Vaporous Marketing: Uncovering Pervasive Electronic Cigarette Advertisements on Twitter

#Delta8: a retailer-driven increase in Delta-8 THC discussions on Twitter from 2020 to 2021

Background: Delta-8 tetrahydrocannabinol (THC) has experienced significant cultivation, use, and online marketing growth in recent years.Objectives: This study utilized natural language processing on Twitter data to examine trends in public discussions regarding this novel psychoactive substance.Methods: This study analyzed the frequency of #Delta8 tweets over time, most commonly used words, sentiment classification of words in tweets, and a qualitative analysis of a random sample of tweets containing the hashtag "Delta8" from January 1, 2020 to September 26, 2021.Results: A total of 41,828 tweets were collected, with 30,826 unique tweets (73.7%) and 11,002 quotes, retweets, or replies (26.3%). Tweet activity increased from 2020 to 2021, with daily original tweets rising from 8.55 to 149. This increase followed a high-engagement retailer promotion in June 2021. Commonly used terms included "cbd," "cannabis," "edibles," and "cbdoil." Sentiment classification revealed a predominance of "positive" (30.93%) and "trust" (14.26%) categorizations, with 8.42% classified as "negative." Qualitative analysis identified 20 codes, encompassing substance type, retailers, links, and other characteristics.Conclusion: Twitter discussions on Delta-8 THC exhibited a sustained increase in prevalence from 2020 to 2022, with online retailers playing a dominant role. The content also demonstrated significant overlap with cannabidiol and various cannabis products. Given the growing presence of retailer marketing and sales on social media, it is crucial for public health researchers to monitor and promote relevant Delta-8 health recommendations on these platforms to ensure a balanced conversation.

Youth-appealing features in popular e-cigarette brand advertising in the USA after heightened scrutiny in 2018

PURPOSE

Youth electronic cigarette (e-cigarette) use remains high in the USA, and advertising is a contributor. The purpose of this study was to identify themes and characteristics of popular e-cigarette companies' advertising after e-cigarette companies became more highly scrutinised in 2018.

METHODS

Using a systematic, quantitative content analysis, three trained coders coded e-cigarette advertisements from JUUL, Puff Bar, Vuse and Blu from 2019 and 2020. Based on previous work, they coded for: type of advertisement, flavours, promotions, product cues, descriptors, claims, imagery, youth-oriented themes and sensational appeals.

RESULTS

Of the 401 e-cigarette advertisements, the majority were emails (38.2%) and Instagram posts (30.9%). Over half (53.6%) showed flavours other than tobacco, with Puff Bar leading the brands (70.2%; p<0.001). The most frequently used product cues were showing the product (51.4%) or packaging (42.4%). The most common claim was being an alternative to smoking (14.2%). The most frequently used imagery was fruit (14.0%), employed most by Puff Bar (p<0.001). The only youth-oriented theme present was humour (4.2%). Positive sensations (eg, good taste, good smell or satisfying; 17.1%) was the most common form of appeal, with Puff Bar using it at the highest frequency (p<0.001).

CONCLUSION

Even with heightened scrutiny of e-cigarette brands, advertisements still included youth-appealing content such as flavours, fruit imagery and positive sensations. Puff Bar led in all these categories, and it rapidly gained market share after market leader JUUL limited the sales of its flavoured products. Research should continue to monitor the characteristics of e-cigarette advertisements and consider their impact on youth.

E-Cigarette-Related Health Beliefs Expressed on Twitter Within the U.S

Introduction

This mixed-methods study analyzed English-language U.S.-based Twitter posts related to E-cigarette use from February 2021.

Methods

Posts were manually identified as health-related or not and, if health-related, whether they were posted by an E-cigarette user. A random selection of 1,000 health-related tweets from 986 unique E-cigarette users were qualitatively content analyzed for theory of planned behavior constructs as well as nature and tone of each tweet message. Using quantitative semantic network analysis, relationships among the identified topics and sentiment-specific conversation patterns were explored.

Results

The most salient health-related conversation topics of E-cigarette users, health beliefs corresponding to each theory of planned behavior construct, and major motivational contexts of E-cigarette use were identified. Seven topics emerged in positive tweets: smoking cessation, social impact generation, controls over addiction, therapeutic effects on physical and mental health, social support, device attachment, and peer influence. Nine topics emerged in negative tweets: side effects on physical health, vaping addiction, lack of E-cigarette regulations, peer pressure, increased risk of COVID-19, side effects on mental health, no help in smoking cessation, social conflict, and polysubstance use. Most assertions for E-cigarette benefits were not substantiated. Jokes in tweets appeared to contribute to the view of vaping as an attractive, enjoyable, safe, and fun activity. Discussions about positive aspects of E-cigarette use were concentrated on a few related topics, whereas tweets discouraging E-cigarette use presented a diverse, less related set of topics.

Conclusions

The results provide insights into the drivers of E-cigarette use behaviors. E-cigarette user perspectives gathered from social media may inform research to guide future prevention and cessation interventions.

How Does Social Media Exposure and Engagement Influence College Students' Use of ENDS Products? A Cross-lagged Longitudinal Study

Electronic nicotine delivery systems (ENDS) products have been marketed heavily on social media throughout the past years, which exerts great influence on young adults' ENDS use. Despite scholars' pioneering efforts in investigating the influence of tobacco and nicotine products marketing on young adults' vaping behavior, scholarly attention has been paid primarily to passive exposure to rather than active engagement with the information on social media. In addition, the majority of existing research has been cross-sectional or focused on the unidirectional path from marketing information to behavior. To extend previous research in tobacco regulatory science on new media, we examined the bidirectional associations between self-reported exposure to and engagement with tobacco and nicotine products messaging on social media, and subsequent use of ENDS products one year later among a large, diverse sample of young adults. Results from cross-lagged panel analyses indicated that pro-tobacco/ENDS engagement and advertising exposure elevated risk whereas anti-tobacco/ENDS engagement decreased risk for the subsequent use of ENDS products one year later. On the other hand, the use of ENDS products positively predicted both pro- and anti-tobacco/ENDS engagement one year later. Findings provide empirical support for the reasoned action approach and the confirmation bias rooted in cognitive dissonance theory through rigorous longitudinal examination. Our findings not only point to the imperativeness of and offer guidance for regulating marketing information on social media, but also suggest social media as a promising platform to prevent young adults from initiating ENDS product use.

Machine learning applications in tobacco research: a scoping review

OBJECTIVE

Identify and review the body of tobacco research literature that self-identified as using machine learning (ML) in the analysis.

DATA SOURCES

MEDLINE, EMABSE, PubMed, CINAHL Plus, APA PsycINFO and IEEE Xplore databases were searched up to September 2020. Studies were restricted to peer-reviewed, English-language journal articles, dissertations and conference papers comprising an empirical analysis where ML was identified to be the method used to examine human experience of tobacco. Studies of genomics and diagnostic imaging were excluded.

STUDY SELECTION

Two reviewers independently screened the titles and abstracts. The reference list of articles was also searched. In an iterative process, eligible studies were classified into domains based on their objectives and types of data used in the analysis.

DATA EXTRACTION

Using data charting forms, two reviewers independently extracted data from all studies. A narrative synthesis method was used to describe findings from each domain such as study design, objective, ML classes/algorithms, knowledge users and the presence of a data sharing statement. Trends of publication were visually depicted.

DATA SYNTHESIS

74 studies were grouped into four domains: ML-powered technology to assist smoking cessation (n=22); content analysis of tobacco on social media (n=32); smoker status classification from narrative clinical texts (n=6) and tobacco-related outcome prediction using administrative, survey or clinical trial data (n=14). Implications of these studies and future directions for ML researchers in tobacco control were discussed.

CONCLUSIONS

ML represents a powerful tool that could advance the research and policy decision-making of tobacco control. Further opportunities should be explored.

Marketing claims on websites of brick-and-mortar vape shops in the Greater Los Angeles area

INTRODUCTION

Brick-and-mortar vape shops have increased in recent years, but there is limited research on the types of marketing claims consumers are exposed to on their websites - a dominant channel for marketing electronic nicotine delivery systems (ENDS). We investigated the websites of vape shop retailers in the Greater Los Angeles Area to describe their ENDS marketing claims.

METHODS

Data collection occurred between 25 March and 20 June 2020. Of the 104 brick-and-mortar vape shops identified, 37 were found to have active websites. Rules were established to analyze website content. ENDS Marketing Claims were coded as the presence or absence of: 1) a direct claim of ENDS as a quitting aid; 2) a disclaimer that ENDS are not approved as smoking cessation devices (i.e. ENDS products are not FDA-approved for smoking cessation); 3) a direct claim of ENDS as healthier/safer than combustible cigarettes; and 4) direct claims regarding social benefits, including that ENDS are less expensive, can be used in more places, are cleaner or less messy/smelly, and are more socially accepted than combustible cigarettes.

RESULTS

Smoking cessation-related benefits were claimed most frequently (43%), followed by health-related claims (30%), and disclaimers that ENDS are not approved as smoking cessation devices (24%). More than half (56.4%) of websites had an age restriction, requiring the user to click on a box to state that they were aged ≥21 years to view the site. None required proof or outside verification of age.

CONCLUSIONS

Brick-and-mortar vape shops in the Greater Los Angeles Area are marketing ENDS on their websites as a healthier alternative to smoking cigarettes. Although half of the websites had an age gate popup that consumers see when they enter the website, action is needed to better enforce age restriction on access to vape shop websites. Utility for smoking cessation was claimed most frequently, followed by the claims of healthier alternatives to smoking cigarettes, and disclaimers that ENDS are not approved as smoking cessation devices. We discuss implications for tobacco regulatory policy.

Detecting Sentiment toward Emerging Infectious Diseases on Social Media: A Validity Evaluation of Dictionary-Based Sentiment Analysis

Despite the popularity and efficiency of dictionary-based sentiment analysis (DSA) for public health research, limited empirical evidence has been produced about the validity of DSA and potential harms to the validity of DSA. A random sample of a second-hand Ebola tweet dataset was used to evaluate the validity of DSA compared to the manual coding approach and examine the influences of textual features on the validity of DSA. The results revealed substantial inconsistency between DSA and the manual coding approach. The presence of certain textual features such as negation can partially account for the inconsistency between DSA and manual coding. The findings imply that scholars should be careful and critical about findings in disease-related public health research that use DSA. Certain textual features should be more carefully addressed in DSA.

Social Media Discussions on the FDA's Modified Risk Tobacco Product Authorization of IQOS

Background: The U.S. Food and Drug Administration (FDA) authorized the marketing of the IQOS tobacco heating system as a modified risk tobacco product (MRTP) in July 2020, permitting its 'reduced exposure' marketing. This decision is accompanied by much controversy among the global health community. We provide a preliminary analysis of Twitter conversations regarding the MRTP authorization of IQOS by identifying the authors, valence towards the policy decision, source of cited link, and focused topic. Methods: We analyzed 548 tweets mentioning MRTP posted between July 2016 (when PMI submitted the proposal) and October 2020. Results: We found a higher proportion of pro-MRTP valence (25.4%) than anti-MRTP (16.2%). Nearly half of the tweets (47.2%) expressing personal opinions presented pro-MRTP valence (vs. anti-MRTP = 23.9%). The FDA website was more frequently cited in pro-MRTP tweets (30.8% vs. anti = 4.8%), while tobacco control advocates' websites were cited only in anti-MRTP tweets (77.4% vs. pro = 0). Pro-MRTP valence appeared more frequently in tweets mentioning health (53.1% vs. anti =38.5%) and cessation (100% vs. anti = 0). Nearly 42% of tweets showed a bot score greater than .43, indicating a possibility of automation. Conclusion: Continuous efforts are needed to surveil the industry's attempts to create a climate of false consensus and circulate misinformation regarding MRTP on social media, as well as to assist non-scientific audiences' understanding of MRTP.

Characteristics of and User Engagement With Antivaping Posts on Instagram: Observational Study

BACKGROUND

Although government agencies acknowledge that messages about the adverse health effects of e-cigarette use should be promoted on social media, effectively delivering those health messages is challenging. Instagram is one of the most popular social media platforms among US youth and young adults, and it has been used to educate the public about the potential harm of vaping through antivaping posts.

OBJECTIVE

We aim to analyze the characteristics of and user engagement with antivaping posts on Instagram to inform future message development and information delivery.

METHODS

A total of 11,322 Instagram posts were collected from November 18, 2019, to January 2, 2020, by using antivaping hashtags including #novape, #novaping, #stopvaping, #dontvape, #antivaping, #quitvaping, #antivape, #stopjuuling, #dontvapeonthepizza, and #escapethevape. Among those posts, 1025 posts were randomly selected and 500 antivaping posts were further identified by hand coding. The image type, image content, and account type of antivaping posts were hand coded, the text information in the caption was explored by topic modeling, and the user engagement of each category was compared.

RESULTS

Analyses found that antivaping images of the educational/warning type were the most common (253/500; 50.6%). The average likes of the educational/warning type (15 likes/post) were significantly lower than the catchphrase image type (these emphasized a slogan such as "athletesdontvape" in the image; 32.5 likes/post; P<.001). The majority of the antivaping posts contained the image content element text (n=332, 66.4%), followed by the image content element people/person (n=110, 22%). The images containing people/person elements (32.8 likes/post) had more likes than the images containing other elements (13.8-21.1 likes/post). The captions of the antivaping Instagram posts covered topics including "lung health," "teen vaping," "stop vaping," and "vaping death cases." Among the 500 antivaping Instagram posts, while most posts were from the antivaping community (n=177, 35.4%) and personal account types (n=182, 36.4%), the antivaping community account type had the highest average number of posts (1.69 posts/account). However, there was no difference in the number of likes among different account types.

CONCLUSIONS

Multiple features of antivaping Instagram posts may be related to user engagement and perception. This study identified the critical elements associated with high user engagement, which could be used to design antivaping posts to deliver health-related information more efficiently.

Highlighting Contributions of Behavioral and Social Sciences in Advancing Public Health: Where We've Come, Where We're Headed

CONTEXT

Social and behavioral sciences, a cross-disciplinary field that examines the interaction among behavioral, biological, environmental, and social factors, has contributed immensely to some public health achievements over the last century. Through collaboration with community organizations and partners, social and behavioral scientists have conducted numerous program interventions involving community engagement and advocacy efforts at the local, state, federal, and international levels.

CONTRIBUTIONS OF SOCIAL AND BEHAVIORAL SCIENCES

This article traces select historical underpinnings of the applications of social and behavioral sciences theories and evidence to public health and highlights 4 areas in which health education specialists have distinctly contributed to public health achievements by building on theory and evidence. Applied social and behavioral sciences have formed the basis of various health education interventions. These 4 areas include the following: (1) Theory, Model Development, and the Professionalization of Health Education; (2) Participation and Community Engagement; (3) Health Communication; and (4) Advocacy and Policy.

DISCUSSION

We present contemporary challenges and recommendations for strengthening the theory, research, and practice of health education within the context of social and behavioral sciences in addressing emerging public health issues.

A content analysis of the tweets of e-cigarette proponents in Australia

ISSUE ADDRESSED

Social media sites have become platforms for public discourse on e-cigarettes, providing proponents with an opportunity to disseminate favourable information about the devices. Research examining the information being presented by Australian proponents of e-cigarettes is limited. Accordingly, this study explored the Twitter feeds of Australian proponents of e-cigarettes to determine the nature of the e-cigarette-related content being disseminated.

METHODS

All publicly available e-cigarette-related tweets and retweets (n = 1397) disseminated over a 15-week period by five Australian e-cigarette proponents were captured and analysed.

RESULTS

The main topics covered in the 1397 tweets analysed related to (a) criticism of the arguments made by public health agencies/advocates who oppose e-cigarettes (29%), (b) Australian e-cigarette policy (19%), (c) the health risks of e-cigarettes (16%) and (d) the efficacy of e-cigarettes as smoking cessation aids (13%). Proponents argued that the precautionary principle adopted by public health agencies/advocates lacks an appropriate evidence base and that legalising e-cigarettes would reduce smoking rates and smoking-related harm. Proponents minimised the risks associated with e-cigarette use and only presented evidence indicating that use facilitates smoking cessation.

CONCLUSIONS

The assessed tweets have the potential to reduce the public's trust in the information being presented by authoritative public health agencies/advocates. The dissemination of information downplaying the health risks associated with e-cigarettes may distort perceptions of the devices. SO WHAT?: To assist tobacco control efforts, results highlight the need for (a) ongoing surveillance of the tweets of e-cigarette proponents and (b) provision of evidence-based counterarguments on social media.

Inside the adolescent voice: A qualitative analysis of the appeal of different tobacco products

INTRODUCTION

While cigarette use has decreased, adolescents’ overall use of tobacco (e.g. e-cigarettes, cigars, and hookah) has increased. The purpose of this qualitative study is to highlight the decision-making process of adolescents to use certain products over others and why certain tobacco products appeal to them.

METHODS

Twenty-five participants were recruited from a larger study surveying adolescents’ perceptions and tobacco use (772 high school students). The participants were involved in one-on-one semi-structured phone interviews on the appeal of different tobacco products. Interviews were recorded, transcribed verbatim, and analyzed by identifying relevant codes and themes.

RESULTS

Participants for this study had a mean age of 16.4 (SD=1.2) years; over half (14/25) were female. Three major themes emerged from the interviews: 1) social context and circumstances to use, including using and sharing with peers, and reducing boredom; 2) importance of flavors, smell, taste, smoke tricks, and accessibility of products; and 3) misperceptions and misinformation of product risks.

CONCLUSIONS

The findings that emerged showed why participants favored certain tobacco products, especially e-cigarettes, over others. The results support areas for future research and practice, and inform how interventions can better address the appeal of different tobacco products to ultimately prevent adolescent use.

General Audience Engagement With Antismoking Public Health Messages Across Multiple Social Media Sites: Comparative Analysis

BACKGROUND

Public health organizations have begun to use social media to increase awareness of health harm and positively improve health behavior. Little is known about effective strategies to disseminate health education messages digitally and ultimately achieve optimal audience engagement.

OBJECTIVE

This study aims to assess the difference in audience engagement with identical antismoking health messages on three social media sites (Twitter, Facebook, and Instagram) and with a referring link to a tobacco prevention website cited in these messages. We hypothesized that health messages might not receive the same user engagement on these media, although these messages were identical and distributed at the same time.

METHODS

We measured the effect of health promotion messages on the risk of smoking among users of three social media sites (Twitter, Facebook, and Instagram) and disseminated 1275 health messages between April 19 and July 12, 2017 (85 days). The identical messages were distributed at the same time and as organic (unpaid) and advertised (paid) messages, each including a link to an educational website with more information about the topic. Outcome measures included message engagement (ie, the click-through rate [CTR] of the social media messages) and educational website engagement (ie, the CTR on the educational website [wCTR]). To analyze the data and model relationships, we used mixed effects negative binomial regression, z-statistic, and the Hosmer-Lemeshow goodness-of-fit test.

RESULTS

Comparisons between social media sites showed that CTRs for identical antitobacco health messages differed significantly across social media (P<.001 for all). Instagram showed the statistically significant highest overall mean message engagement (CTR=0.0037; 95% CI 0.0032-0.0042), followed by Facebook (CTR=0.0026; 95% CI 0.0022-0.0030) and Twitter (CTR=0.0015; 95% CI 0.0013-0.0017). Facebook showed the highest as well as the lowest CTR for any individual message. However, the message CTR is not indicative of user engagement with the educational website content. Pairwise comparisons of the social media sites differed with respect to the wCTR (P<.001 for all). Messages on Twitter showed the lowest CTR, but they resulted in the highest level of website engagement (wCTR=0.6308; 95% CI 0.5640-0.6975), followed by Facebook (wCTR=0.2213; 95% CI 0.1932-0.2495) and Instagram (wCTR=0.0334; 95% CI 0.0230-0.0438). We found a statistically significant higher CTR for organic (unpaid) messages (CTR=0.0074; 95% CI 0.0047-0.0100) compared with paid advertisements (CTR=0.0022; 95% CI 0.0017-0.0027; P<.001 and P<.001, respectively).

CONCLUSIONS

Our study provides evidence-based insights to guide the design of health promotion efforts on social media. Future studies should examine the platform-specific impact of psycholinguistic message variations on user engagement, include newer sites such as Snapchat and TikTok, and study the correlation between web-based behavior and real-world health behavior change. The need is urgent in light of increased health-related marketing and misinformation on social media.

Marketing Content on E-Cigarette Brand-Sponsored Facebook Profile Pages

INTRODUCTION

E-cigarettes are marketed on brand-sponsored Facebook profile pages despite Facebook's policy to prohibit e-cigarette marketing on their platform. We aimed to identify e-cigarette marketing strategies used and products marketed on brand-sponsored Facebook profiles and assess whether these strategies and featured products differ by user engagement.

METHODS

We examined up to 10 recent Facebook posts on 26 e-cigarette brand-sponsored profile pages uploaded between August 1 and November 31, 2016. We identified positive engagement (i.e. "like," "love"), negative engagement (i.e. "sad," "angry"), post type (e.g. link, photo), type of sales promotion (e.g. giveaways, discounts), non-sales promotion (e.g. event promotion without product marketing), and marketed products (e.g. e-cigarettes, e-liquids).

RESULTS

We examined 225 Facebook posts. Engagement was modest (e.g. Median "likes" = 8 [Min = 0, Max = 591]). The most common post types were photos (52.6%) and links (35.5%). Of all links, 83.7% were links to online shops. Of all posts, 35.0% had overt sales promotional content, 32.0% featured non-sales promotional content, and 68.0% featured an e-cigarette product. The most commonly featured product was an e-cigarette device (50.6%). Posts with more positive engagement included giveaways (versus sales [p = 0.009]) and posts marketing vaping devices (versus e-liquids [p = 0.004)]). Negative engagement was not associated with marketing strategies or products. Of the brand-sponsored profile pages, 42.3% could be accessed by underage users.

DISCUSSION

E-cigarettes are marketed on Facebook using a variety of promotional strategies. Importantly, underage youth often can access this marketing content. Comprehensive tobacco control policies that restrict e-cigarette marketing on social media are needed urgently.

Differential patterns of e-cigarette and tobacco marketing exposures among youth: Associations with substance use and tobacco prevention strategies

BACKGROUND

This study identified patterns of tobacco marketing exposures among youth and examined their associations with substance use and tobacco prevention strategies.

METHODS

In Fall 2018, 2,058 middle and high school students (ages 11-18) in an Appalachian county completed a substance use and behavioral health surveillance survey. We conducted latent class analysis (LCA) to identify exposure classes based on responses to 14 tobacco marketing exposures. Multinomial logistic regression was then performed to determine associations between the latent classes with past 30-day substance use and tobacco prevention strategies (e.g., school policies, parental rules, prevention messages).

RESULTS

Four latent classes of marketing exposure were identified among middle school students: low exposure, television, social media, and high exposure. Multinomial logistic regression found significant associations between e-cigarette use with the social media and high exposure classes, while prescription drug use was associated with the social media class and alcohol use with the high exposure class. For high school students, five classes were identified: low exposure, social media, environmental, cigarettes, and high exposure. E-cigarette and prescription drug use were associated with the social media and high exposure classes. Cigarette use was associated with the social media class. School rules prohibiting e-cigarettes were associated with the television class for middle school students. Self-reported exposure to prevention messages about the harms of tobacco were associated with multiple exposure classes for both middle (television and social media) and high school (social media and cigarettes) students, suggesting that both pro- and anti-tobacco communications have become ubiquitous and may be saturating youth.

CONCLUSION

This study demonstrates the need for stricter tobacco marketing regulations and multi-level interventions beginning in early adolescence that focus on increasing media-based literacy for youth to better discern tobacco prevention messages from pro-tobacco communications.

Early Cardiovascular Risk in E-cigarette Users: the Potential Role of Metals

PURPOSE OF REVIEW

Electronic cigarettes (e-cigs) are a source of metals. Epidemiologic and experimental evidence support that metals are toxic to the cardiovascular system. Little is known, however, about the role that e-cig metals may play as toxicants for the possible cardiovascular effects of e-cig use. The goal of this narrative review is to summarize the evidence on e-cig use and metal exposure and on e-cig use and cardiovascular toxicity and discuss the research needs.

RECENT FINDINGS

In vitro studies show cytotoxicity and increased oxidative stress in myocardial cells and vascular endothelial cells exposed to e-liquids and e-cig aerosols, with effects partially reversed with antioxidant treatment. There is some evidence that the heating coil plays a role in cell toxicity. Mice exposed to e-cigs for several weeks showed higher levels of oxidative stress, inflammation, platelet activation, and thrombogenesis. Cross-over clinical experiments show e-cig use alters nitric oxide-mediated flow-mediated dilation, endothelial progenitor cells, and arterial stiffness. Cross-sectional evidence from large nationally representative samples in the USA support that e-cig use is associated with self-reported myocardial infarction. Smaller studies found associations of e-cig use with higher oxidized low-density protein and heart variability compared to healthy controls. Numerous studies have measured elevated levels of toxic metals in e-cig aerosols including lead, nickel, chromium, and manganese. Arsenic has been measured in some e-liquids. Several of these metals are well known to be cardiotoxic. Numerous studies show that e-cigs are a source of cardiotoxic metals. Experimental studies (in vitro, in vivo, and clinical studies) show acute toxicity of e-cigs to the vascular system. Studies of long-term toxicity in animals and humans are missing. Longitudinal studies with repeated measures of metal exposure and subclinical cardiovascular outcomes (e.g., coronary artery calcification) could contribute to determine the long-term cardiovascular effects of e-cigs and the potential role of metals in those effects.

Electronic Cigarette-Related Contents on Instagram: Observational Study and Exploratory Analysis

Background

Instagram is a popular social networking platform for users to upload pictures sharing their experiences. Instagram has been widely used by vaping companies and stores to promote electronic cigarettes (e-cigarettes), as well as by public health entities to communicate the risks of e-cigarette use (vaping) to the public.

Objective

We aimed to characterize current vaping-related content on Instagram through descriptive analyses.

Methods

From Instagram, 42,951 posts were collected using vaping-related hashtags in November 2019. The posts were grouped as (1) pro-vaping, (2) vaping warning, (3) neutral to vaping, and (4) not related to vaping based on the attitudes to vaping expressed within the posts. From these Instagram posts and the corresponding 18,786 unique Instagram user accounts, 200 pro-vaping and 200 vaping-warning posts as well as 200 pro-vaping and 200 vaping-warning user accounts were randomly selected for hand coding. Furthermore, follower counts and media counts of the Instagram user accounts as well as the “like” counts and hashtags of the posts were compared between pro-vaping and vaping-warning groups.

Results

There were more posts in the pro-vaping group (41,412 posts) than there were in the vaping-warning group (1539 posts). The majority of pro-vaping images were product display images (163/200, 81.5%), and the most popular image type in vaping-warning posts was educational (95/200, 47.5%). The highest proportion of pro-vaping user account type was vaping store (110/189, 58.1%), and the store account type had the highest mean number of posts (10.33 posts/account). The top 3 vaping-warning user account types were personal (79/155, 51%), vaping-warning community (37/155, 23.9%), and community (35/155, 22.6%), of which the vaping-warning community had the highest mean number of posts (3.68 posts/account). Pro-vaping user accounts had more followers (median 850) and media (median 232) than vaping-warning user accounts had (follower count: median 191; media count: 92). Pro-vaping posts had more “likes” (median 22) and hashtags (mean 20.39) than vaping-warning posts had (“like” count: median 12; hashtags: mean 7.16).

Conclusions

Instagram is dominated by pro-vaping content, and pro-vaping posts and user accounts seem to have more user engagement than vaping-warning accounts have. These results highlight the importance of regulating e-cigarette posts on social media and the urgency of identifying effective communication content and message delivery methods with the public about the health effects of e-cigarettes to ameliorate the epidemic of vaping in youth.

What Does It Meme? A Qualitative Analysis of Adolescents' Perceptions of Tobacco and Marijuana Messaging

OBJECTIVES

With the increasing popularity of electronic cigarettes and legalization of recreational marijuana, messaging from websites and social media is shaping product perceptions and use. Quantitative research on the aesthetic appeal of these advertisements from the adolescent and young adult perspective is lacking. We evaluated (1) how adolescents and young adults perceived tobacco and marijuana messaging online and through social media platforms and (2) interactive behaviors related to these messages.

METHODS

We interviewed 24 participants from the Tobacco Perceptions Study, a longitudinal study of adolescents' and young adults' (aged 17-21) tobacco-related perceptions and tobacco use. We collected qualitative data from October 2017 through February 2018, through individual semi-structured interviews, on participants' experiences and interactions with online tobacco and marijuana advertisements and the advertisements' appeal. Two analysts recorded, transcribed, and coded interviews.

RESULTS

Themes that emerged from the interviews focused on the direct appeal of online messaging to adolescents and young adults; the value of trusting the source; the role of general attitudes and personal decision-making related to using tobacco and/or marijuana; the appeal of messaging that includes colors, interesting packaging, and appealing flavors; and the preference of messages communicated by young people and influencers rather than by industry.

CONCLUSION

These findings suggest the need for increased regulation of social media messaging and marketing of tobacco and marijuana, with a particular focus on regulating social media, paid influencers, and marketing that appeals to adolescents and young adults. The findings also suggest the importance of prevention programs addressing the role of social media in influencing the use of tobacco and marijuana.

#toolittletoolate: JUUL-related content on Instagram before and after self-regulatory action

Introduction

Digital e-cigarette marketing is largely unregulated and remains easily accessible to young people. The growing public concern around youth JUUL use and its viral presence on social media led the company to engage in several voluntary actions to remove and reduce JUUL-related content on Instagram in May 2018. The current study examined how JUUL-related Instagram content changed in the US following JUUL Labs’ wave of voluntary actions in May 2018.

Methods

In 2019, we collected a total of 50,817 JUUL-relevant posts by 16,323 unique users on Instagram from March 1-May 15, 2018 (Phase 1) and May 16-November 11, 2018 (Phase II) using the application programming interface. We conducted a semantic network analysis to identify major topic clusters over time.

Results

Approximately 14,838 JUUL-related posts were made by 5,201 accounts in Phase I and 35,979 posts were made by 11,122 accounts in Phase II. Major content clusters remained unchanged over time–key topics were JUUL-related product characteristics and JUUL-communities; the general vape community; and cannabis-related behavior. Of note, cannabis-related content grew in Phase II, particularly use of the term CBD.

Conclusions

Our results reflect the limits of voluntary industry actions to reduce or change vaping-related content on social media. Rather, strong federal restriction on commercial tobacco marketing is the optimal pathway to reduce initial product marketing exposure among youth. These limits would make the emergence and viral contagion of brand-related social media content less likely and reduce its influence on youth behavior.

Harnessing the power of social media: how can it help in axial spondyloarthritis research?

PURPOSE OF REVIEW

Axial spondyloarthritis (axSpA) is a chronic inflammatory rheumatic disease that is relatively unknown among the general public. Most patients with axSpA are young or middle-aged adults and more likely to use some social media. This review highlights trends in the application of social media and different ways in which these tools do already or may benefit clinical research, delivery of care, and education in rheumatology, particularly in the field of axSpA.

RECENT FINDINGS

This article discusses four areas in the biomedical field that social media has infused with novel ideas: (i) the use of patient-generated health data from social media to learn about their disease experience, (ii) delivering health education and interventions, (iii) recruiting study participants, and (iv) reform, transfer, and disseminate medical education. We conclude with promising studies in rheumatology that have incorporated social media and suggestions for future directions.

SUMMARY

Rheumatologists now have the opportunity to use social media and innovate on many aspects of their practice. We propose further exploration of multiple ways in which social media might help with the identification, diagnosis, education, and research study enrollment of axSpA patients. However, standardization in study design, reporting, and managing ethical and regulatory aspects will be required to take full advantage of this opportunity.

Engagement With Online Tobacco Marketing Among Adolescents in the United States: 2013-2014 to 2014-2015

OBJECTIVE

To assess changes in engagement with online tobacco and electronic cigarette (e-cigarette) marketing (online tobacco marketing) among adolescents in the United States between 2013 and 2015.

METHODS

We assessed the prevalence of six forms of engagement with online tobacco marketing, both overall and by brand, among adolescents sampled in Wave 1 (2013-2014; n = 13651) and Wave 2 (2014-2015; n = 12172) of the nationally representative Population Assessment for Tobacco and Health Study. Engagement was analyzed by tobacco use status: non-susceptible never tobacco users; susceptible never tobacco users; ever tobacco users, but not within the past year; and past-year tobacco users.

RESULTS

Among all adolescents, the estimated prevalence of engagement with at least one form of online tobacco marketing increased from 8.7% in 2013-2014 to 20.9% in 2014-2015. The estimated prevalence of engagement also increased over time across all tobacco use statuses (eg, from 10.5% to 26.6% among susceptible adolescents). Brand-specific engagement increased over time for cigarette, cigar, and e-cigarette brands.

CONCLUSION

Engagement with online tobacco marketing, both for tobacco and e-cigarettes, increased almost twofold over time. This increase emphasizes the dynamic nature of online tobacco marketing and its ability to reach youth. The Food and Drug Administration, in cooperation with social networking sites, should consider new approaches to regulate this novel form of marketing.

IMPLICATIONS

This is the first study to estimate the national prevalence of engagement with online tobacco marketing among adolescents over time. The estimated prevalence of this engagement approximately doubled between 2013-2014 and 2014-2015 among all adolescents and, notably, among adolescents at relatively low risk to initiate tobacco use. This increase in engagement could represent public health harm if it results in increased initiation and use of tobacco products. Stronger federal regulation of online tobacco marketing and tighter control of access to tobacco-related content by social media sites could reduce adolescents' exposure to and engagement with online tobacco marketing.

Tobacco Risk Information and Comparative Risk Assessment of E-Cigarettes Vs. Cigarettes: Application of the Reinforcing Spirals Model

We examine how individuals seek information about e-cigarette risk and selectively expose themselves to media sources that may provide information consistent with their existing beliefs and behaviors related to e-cigarettes in application of the Reinforcing Spirals Model (Slater, 2007). Additionally, the associations among e-cigarette risk information-seeking, tobacco risk information exposure via media, and comparative risk assessment of e-cigarettes versus conventional cigarettes were identified. The results were compared among current users, former users, and those who had never used e-cigarettes ("never users"). A nationally representative data from the 2017 Health Information National Trends Surveys - FDA was employed. Our analyses suggest the presence of comparative risk perception among current users as assessing the health harm and addiction risk of e-cigarettes significantly lower than cigarettes. Current users did not avoid information about the health effects of e-cigarettes; they were more likely to look for such information than former and never users. Current users' e-cigarette risk information-seeking was negatively associated with the difference between perceived addiction risk of e-cigarettes and that of cigarettes. Current users' tobacco risk information exposure via social media was related with a lower level of the perceived risk of e-cigarettes, while such exposure via news media was related with a higher level of perceived risk of e-cigarettes. Our findings suggest the need for regulating and counteracting the prevalent e-cigarette information that discounts the relative risks of e-cigarettes as well as the potential of news media as influential sources helping current users scrutinize the risks.

Youth say ads for flavored e-liquids are for them

INTRODUCTION

E-cigarettes are the most popular tobacco product among adolescents and young adults ("AYA") and are available in many flavors. The e-cigarette industry argues that flavors are not meant to appeal to youth, yet no study has asked youth what age group they think ads for flavored e-liquids are targeting. We asked AYA which age group they thought ads for flavored e-liquids targeted.

METHODS

In 2016 as part of a larger survey, a random sample of 255 youth from across California (62.4% female, mean age = 17.5, SD = 1.7) viewed eight ads, presented in randomized order, for fruit-, dessert-, alcohol-, and coffee-flavored e-liquids and indicated the age group they thought the ads targeted: younger, same age, a little older, or much older than them. Population means and 95% confidence intervals were estimated using bootstrapping (100,000 replicate samples).

RESULTS

Most participants (93.7%) indicated the cupcake man flavor ad targeted an audience of people younger than they. Over half felt ads for smoothy (68.2%), cherry (63.9%), vanilla cupcake (58%), and caramel cappuccino (50.4%) targeted their age and for no flavor ad did most feel the primary target age group was much older.

CONCLUSIONS

Youth believe ads for flavored e-liquids target individuals about their age, not older adults. Findings support the need to regulate flavored e-liquids and associated ads to reduce youth appeal, which ultimately could reduce youth use of e-cigarettes.

"Technophilia": A new risk factor for electronic cigarette use among early adolescents?

PURPOSE

Develop and validate a scale that measures Technophilia (positive orientation toward new technology) and use it to address orientation toward new technologies to explain e-cigarette trial and adoption, especially in relatively low risk adolescents.

METHODS

Survey data were obtained from students of the three largest cities in Mexico (n = 8123). We developed eight questions involving access, use and pleasure from different electronic media to measure technophilia. Exploratory factor analysis (EFA) was conducted. Linear GEE models were used when regressing technophilia on covariates. When regressing e-cigarette and conventional cigarette trial and use, logistic GEE models were used. Finally, we used multinomial logistic regression to evaluate the associations between technophilia and e-cigarettes as the first tobacco product.

RESULTS

Technophilia were correlated with theoretically-related variables. Unadjusted and adjusted models regressing e-cigarette trial and use indicated that students in the highest quartile for technophilia were more likely to have tried e-cigarettes compared with the lowest quartile (AORQ4 vs Q1 = 1.36, 95% CI 1.14-1.62). Technophilia was not independently associated with current e-cigarette use in adjusted models. Students with higher technophilia were more likely to have first tried e-cigarettes in both crude and adjusted models (AORQ4vQ1 = 1.66, 95% CI 1.20-2.31; AORQ3vQ1 = 1.43, 95% CI 1.02-2.01). Technophilia did not have a statistically significant, independent association with first use of other tobacco products.

CONCLUSION

This study suggests that technophilia is associated with trial of e-cigarettes among youth. The measure we developed appears useful for understanding why some youth are open to trying novel, technologically oriented ways to consume nicotine.

A longitudinal analysis of electronic cigarette forum participation

Electronic cigarette (e-cigarette) Internet forums are social networking websites that allow members around the world to share information and personal experiences about e-cigarettes. However, little is known about their popularity and reach. This longitudinal study investigated indicators of participation (membership, number of discussion boards, and number of message posts) in 77 e-cigarette forums from February 2016 to January 2017. Autoregressive time-series analyses were used to assess monthly changes in participation among small (<1000 members), medium (1000-5000 members), and large (>5000 members) forums that were active at all 12 observation time points. Paired sample t-tests were conducted to compare changes in participation before and after the U.S. Food and Drug Administration announced the regulation of e-cigarettes. Analyses revealed significant and consistent increases in forum membership (R²s > 0.72; ps < 0.01), discussion boards (R²s > 0.97; ps < 0.001), and message posts (R²s > 0.96; ps < 0.001) across all forum sizes during the 12-month period. No differences were found in participation indicators pre- and post-regulation announcement. E-cigarette forums provide real-time information on the levels of participation over time and therefore may be an important platform to study interactions among consumers and how these interactions shape e-cigarette knowledge, attitudes and use behaviors.

Strategies to find audience segments on Twitter for e-cigarette education campaigns

The development of public health education campaigns about tobacco products requires an understanding of specific audience segments including their views, intentions, use of media, perceived barriers, and benefits of change. For example, identifying and targeting individuals who express ambivalence about e-cigarette use on Twitter may be helpful in devising and focusing public health campaigns to reduce e-cigarette use. This study developed a novel analytic strategy using social network analysis to identify audience segments on Twitter based on positive, negative, and neutral e-cigarette sentiment. Using Twitter data collected from April 2015 to March 2016, we identified different sub-groups of users who retweeted about e-cigarettes, and measured each sub-group's clustering coefficient (CC), which describes how tightly people cluster together. Ten high CC and ten low CC groups were randomly selected; then 100 randomly selected tweets from each group were coded for e-cigarette sentiment (positive, negative, neutral). Results indicate that differences in e-cigarette sentiment are associated with clustering of Twitter network ties. Statistical analyses revealed that high CC groups were more likely to have strong e-cigarette sentiments, suggesting that tightly clustered groups may be "echo chambers" (i.e., like-minded people repeating the same messages). By contrast, low CC groups were more likely to have neutral sentiments, and had greater fluctuation in sentiment over time, suggesting that they may be more flexible in their opinions about e-cigarettes and may be particularly receptive to targeted public health campaigns. Informatics techniques such as determination of clusters using social network analysis can be useful in identifying audience segments for future public health campaigns.

Tweeting about public health policy: Social media response to the UK Government's announcement of a Parliamentary vote on draft standardised packaging regulations

BACKGROUND

Standardised tobacco packaging has been, and remains, a contentious policy globally, attracting corporate, public health, political, media and popular attention. In January 2015, the UK Government announced it would vote on draft regulations for the policy before the May 2015 General Election. We explored reactions to the announcement on Twitter, in comparison with an earlier period of little UK Government activity on standardised packaging.

METHODS

We obtained a random sample of 1038 tweets in two 4-week periods, before and after the UK Government's announcement. Content analysis was used to examine the following Tweet characteristics: support for the policy, purpose, Twitter-user's geographical location and affiliation, and evidence citation and quality. Chi-squared analyses were used to compare Tweet characteristics between the two periods.

RESULTS

Overall, significantly more sampled Tweets were in favour of the policy (49%) in comparison to those opposed (19%). Yet, at Time 2, following the announcement, a greater proportion of sampled tweets opposed standardised packaging compared to the period sampled at Time 1, prior to the announcement (p<0.001). The quality of evidence and research cited in URLs linked at Time 2 was significantly lower than at Time 1 (p<0.001), with peer-reviewed research more likely to be shared in positive Tweets (p<0.001) and in Tweets linking to URLs originating from the health sector (p<0.001). The decline in the proportion of positive Tweets was mirrored by a reduction in Tweets by health sector Twitter-users at Time 2 (p<0.001).

CONCLUSIONS

Microblogging sites can reflect offline policy debates and are used differently by policy proponents and opponents dependent on the policy context. Twitter-users opposed to standardised packaging increased their activity following the Government's announcement, while those in support broadly maintained their rate of Twitter engagement. The findings offer insight into the public health community's options for using Twitter to influence policy and disseminate research. In particular, proliferation of Twitter activity following pro-public health policy announcements could be considered to ensure pro-health messages are not overshadowed by anti-regulation voices.

The Messages Presented in Electronic Cigarette-Related Social Media Promotions and Discussion: Scoping Review

BACKGROUND

There has been a rapid rise in the popularity of electronic cigarettes (e-cigarettes) over the last decade, with growth predicted to continue. The uptake of these devices has escalated despite inconclusive evidence of their efficacy as a smoking cessation device and unknown long-term health consequences. As smoking rates continue to drop or plateau in many well-developed countries, transnational tobacco companies have transitioned into the vaping industry and are now using social media to promote their products. Evidence indicates e-cigarettes are being marketed on social media as a harm reduction alternative, with retailers and manufacturers utilizing marketing techniques historically used by the tobacco industry.

OBJECTIVE

This study aimed to identify and describe the messages presented in e-cigarette-related social media (Twitter, YouTube, Instagram, and Pinterest) promotions and discussions and identify future directions for research, surveillance, and regulation.

METHODS

Data sources included MEDLINE, Scopus, ProQuest, Informit, the Journal of Medical Internet Research, and Google Scholar. Included studies were published in English between 2007 and 2017, analyzed content captured from e-cigarette-related social media promotions or discussions, and reported results for e-cigarettes separately from other forms of tobacco and nicotine delivery. Database search ceased in October 2017. Initial searches identified 536 studies. Two reviewers screened studies by title and abstract. One reviewer examined 71 full-text articles to determine eligibility and identified 25 studies for inclusion. This process was undertaken with the assistance of the Web-based screening and data extraction tool-Covidence. The review was registered with the Joanna Briggs Institute (JBI) Systematic Reviews database and followed the methodology for JBI Scoping Reviews.

RESULTS

Several key messages are being used to promote e-cigarettes including as a safer alternative to cigarettes, efficacy as a smoking cessation aid, and for use where smoking is prohibited. Other major marketing efforts aimed at capturing a larger market involve promotion of innovative flavoring and highlighting the public performance of vaping. Discussion and promotion of these devices appear to be predominantly occurring among the general public and those with vested interests such as retailers and manufacturers. There is a noticeable silence from the public health and government sector in these discussions on social media.

CONCLUSIONS

The social media landscape is dominated by pro-vaping messages disseminated by the vaping industry and vaping proponents. The uncertainty surrounding e-cigarette regulation expressed within the public health field appears not to be reflected in ongoing social media dialogues and highlights the need for public health professionals to interact with the public to actively influence social media conversations and create a more balanced discussion. With the vaping industry changing so rapidly, real-time monitoring and surveillance of how these devices are discussed, promoted, and used on social media is necessary in conjunction with evidence published in academic journals.

Supplementing a survey with respondent Twitter data to measure e-cigarette information exposure

Social media data are increasingly used by researchers to gain insights on individuals' behaviors and opinions. Platforms like Twitter provide access to individuals' postings, networks of friends and followers, and the content to which they are exposed. This article presents the methods and results of an exploratory study to supplement survey data with respondents' Twitter postings, networks of Twitter friends and followers, and information to which they were exposed about e-cigarettes. Twitter use is important to consider in e-cigarette research and other topics influenced by online information sharing and exposure. Further, Twitter metadata provide direct measures of user's friends and followers as opposed to survey self-reports. We find that Twitter metadata provide similar information to survey questions on Twitter network size without inducing recall error or other measurement issues. Using sentiment coding and machine learning methods, we find Twitter can elucidate on topics difficult to measure via surveys such as online expressed opinions and network composition. We present and discuss models predicting whether respondents' tweet positively about e-cigarettes using survey and Twitter data, finding the combined data to provide broader measures than either source alone.

"Okay, We Get It. You Vape": An Analysis of Geocoded Content, Context, and Sentiment regarding E-Cigarettes on Twitter

The current study examined conversations on Twitter related to use and perceptions of e-cigarettes in the United States. We employed the Social Media Analytic and Research Testbed (SMART) dashboard, which was used to identify and download (via a public API) e-cigarette-related geocoded tweets. E-cigarette-related tweets were collected continuously using customized geo-targeted Twitter APIs. A total of 193,051 tweets were collected between October 2015 and February 2016. Of these tweets, a random sample of 973 geocoded tweets were selected and manually coded for information regarding source, context, and message characteristics. Our findings reveal that although over half of tweets were positive, a sizeable portion was negative or neutral. We also found that, among those tweets mentioning a stigma of e-cigarettes, most confirmed that a stigma does exist. Conversely, among tweets mentioning the harmfulness of e-cigarettes, most denied that e-cigarettes were a health hazard. These results suggest that current efforts have left the public with ambiguity regarding the potential dangers of e-cigarettes. Consequently, it is critical to communicate the public health stance on this issue to inform the public and provide counterarguments to the positive sentiments presently dominating conversations about e-cigarettes on social media. The lack of awareness and need to voice a public health position on e-cigarettes represents a vital opportunity to continue winning gains for tobacco control and prevention efforts through health communication interventions targeting e-cigarettes.

Whose Post Is It? Predicting E-cigarette Brand from Social Media Posts

OBJECTIVES

E-cigarette advertisers know that 76% of youth use social media, yet little is known about the nature of e-cigarette advertising on social media most favored by youth. We utilized text-mining to characterize e-cigarette advertising and marketing messages from image-focused social media brand sites, and to construct and test an algorithm for predicting brand from brand-generated social media posts.

METHODS

Data comprised 5022 unique posts accompanied by an image from Facebook, Instagram or Pinterest e-cigarette brand pages for Blu, Logic, Metro, and NJOY from February 2012 to April 2015. Text-tokenization was used to quantify text for use as predictors in analyses.

RESULTS

Blu had the largest social media presence (65%), followed by Logic (16%), NJOY (12%) and Metro (7%). Blu's average post length was significantly shorter than all other brands. Words most commonly used in posts differed by brand. Regression analyses successfully differentiated Blu and NJOY brands from other brands.

CONCLUSIONS

Analyses revealed e-cigarette brands used different types of messages to appeal to social media users. Whereas words used by Blu and NJOY sold a "lifestyle," words used by Logic and Metro relied on device and product identification.

Real Time Assessment of Young Adults' Attitudes toward Tobacco Messages

Objectives

We used ecological momentary assessment (EMA) to examine young adults' attitudes towards pro-tobacco messages encountered in real time and their association with intentions to use tobacco.

Methods

Young adults (N = 92, ages 18-29) recorded sightings of marketing or social media related to tobacco in real time via mobile app for 28 days. Participants reported message characteristics, their attitudes towards the message, and intentions to use the depicted product for each submission. We used generalized linear mixed models to examine factors related to attitude towards message and intentions to use tobacco.

Results

Messages depicting e-cigarettes (p < .001) or hookah (p < .05) were associated with significantly more favorable attitudes compared with traditional cigarettes. Positive attitude towards the message was significantly associated with intention to use the depicted product (p < .001). Messages depicting e-cigarettes and hookah were significantly associated with higher intention to use. Message source was not significantly related to attitudes towards the message or product use intentions.

Conclusions

Marketing featuring e-cigarettes and hookah is an important target for future regulation. Given that pro-tobacco and e-cigarette messages are prevalent online, future research should consider the Internet and social media as important venues for counter-marketing and intervention efforts.

The 500-year Cultural & Economic Trajectory of Tobacco: A Circle Complete

Who smokes, and why do they do it? What factors discourage and otherwise reward or incentivize smoking? Tobacco use has been accompanied by controversy from the moment of its entry into European culture, and conflicting opinions regarding its potentially adverse influence on health have coexisted for hundreds of years. Its use in all forms represents the world's single greatest cause of preventable disease and death. Tobacco was introduced to Europe by Christopher Columbus, who in October 1492 discovered the crop in Cuba. While the next four centuries would see tobacco as the most highly traded economic commodity, by 1900, the now familiar cigarette remained obscure and accounted for only 2% of total tobacco sales. Global tobacco consumption rose sharply after 1914 and became especially prevalent following World War II, particularly among men. Indeed, overall tobacco sales increased by more than 60% by the mid-20th century, and cigarettes were a critical driver of this growth. Cigarettes dominated the tobacco market by 1950, by then accounting for more than 80% of all tobacco purchases. In the absence of clinical and scientific evidence against tobacco, moral and religious arguments dominated opposition voices against tobacco consumption in the 1800s. However, by the mid-20th century, advancements in medical research supported enhanced government and voluntary actions against tobacco advertising and also raised awareness of the dangers associated with passive tobacco smoke exposure. Solid epidemiological work connecting tobacco use with "the shortening of life span" began to appear in the medical literature in the 1950s, linking smoking with lung cancer and related conditions. In subsequent years, these developments led to significant curtailment of tobacco use. This monograph explores aspects of the intersection of tobacco with themes of behavioral incentives, religion, culture, literature, economics, and government over the past five centuries.

E-Cigarette Surveillance With Social Media Data: Social Bots, Emerging Topics, and Trends

Background

As e-cigarette use rapidly increases in popularity, data from online social systems (Twitter, Instagram, Google Web Search) can be used to capture and describe the social and environmental context in which individuals use, perceive, and are marketed this tobacco product. Social media data may serve as a massive focus group where people organically discuss e-cigarettes unprimed by a researcher, without instrument bias, captured in near real time and at low costs.

Objective

This study documents e-cigarette–related discussions on Twitter, describing themes of conversations and locations where Twitter users often discuss e-cigarettes, to identify priority areas for e-cigarette education campaigns. Additionally, this study demonstrates the importance of distinguishing between social bots and human users when attempting to understand public health–related behaviors and attitudes.

Methods

E-cigarette–related posts on Twitter (N=6,185,153) were collected from December 24, 2016, to April 21, 2017. Techniques drawn from network science were used to determine discussions of e-cigarettes by describing which hashtags co-occur (concept clusters) in a Twitter network. Posts and metadata were used to describe where geographically e-cigarette–related discussions in the United States occurred. Machine learning models were used to distinguish between Twitter posts reflecting attitudes and behaviors of genuine human users from those of social bots. Odds ratios were computed from 2x2 contingency tables to detect if hashtags varied by source (social bot vs human user) using the Fisher exact test to determine statistical significance.

Results

Clusters found in the corpus of hashtags from human users included behaviors (eg, #vaping), vaping identity (eg, #vapelife), and vaping community (eg, #vapenation). Additional clusters included products (eg, #eliquids), dual tobacco use (eg, #hookah), and polysubstance use (eg, #marijuana). Clusters found in the corpus of hashtags from social bots included health (eg, #health), smoking cessation (eg, #quitsmoking), and new products (eg, #ismog). Social bots were significantly more likely to post hashtags that referenced smoking cessation and new products compared to human users. The volume of tweets was highest in the Mid-Atlantic (eg, Pennsylvania, New Jersey, Maryland, and New York), followed by the West Coast and Southwest (eg, California, Arizona and Nevada).

Conclusions

Social media data may be used to complement and extend the surveillance of health behaviors including tobacco product use. Public health researchers could harness these data and methods to identify new products or devices. Furthermore, findings from this study demonstrate the importance of distinguishing between Twitter posts from social bots and humans when attempting to understand attitudes and behaviors. Social bots may be used to perpetuate the idea that e-cigarettes are helpful in cessation and to promote new products as they enter the marketplace.

The messages presented in online electronic cigarette promotions and discussions: a scoping review protocol

INTRODUCTION

Electronic cigarettes have become increasingly popular over the last 10 years. These devices represent a new paradigm for tobacco control offering smokers an opportunity to inhale nicotine without inhaling tobacco smoke. To date there are no definite conclusions regarding the safety and long-term health effects of electronic cigarettes; however, there is evidence that they are being marketed online as a healthier alternative to traditional cigarettes. This scoping review aims to identify and describe the breadth of messages (eg, health, smoking-cessation and price related claims) presented in online electronic cigarette promotions and discussions.

METHODS AND ANALYSIS

A scoping review will be undertaken adhering to the methodology outlined in The Joanna Briggs Institute Manual for Scoping Reviews. Six key electronic databases will be searched to identify eligible studies. Studies must be published in English between 2007 and 2017, examine and/or analyse content captured from online electronic cigarette promotions or discussions and report results for electronic cigarettes separately to other forms of tobacco delivery. Studies will be screened initially by title and abstract, followed by full-text review. Results of the search strategy will be reported in a PRISMA flow diagram and presented in tabular form with accompanying narrative summary.

ETHICS AND DISSEMINATION

The methodology consists of reviewing and collecting data from publicly available studies, and therefore does not require ethics approval. Results will be published in a peer reviewed journal and be presented at national/international conferences. Additionally, findings will be disseminated via social media and online platforms. Advocacy will be key to informing policy makers of regulatory and health issues that need to be addressed.

REGISTRATION DETAILS

The review was registered prospectively with The Joanna Briggs Institute Systematic Reviews database.

Classification of Twitter Users Who Tweet About E-Cigarettes

Background

Despite concerns about their health risks, e‑cigarettes have gained popularity in recent years. Concurrent with the recent increase in e‑cigarette use, social media sites such as Twitter have become a common platform for sharing information about e-cigarettes and to promote marketing of e‑cigarettes. Monitoring the trends in e‑cigarette–related social media activity requires timely assessment of the content of posts and the types of users generating the content. However, little is known about the diversity of the types of users responsible for generating e‑cigarette–related content on Twitter.

Objective

The aim of this study was to demonstrate a novel methodology for automatically classifying Twitter users who tweet about e‑cigarette–related topics into distinct categories.

Methods

We collected approximately 11.5 million e‑cigarette–related tweets posted between November 2014 and October 2016 and obtained a random sample of Twitter users who tweeted about e‑cigarettes. Trained human coders examined the handles’ profiles and manually categorized each as one of the following user types: individual (n=2168), vaper enthusiast (n=334), informed agency (n=622), marketer (n=752), and spammer (n=1021). Next, the Twitter metadata as well as a sample of tweets for each labeled user were gathered, and features that reflect users’ metadata and tweeting behavior were analyzed. Finally, multiple machine learning algorithms were tested to identify a model with the best performance in classifying user types.

Results

Using a classification model that included metadata and features associated with tweeting behavior, we were able to predict with relatively high accuracy five different types of Twitter users that tweet about e‑cigarettes (average F₁ score=83.3%). Accuracy varied by user type, with F₁ scores of individuals, informed agencies, marketers, spammers, and vaper enthusiasts being 91.1%, 84.4%, 81.2%, 79.5%, and 47.1%, respectively. Vaper enthusiasts were the most challenging user type to predict accurately and were commonly misclassified as marketers. The inclusion of additional tweet-derived features that capture tweeting behavior was found to significantly improve the model performance—an overall F₁ score gain of 10.6%—beyond metadata features alone.

Conclusions

This study provides a method for classifying five different types of users who tweet about e‑cigarettes. Our model achieved high levels of classification performance for most groups, and examining the tweeting behavior was critical in improving the model performance. Results can help identify groups engaged in conversations about e‑cigarettes online to help inform public health surveillance, education, and regulatory efforts.

Patterns of Twitter Behavior Among Networks of Cannabis Dispensaries in California

Background

Twitter represents a social media platform through which medical cannabis dispensaries can rapidly promote and advertise a multitude of retail products. Yet, to date, no studies have systematically evaluated Twitter behavior among dispensaries and how these behaviors influence the formation of social networks.

Objectives

This study sought to characterize common cyberbehaviors and shared follower networks among dispensaries operating in two large cannabis markets in California.

Methods

From a targeted sample of 119 dispensaries in the San Francisco Bay Area and Greater Los Angeles, we collected metadata from the dispensary accounts using the Twitter API. For each city, we characterized the network structure of dispensaries based upon shared followers, then empirically derived communities with the Louvain modularity algorithm. Principal components factor analysis was employed to reduce 12 Twitter measures into a more parsimonious set of cyberbehavioral dimensions. Finally, quadratic discriminant analysis was implemented to verify the ability of the extracted dimensions to classify dispensaries into their derived communities.

Results

The modularity algorithm yielded three communities in each city with distinct network structures. The principal components factor analysis reduced the 12 cyberbehaviors into five dimensions that encompassed account age, posting frequency, referencing, hyperlinks, and user engagement among the dispensary accounts. In the quadratic discriminant analysis, the dimensions correctly classified 75% (46/61) of the communities in the San Francisco Bay Area and 71% (41/58) in Greater Los Angeles.

Conclusions

The most centralized and strongly connected dispensaries in both cities had newer accounts, higher daily activity, more frequent user engagement, and increased usage of embedded media, keywords, and hyperlinks. Measures derived from both network structure and cyberbehavioral dimensions can serve as key contextual indicators for the online surveillance of cannabis dispensaries and consumer markets over time.

Methods for Coding Tobacco-Related Twitter Data: A Systematic Review

Background

As Twitter has grown in popularity to 313 million monthly active users, researchers have increasingly been using it as a data source for tobacco-related research.

Objective

The objective of this systematic review was to assess the methodological approaches of categorically coded tobacco Twitter data and make recommendations for future studies.

Methods

Data sources included PsycINFO, Web of Science, PubMed, ABI/INFORM, Communication Source, and Tobacco Regulatory Science. Searches were limited to peer-reviewed journals and conference proceedings in English from January 2006 to July 2016. The initial search identified 274 articles using a Twitter keyword and a tobacco keyword. One coder reviewed all abstracts and identified 27 articles that met the following inclusion criteria: (1) original research, (2) focused on tobacco or a tobacco product, (3) analyzed Twitter data, and (4) coded Twitter data categorically. One coder extracted data collection and coding methods.

Results

E-cigarettes were the most common type of Twitter data analyzed, followed by specific tobacco campaigns. The most prevalent data sources were Gnip and Twitter’s Streaming application programming interface (API). The primary methods of coding were hand-coding and machine learning. The studies predominantly coded for relevance, sentiment, theme, user or account, and location of user.

Conclusions

Standards for data collection and coding should be developed to be able to more easily compare and replicate tobacco-related Twitter results. Additional recommendations include the following: sample Twitter’s databases multiple times, make a distinction between message attitude and emotional tone for sentiment, code images and URLs, and analyze user profiles. Being relatively novel and widely used among adolescents and black and Hispanic individuals, Twitter could provide a rich source of tobacco surveillance data among vulnerable populations.

Public reactions to e-cigarette regulations on Twitter: a text mining analysis

BACKGROUND

In May 2016, the Food and Drug Administration (FDA) issued a final rule that deemed e-cigarettes to be within their regulatory authority as a tobacco product. News and opinions about the regulation were shared on social media platforms, such as Twitter, which can play an important role in shaping the public's attitudes. We analysed information shared on Twitter for insights into initial public reactions.

METHODS

A text mining approach was used to uncover important topics among reactions to the e-cigarette regulations on Twitter. SAS Text Miner V.12.1 software was used for descriptive text mining to uncover the primary topics from tweets collected from May 1 to May 17 2016 using NUVI software to gather the data.

RESULTS

A total of nine topics were generated. These topics reveal initial reactions to whether the FDA's e-cigarette regulations will benefit or harm public health, how the regulations will impact the emerging e-cigarette market and efforts to share the news. The topics were dominated by negative or mixed reactions.

CONCLUSIONS

In the days following the FDA's announcement of the new deeming regulations, the public reaction on Twitter was largely negative. Public health advocates should consider using social media outlets to better communicate the policy's intentions, reach and potential impact for public good to create a more balanced conversation.

E-Cigarette Social Media Messages: A Text Mining Analysis of Marketing and Consumer Conversations on Twitter

Background

As the use of electronic cigarettes (e-cigarettes) rises, social media likely influences public awareness and perception of this emerging tobacco product.

Objective

This study examined the public conversation on Twitter to determine overarching themes and insights for trending topics from commercial and consumer users.

Methods

Text mining uncovered key patterns and important topics for e-cigarettes on Twitter. SAS Text Miner 12.1 software (SAS Institute Inc) was used for descriptive text mining to reveal the primary topics from tweets collected from March 24, 2015, to July 3, 2015, using a Python script in conjunction with Twitter’s streaming application programming interface. A total of 18 keywords related to e-cigarettes were used and resulted in a total of 872,544 tweets that were sorted into overarching themes through a text topic node for tweets (126,127) and retweets (114,451) that represented more than 1% of the conversation.

Results

While some of the final themes were marketing-focused, many topics represented diverse proponent and user conversations that included discussion of policies, personal experiences, and the differentiation of e-cigarettes from traditional tobacco, often by pointing to the lack of evidence for the harm or risks of e-cigarettes or taking the position that e-cigarettes should be promoted as smoking cessation devices.

Conclusions

These findings reveal that unique, large-scale public conversations are occurring on Twitter alongside e-cigarette advertising and promotion. Proponents and users are turning to social media to share knowledge, experience, and questions about e-cigarette use. Future research should focus on these unique conversations to understand how they influence attitudes towards and use of e-cigarettes.