Discussions and Misinformation About Electronic Nicotine Delivery Systems and COVID-19: Qualitative Analysis of Twitter Content

Abstract

Background Misinformation 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. Objective Twitter 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. Methods Approximately 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. Results A 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. Conclusions Discussions 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.

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

“…Building on previous research both identifying and quantifying the extent of a specific piece of misinformation that nicotine can prevent COVID-19, we showed the disproportionately broad reach of this claim across the most retweeted content during this period [16,37,48]. Even in May 2020, when the original study by Farsalinos et al [10] was published, the preponderance of scientific evidence, including multiple meta-analyses, still opposed the notion that nicotine, and especially smoking, would protect people from COVID-19.…”

“…It is important to note that our findings do not contradict previous work examining the prevalence of misinformation on the protective role of nicotine but rather add context that helps to characterize the process through which misinformation spreads on Twitter. Kavaluru et al [16] identified that the protective role of nicotine constitutes about 1% of the overall content, while Sidani et al [37] identified a variety of different misinformation claims that arose on Twitter about vaping products. Both studies provide an overview of the overall "firehose" of information.…”

“…Although there is evidence of a provaping bias on Twitter, neither the extent of this bias nor the influence on the volume of pro-versus antivaping content is clear. A recent examination of vaping-related tweets between March and June 2020 found that misinformation about the relationship between COVID-19 and vaping informed chatter that was both pro-as well as antivaping [37]. In a separate study, the same researchers showed that misinformation was endemic to the Twitter discourse about vaping even prior to COVID-19 [36].…”

Public Figure Vaccination Rhetoric and Vaccine Hesitancy: Retrospective Twitter Analysis

“…First, we acknowledge that attitudes of Twitter users are unlikely to be representative of the general population or attitudes specifically toward celebrities or public personalities. Second, we sampled based on anti-vaccination keywords and for a specific period of time during the COVID-19 pandemic; this method is a common approach in infodemiology and misinformation studies [ 13 , 31 , 32 ], but we could have nevertheless missed messages relevant to the study aims that did not include these hashtags or occurred later during the pandemic. Hence, our choice of keywords or hashtags used for this study is not generalizable to all anti-vax posts occurring on Twitter.…”