COVID-19 than in the French general population, implying a potentially protective effect of smoking. OBJECTIVE: We aimed to examine the dissemination of the Miyara et al study among Twitter users and whether a shift in their attitudes toward smoking occurred after its publication as preprint on April 21, 2020. METHODS: Twitter posts were crawled between April 14 and May 4, 2020, by the Tweepy stream application programming interface, using a COVID-19–related keyword query. After filtering, the final 1929 tweets were classified into three groups: (1) tweets that were not related to the Miyara et al study before it was published, (2) tweets that were not related to Miyara et al study after it was published, and (3) tweets that were related to Miyara et al study after it was published. The attitudes toward smoking, as expressed in the tweets, were compared among the above three groups using multinomial logistic regression models in the statistical analysis software R (The R Foundation). RESULTS: Temporal analysis showed a peak in the number of tweets discussing the results from the Miyara et al study right after its publication. Multinomial logistic regression models on sentiment scores showed that the proportion of negative attitudes toward smoking in tweets related to the Miyara et al study after it was published (17.07%) was significantly lower than the proportion in tweets that were not related to the Miyara et al study, either before (44/126, 34.9%; P<.001) or after the Miyara et al study was published (68/198, 34.3%; P<.001). CONCLUSIONS: The public’s attitude toward smoking shifted in a positive direction after the Miyara et al study found a lower incidence of COVID-19 cases among daily smokers. |
format | Online Article Text |
id | pubmed-8208470 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-82084702021-06-30 Potential Impact of a Paper About COVID-19 and Smoking on Twitter Users’ Attitudes Toward Smoking: Observational Study Tao, Chunliang Diaz, Destiny Xie, Zidian Chen, Long Li, Dongmei O’Connor, Richard JMIR Form Res Original Paper BACKGROUND: A cross-sectional study (Miyara et al, 2020) conducted by French researchers showed that the rate of current daily smoking was significantly lower in patients with COVID-19 than in the French general population, implying a potentially protective effect of smoking. OBJECTIVE: We aimed to examine the dissemination of the Miyara et al study among Twitter users and whether a shift in their attitudes toward smoking occurred after its publication as preprint on April 21, 2020. METHODS: Twitter posts were crawled between April 14 and May 4, 2020, by the Tweepy stream application programming interface, using a COVID-19–related keyword query. After filtering, the final 1929 tweets were classified into three groups: (1) tweets that were not related to the Miyara et al study before it was published, (2) tweets that were not related to Miyara et al study after it was published, and (3) tweets that were related to Miyara et al study after it was published. The attitudes toward smoking, as expressed in the tweets, were compared among the above three groups using multinomial logistic regression models in the statistical analysis software R (The R Foundation). RESULTS: Temporal analysis showed a peak in the number of tweets discussing the results from the Miyara et al study right after its publication. Multinomial logistic regression models on sentiment scores showed that the proportion of negative attitudes toward smoking in tweets related to the Miyara et al study after it was published (17.07%) was significantly lower than the proportion in tweets that were not related to the Miyara et al study, either before (44/126, 34.9%; P<.001) or after the Miyara et al study was published (68/198, 34.3%; P<.001). CONCLUSIONS: The public’s attitude toward smoking shifted in a positive direction after the Miyara et al study found a lower incidence of COVID-19 cases among daily smokers. JMIR Publications 2021-06-15 /pmc/articles/PMC8208470/ /pubmed/33939624 http://dx.doi.org/10.2196/25010 Text en ©Chunliang Tao, Destiny Diaz, Zidian Xie, Long Chen, Dongmei Li, Richard O’Connor. Originally published in JMIR Formative Research (https://formative.jmir.org), 15.06.2021. 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 JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Tao, Chunliang Diaz, Destiny Xie, Zidian Chen, Long Li, Dongmei O’Connor, Richard Potential Impact of a Paper About COVID-19 and Smoking on Twitter Users’ Attitudes Toward Smoking: Observational Study |
title | Potential Impact of a Paper About COVID-19 and Smoking on Twitter Users’ Attitudes Toward Smoking: Observational Study |
title_full | Potential Impact of a Paper About COVID-19 and Smoking on Twitter Users’ Attitudes Toward Smoking: Observational Study |
title_fullStr | Potential Impact of a Paper About COVID-19 and Smoking on Twitter Users’ Attitudes Toward Smoking: Observational Study |
title_full_unstemmed | Potential Impact of a Paper About COVID-19 and Smoking on Twitter Users’ Attitudes Toward Smoking: Observational Study |
title_short | Potential Impact of a Paper About COVID-19 and Smoking on Twitter Users’ Attitudes Toward Smoking: Observational Study |
title_sort | potential impact of a paper about covid-19 and smoking on twitter users’ attitudes toward smoking: observational study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8208470/ https://www.ncbi.nlm.nih.gov/pubmed/33939624 http://dx.doi.org/10.2196/25010 |
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