Jidong Huang

A cross-sectional examination of marketing of electronic cigarettes on Twitter.

Background Rapid increases in marketing of e-cigarettes coincide with growth in e-cigarette use in recent years; however, little is known about how e-cigarettes are marketed on social media platforms. Methods Keywords were used to collect tweets related to e-cigarettes from the Twitter Firehose between 1 May 2012 and 30 June 2012. Tweets were coded for smoking cessation mentions, as well as health and safety mentions, and were classified as commercial or non-commercial (‘organic’) tweets using a combination of Naïve Bayes machine learning methods, keyword algorithms and human coding. Metadata associated with each tweet were used to examine the characteristics of accounts tweeting about e-cigarettes. Results 73 672 tweets related to e-cigarettes were captured in the study period, 90% of which were classified as commercial tweets. Accounts tweeting commercial e-cigarette content were associated with lower Klout scores, a measure of influence. Commercial tweeting was largely driven by a small group of highly active accounts, and 94% of commercial tweets included links to websites, many of which sell or promote e-cigarettes. Approximately 10% of commercial and organic tweets mentioned smoking cessation, and 34% of commercial tweets included mentions of prices or discounts for e-cigarettes. Conclusions Twitter appears to be an important marketing platform for e-cigarettes. Tweets related to e-cigarettes were overwhelmingly commercial, and a substantial proportion mentioned smoking cessation. E-cigarette marketing on Twitter may have public health implications. Continued surveillance of e-cigarette marketing on social media platforms is needed.

Wanna know about vaping? Patterns of message exposure, seeking and sharing information about e-cigarettes across media platforms.

Background Awareness and use of electronic cigarettes has rapidly grown in the USA recently, in step with increased product marketing. Using responses to a population survey of US adults, we analysed demographic patterns of exposure to, searching for and sharing of e-cigarette-related information across media platforms. Methods An online survey of 17 522 US adults was conducted in 2013. The nationally representative sample was drawn from GfK Groups KnowledgePanel plus off-panel recruitment. Fixed effects logit models were applied to analyse relationships between exposure to, searching for and sharing of e-cigarette-related information and demographic characteristics, e-cigarette and tobacco use, and media behaviours. Results High levels of awareness about e-cigarettes were indicated (86% aware; 47% heard through media channels). Exposure to e-cigarette-related information was associated with tobacco use, age, gender, more education, social media use and time spent online. Although relatively small proportions of the sample had searched for (∼5%) or shared (∼2%) e-cigarette information, our analyses indicated demographic patterns to those behaviours. Gender, high income and using social media were associated with searching for e-cigarette information; lesbian, gay and bisexual and less education were associated with sharing. Current tobacco use, age, being Hispanic and time spent online were associated with both searching and sharing. Conclusions US adults are widely exposed to e-cigarette marketing through the media; such marketing may differentially target specific demographic groups. Further research should longitudinally examine how exposure to, searching for and sharing of e-cigarette information relate to subsequent use of e-cigarettes and/or combustible tobacco.

The availability of electronic cigarettes in US retail outlets, 2012: results of two national studies

Background Since their introduction in 2007, electronic cigarette (‘e-cigarette’) awareness and use has grown rapidly. Little is known about variation in e-cigarette availability across areas with different levels of tobacco taxes and smoke-free air policies. This paper looks at US retail availability of e-cigarettes and factors at the store, neighbourhood and policy levels associated with it. Methods In-person store audit data collected in 2012 came from two national samples of tobacco retailers in the contiguous US. Study 1 collected data from a nationally representative sample of tobacco retailers (n=2165). Study 2 collected data from tobacco retailers located in school enrolment zones for nationally representative samples of 8th, 10th and 12th grade public school students (n=2526). Results In 2012, e-cigarette retail availability was 34% in study 1 and 31% in study 2. Tobacco, pharmacy and gas/convenience stores were more likely to sell e-cigarettes than beer/wine/liquor stores. Retail availability of e-cigarettes was more likely in neighbourhoods with higher median household income (study 1), and lower percent of African–American (studies 1 and 2) and Hispanic residents (study 2). Price of traditional cigarettes was inversely related to e-cigarette availability. Stores in states with an American Lung Association Smoke-Free Air grade of F (study 1) or D (study 2) compared with A had increased likelihood of having e-cigarettes. Conclusions Currently, e-cigarette availability appears more likely in areas with weak tax and smoke-free air policies. Given the substantial availability of e-cigarettes at tobacco retailers nationwide, states and localities should monitor the sales and marketing of e-cigarettes at point of sale (POS).

Cigarette graphic warning labels and smoking prevalence in Canada: a critical examination and reformulation of the FDA regulatory impact analysis

Background The estimated effect of cigarette graphic warning labels (GWL) on smoking rates is a key input to the Food and Drug Administrations (FDA) regulatory impact analysis (RIA), required by law as part of its rule-making process. However, evidence on the impact of GWLs on smoking prevalence is scarce. Objective The goal of this paper is to critically analyse FDAs approach to estimating the impact of GWLs on smoking rates in its RIA, and to suggest a path forward to estimating the impact of the adoption of GWLs in Canada on Canadian national adult smoking prevalence. Methods A quasi-experimental methodology was employed to examine the impact of adoption of GWLs in Canada in 2000, using the USA as a control. Findings We found a statistically significant reduction in smoking rates after the adoption of GWLs in Canada in comparison with the USA. Our analyses show that implementation of GWLs in Canada reduced smoking rates by 2.87–4.68 percentage points, a relative reduction of 12.1–19.6%; 33–53 times larger than FDA’s estimates of a 0.088 percentage point reduction. We also demonstrated that FDA’s estimate of the impact was flawed because it is highly sensitive to the changes in variable selection, model specification, and the time period analysed. Conclusions Adopting GWLs on cigarette packages reduces smoking prevalence. Applying our analysis of the Canadian GWLs, we estimate that if the USA had adopted GWLs in 2012, the number of adult smokers in the USA would have decreased by 5.3–8.6 million in 2013. Our analysis demonstrates that FDA’s approach to estimating the impact of GWLs on smoking rates is flawed. Rectifying these problems before this approach becomes the norm is critical for FDA’s effective regulation of tobacco products.

The impact of price and tobacco control policies on the demand for electronic nicotine delivery systems

Background While much is known about the demand for conventional cigarettes, little is known about the determinants of demand for electronic nicotine delivery systems (ENDS or e-cigarettes). The goal of this study is to estimate the own and cross-price elasticity of demand for e-cigarettes and to examine the impact of cigarette prices and smoke-free policies on e-cigarette sales. Methods Quarterly e-cigarette prices and sales and conventional cigarette prices from 2009 to 2012 were constructed from commercial retail store scanner data from 52 US markets, for food, drug and mass stores, and from 25 markets, for convenience stores. Fixed-effects models were used to estimate the own and cross-price elasticity of demand for e-cigarettes and associations between e-cigarette sales and cigarette prices and smoke-free policies. Results Estimated own price elasticities for disposable e-cigarettes centred around −1.2, while those for reusable e-cigarettes were approximately −1.9. Disposable e-cigarette sales were higher in markets where reusable e-cigarette prices were higher and where less of the population was covered by a comprehensive smoke-free policy. There were no consistent and statistically significant relationships between cigarette prices and e-cigarette sales. Conclusions E-cigarette sales are very responsive to own price changes. Disposable e-cigarettes appear to be substitutes for reusable e-cigarettes. Policies increasing e-cigarette retail prices, such as limiting rebates, discounts and coupons and imposing a tax on e-cigarettes, could potentially lead to significant reductions in e-cigarette sales. Differential tax policies based on product type could lead to substitution between different types of e-cigarettes.

Rapidly increasing promotional expenditures for e-cigarettes

Awareness and use of e-cigarettes have increased rapidly, and the products now represent a billion-dollar industry in the USA.1 ,2 Public health concerns about e-cigarettes centre on their potential appeal to the youth market,3 limited scientific evidence regarding their impact on individual and population health,4 and inconsistent product standards, including variations in nicotine content within and across brands.5–7 While some US cities have extended public smoking bans to cover e-cigarettes or taken other restrictive measures,8 ,9 the products remain unregulated at the federal level. Globally, there is significant variation in how products are treated, with some countries including Canada and Australia taking a more restrictive approach.10 A recent proliferation of e-cigarette marketing—including ads in media where traditional tobacco advertising has long been prohibited, such as television1—likely plays a key role in the exponential growth of the products’ popularity. With some exceptions,11 ,12 reports of e-cigarette marketing to-date have been mainly anecdotal; surveillance and tracking of the quantity and content of such marketing is much needed. The goal of this Industry …

100 Million Views of Electronic Cigarette YouTube Videos and Counting: Quantification, Content Evaluation, and Engagement Levels of Videos.

Background The video-sharing website, YouTube, has become an important avenue for product marketing, including tobacco products. It may also serve as an important medium for promoting electronic cigarettes, which have rapidly increased in popularity and are heavily marketed online. While a few studies have examined a limited subset of tobacco-related videos on YouTube, none has explored e-cigarette videos’ overall presence on the platform. Objective To quantify e-cigarette-related videos on YouTube, assess their content, and characterize levels of engagement with those videos. Understanding promotion and discussion of e-cigarettes on YouTube may help clarify the platform’s impact on consumer attitudes and behaviors and inform regulations. Methods Using an automated crawling procedure and keyword rules, e-cigarette-related videos posted on YouTube and their associated metadata were collected between July 1, 2012, and June 30, 2013. Metadata were analyzed to describe posting and viewing time trends, number of views, comments, and ratings. Metadata were content coded for mentions of health, safety, smoking cessation, promotional offers, Web addresses, product types, top-selling brands, or names of celebrity endorsers. Results As of June 30, 2013, approximately 28,000 videos related to e-cigarettes were captured. Videos were posted by approximately 10,000 unique YouTube accounts, viewed more than 100 million times, rated over 380,000 times, and commented on more than 280,000 times. More than 2200 new videos were being uploaded every month by June 2013. The top 1% of most-viewed videos accounted for 44% of total views. Text fields for the majority of videos mentioned websites (70.11%); many referenced health (13.63%), safety (10.12%), smoking cessation (9.22%), or top e-cigarette brands (33.39%). The number of e-cigarette-related YouTube videos was projected to exceed 65,000 by the end of 2014, with approximately 190 million views. Conclusions YouTube is a major information-sharing platform for electronic cigarettes. YouTube appears to be used unevenly for promotional purposes by e-cigarette brands, and our analyses indicated a high level of user engagement with a small subset of content. There is evidence that YouTube videos promote e-cigarettes as cigarette smoking cessation tools. Presence and reach of e-cigarette videos on YouTube warrants attention from public health professionals and policymakers.

Electronic Cigarettes among Priority Populations: Role of Smoking Cessation and Tobacco Control Policies

INTRODUCTION The electronic cigarette (e-cigarette) market has evolved rapidly in recent years, with exploding growth in brands and product types; however, e-cigarette use among priority (sexual minority and low-income) populations and its relationship with smoking-cessation and tobacco control policies have yet to be fully characterized. METHODS The authors conducted a nationally representative online survey of 17,522 U.S. adults in 2013. Participants were drawn from GfKs KnowledgePanel. Logistic regression models were used to analyze relationships between e-cigarettes (awareness, ever use, current use) and cigarette smoking and cessation behaviors, tobacco control policies, and demographics. Analyses were conducted in 2014. RESULTS Approximately 15% of participants reported ever use of e-cigarettes, 5.1% reported current use, and 34.5% of ever users reported current use. E-cigarette awareness was lower among women, minorities, and those with low education. Ever and current use of e-cigarettes was higher among current cigarette smokers, young adults, and those with low SES; both ever use and current use were correlated with current cigarette smoking status, particularly when combined with quit intentions or attempts. Lesbian/gay/bisexual/transgender respondents had higher rates of ever use and current use. Ever use was lower in states with comprehensive smoking bans. No significant relationship between cigarette price and e-cigarette use was detected. CONCLUSIONS Ongoing surveillance of e-cigarette use among subpopulation groups and monitoring their use for combustible cigarette cessation are needed. Important variations in the patterns and correlates of e-cigarette awareness and use exist among priority populations. These findings have implications for future e-cigarette policy decisions.

Differential Impact of Tobacco Control Policies on Youth Sub-Populations

Background: While previous studies have demonstrated the efficacy of tobacco control interventions in reducing tobacco use among youth overall, there have been very few studies that examine the potential differential impact of tobacco control policies on various youth subgroups, defined by socio-economic status (SES), race/ethnicity, and gender. Objective: We examined the relationship between state-level cigarette prices and smoke-free air laws and youth smoking prevalence and intensity for various youth sub-populations in the United States. Methods: We estimated a 2-part model of cigarette demand using data from the 1991 through 2010 nationally representative surveys of 8th-, 10th-, and 12th-grade students as part of the Monitoring the Future project. Findings: We found that real cigarette prices are strong determinants of youth smoking. Blacks, females, Hispanics, and low-SES subpopulations are found to have a larger price response with respect to smoking prevalence than the full sample. Smoke-free air laws are found to have a negative effect on smoking prevalence for the full sample and for the male, white, and high-SES sub-populations. Conclusions: This research concludes that higher cigarette prices will reduce smoking prevalence rates of Blacks, Hispanics, females, and low-SES subpopulations faster than the overall youth population and other youth sub-populations. Moreover, this research concludes that smoke-free air laws will reduce smoking prevalence for the overall youth population with the largest reductions in high SES and male subpopulations.

Garbage in, Garbage Out: Data Collection, Quality Assessment and Reporting Standards for Social Media Data Use in Health Research, Infodemiology and Digital Disease Detection

Background Social media have transformed the communications landscape. People increasingly obtain news and health information online and via social media. Social media platforms also serve as novel sources of rich observational data for health research (including infodemiology, infoveillance, and digital disease detection detection). While the number of studies using social data is growing rapidly, very few of these studies transparently outline their methods for collecting, filtering, and reporting those data. Keywords and search filters applied to social data form the lens through which researchers may observe what and how people communicate about a given topic. Without a properly focused lens, research conclusions may be biased or misleading. Standards of reporting data sources and quality are needed so that data scientists and consumers of social media research can evaluate and compare methods and findings across studies. Objective We aimed to develop and apply a framework of social media data collection and quality assessment and to propose a reporting standard, which researchers and reviewers may use to evaluate and compare the quality of social data across studies. Methods We propose a conceptual framework consisting of three major steps in collecting social media data: develop, apply, and validate search filters. This framework is based on two criteria: retrieval precision (how much of retrieved data is relevant) and retrieval recall (how much of the relevant data is retrieved). We then discuss two conditions that estimation of retrieval precision and recall rely on—accurate human coding and full data collection—and how to calculate these statistics in cases that deviate from the two ideal conditions. We then apply the framework on a real-world example using approximately 4 million tobacco-related tweets collected from the Twitter firehose. Results We developed and applied a search filter to retrieve e-cigarette–related tweets from the archive based on three keyword categories: devices, brands, and behavior. The search filter retrieved 82,205 e-cigarette–related tweets from the archive and was validated. Retrieval precision was calculated above 95% in all cases. Retrieval recall was 86% assuming ideal conditions (no human coding errors and full data collection), 75% when unretrieved messages could not be archived, 86% assuming no false negative errors by coders, and 93% allowing both false negative and false positive errors by human coders. Conclusions This paper sets forth a conceptual framework for the filtering and quality evaluation of social data that addresses several common challenges and moves toward establishing a standard of reporting social data. Researchers should clearly delineate data sources, how data were accessed and collected, and the search filter building process and how retrieval precision and recall were calculated. The proposed framework can be adapted to other public social media platforms.