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A Social Media Study on the Associations of Flavored Electronic Cigarettes With Health Symptoms: Observational Study
BACKGROUND: In recent years, flavored electronic cigarettes (e-cigarettes) have become popular among teenagers and young adults. Discussions about e-cigarettes and e-cigarette use (vaping) experiences are prevalent online, making social media an ideal resource for understanding the health risks asso...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338924/ https://www.ncbi.nlm.nih.gov/pubmed/32568093 http://dx.doi.org/10.2196/17496 |
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author | Chen, Long Lu, Xinyi Yuan, Jianbo Luo, Joyce Luo, Jiebo Xie, Zidian Li, Dongmei |
author_facet | Chen, Long Lu, Xinyi Yuan, Jianbo Luo, Joyce Luo, Jiebo Xie, Zidian Li, Dongmei |
author_sort | Chen, Long |
collection | PubMed |
description | BACKGROUND: In recent years, flavored electronic cigarettes (e-cigarettes) have become popular among teenagers and young adults. Discussions about e-cigarettes and e-cigarette use (vaping) experiences are prevalent online, making social media an ideal resource for understanding the health risks associated with e-cigarette flavors from the users’ perspective. OBJECTIVE: This study aimed to investigate the potential associations between electronic cigarette liquid (e-liquid) flavors and the reporting of health symptoms using social media data. METHODS: A dataset consisting of 2.8 million e-cigarette–related posts was collected using keyword filtering from Reddit, a social media platform, from January 2013 to April 2019. Temporal analysis for nine major health symptom categories was used to understand the trend of public concerns related to e-cigarettes. Sentiment analysis was conducted to obtain the proportions of positive and negative sentiment scores for all reported health symptom categories. Topic modeling was applied to reveal the topics related to e-cigarettes and health symptoms. Furthermore, generalized estimating equation (GEE) models were used to quantitatively measure potential associations between e-liquid flavors and the reporting of health symptoms. RESULTS: Temporal analysis showed that the Respiratory category was consistently the most discussed health symptom category among all categories related to e-cigarettes on Reddit, followed by the Throat category. Sentiment analysis showed higher proportions of positive sentiment scores for all reported health symptom categories, except for the Cancer category. Topic modeling conducted on all health-related posts showed that 17 of the top 100 topics were flavor related. GEE models showed different associations between the reporting of health symptoms and e-liquid flavor categories, for example, lower association of the Beverage flavors with Respiratory compared with other flavors and higher association of the Fruit flavors with Cardiovascular than other flavors. CONCLUSIONS: This study identified different potential associations between e-liquid flavors and the reporting of health symptoms using social media data. The results of this study provide valuable information for further investigation of the health effects associated with different e-liquid flavors. |
format | Online Article Text |
id | pubmed-7338924 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-73389242020-07-14 A Social Media Study on the Associations of Flavored Electronic Cigarettes With Health Symptoms: Observational Study Chen, Long Lu, Xinyi Yuan, Jianbo Luo, Joyce Luo, Jiebo Xie, Zidian Li, Dongmei J Med Internet Res Original Paper BACKGROUND: In recent years, flavored electronic cigarettes (e-cigarettes) have become popular among teenagers and young adults. Discussions about e-cigarettes and e-cigarette use (vaping) experiences are prevalent online, making social media an ideal resource for understanding the health risks associated with e-cigarette flavors from the users’ perspective. OBJECTIVE: This study aimed to investigate the potential associations between electronic cigarette liquid (e-liquid) flavors and the reporting of health symptoms using social media data. METHODS: A dataset consisting of 2.8 million e-cigarette–related posts was collected using keyword filtering from Reddit, a social media platform, from January 2013 to April 2019. Temporal analysis for nine major health symptom categories was used to understand the trend of public concerns related to e-cigarettes. Sentiment analysis was conducted to obtain the proportions of positive and negative sentiment scores for all reported health symptom categories. Topic modeling was applied to reveal the topics related to e-cigarettes and health symptoms. Furthermore, generalized estimating equation (GEE) models were used to quantitatively measure potential associations between e-liquid flavors and the reporting of health symptoms. RESULTS: Temporal analysis showed that the Respiratory category was consistently the most discussed health symptom category among all categories related to e-cigarettes on Reddit, followed by the Throat category. Sentiment analysis showed higher proportions of positive sentiment scores for all reported health symptom categories, except for the Cancer category. Topic modeling conducted on all health-related posts showed that 17 of the top 100 topics were flavor related. GEE models showed different associations between the reporting of health symptoms and e-liquid flavor categories, for example, lower association of the Beverage flavors with Respiratory compared with other flavors and higher association of the Fruit flavors with Cardiovascular than other flavors. CONCLUSIONS: This study identified different potential associations between e-liquid flavors and the reporting of health symptoms using social media data. The results of this study provide valuable information for further investigation of the health effects associated with different e-liquid flavors. JMIR Publications 2020-06-22 /pmc/articles/PMC7338924/ /pubmed/32568093 http://dx.doi.org/10.2196/17496 Text en ©Long Chen, Xinyi Lu, Jianbo Yuan, Joyce Luo, Jiebo Luo, Zidian Xie, Dongmei Li. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.06.2020. 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 Chen, Long Lu, Xinyi Yuan, Jianbo Luo, Joyce Luo, Jiebo Xie, Zidian Li, Dongmei A Social Media Study on the Associations of Flavored Electronic Cigarettes With Health Symptoms: Observational Study |
title | A Social Media Study on the Associations of Flavored Electronic Cigarettes With Health Symptoms: Observational Study |
title_full | A Social Media Study on the Associations of Flavored Electronic Cigarettes With Health Symptoms: Observational Study |
title_fullStr | A Social Media Study on the Associations of Flavored Electronic Cigarettes With Health Symptoms: Observational Study |
title_full_unstemmed | A Social Media Study on the Associations of Flavored Electronic Cigarettes With Health Symptoms: Observational Study |
title_short | A Social Media Study on the Associations of Flavored Electronic Cigarettes With Health Symptoms: Observational Study |
title_sort | social media study on the associations of flavored electronic cigarettes with health symptoms: observational study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338924/ https://www.ncbi.nlm.nih.gov/pubmed/32568093 http://dx.doi.org/10.2196/17496 |
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