ArticleJMIR formative research2022
Discussions and Misinformation About Electronic Nicotine Delivery Systems and COVID-19: Qualitative Analysis of Twitter Content.
Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- Building an analytical framework for tobacco-related information on social media: an exploratory analysis with generative AI assistance.BMC public health · 2025Article
- Response to the Netflix Docuseries "Big Vape: The Rise and Fall of JUUL": Mixed Methods Analysis of YouTube Comments Using Qualitative Coding and Topic Modeling.JMIR formative research · 2025Article
- Social Network Analysis of e-Cigarette-Related Social Media Influencers on Twitter/X: Observational Study.JMIR formative research · 2024Article
- Knowledge, Attitudes, and Practices Among Community Populations Toward Long COVID in China.International journal of general medicine · 2024Article
- Content Analysis of YouTube Videos Related to E-Cigarettes and COVID-19.Substance use & misuse · 2024Article
- Viewer Reactions to EVALI Storylines on Popular Medical Dramas: A Thematic Analysis of Twitter Messages.Journal of health communication · 2023Article
- Public Figure Vaccination Rhetoric and Vaccine Hesitancy: Retrospective Twitter Analysis.JMIR infodemiology · 2023Article
- The Influence of Provaping "Gatewatchers" on the Dissemination of COVID-19 Misinformation on Twitter: Analysis of Twitter Discourse Regarding Nicotine and the COVID-19 Pandemic.Journal of medical Internet research · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundMisinformation and conspiracy theories related to COVID-19 and electronic nicotine delivery systems (ENDS) are increasing. Some of this may stem from early reports suggesting a lower risk of severe COVID-19 in nicotine users. Additionally, a common conspiracy is that the e-cigarette or vaping product use-associated lung injury (EVALI) outbreak of 2019 was actually an early presentation of COVID-19. This may have important public health ramifications for both COVID-19 control and ENDS use.
objectiveTwitter is an ideal tool for analyzing real-time public discussions related to both ENDS and COVID-19. This study seeks to collect and classify Twitter messages ("tweets") related to ENDS and COVID-19 to inform public health messaging.
methodsApproximately 2.1 million tweets matching ENDS-related keywords were collected from March 1, 2020, through June 30, 2020, and were then filtered for COVID-19-related keywords, resulting in 67,321 original tweets. A 5% (n=3366) subsample was obtained for human coding using a systematically developed codebook. Tweets were coded for relevance to the topic and four overarching categories.
resultsA total of 1930 (57.3%) tweets were coded as relevant to the research topic. Half (n=1008, 52.2%) of these discussed a perceived association between ENDS use and COVID-19 susceptibility or severity, with 42.4% (n=818) suggesting that ENDS use is associated with worse COVID-19 symptoms. One-quarter (n=479, 24.8%) of tweets discussed the perceived similarity/dissimilarity of COVID-19 and EVALI, and 13.8% (n=266) discussed ENDS use behavior. Misinformation and conspiracy theories were present throughout all coding categories.
conclusionsDiscussions about ENDS use and COVID-19 on Twitter frequently highlight concerns about the susceptibility and severity of COVID-19 for ENDS users; however, many contain misinformation and conspiracy theories. Public health messaging should capitalize on these concerns and amplify accurate Twitter messaging.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.