JUUL's 2019 Removal of Mint-Flavored Pods and Changes to the Retail Environment of Electronic Nicotine Delivery Systems in Florida and the United States.

INTRODUCTION: The increase in youth electronic nicotine delivery system (ENDS) use coincided with JUUL's rapid rise, which prompted investigations and lawsuits aimed at this leading brand. In response, JUUL discontinued sweet flavors in late 2018, followed by mint flavors in November 2019. We assessed ENDS sales and prices at both the state and national level before and after JUUL's removal of mint flavors. AIMS AND METHODS: Nielsen retail sales data on ENDS products from convenience and food stores in 4-week aggregates were analyzed between January 2019 and January 2020 in Florida and the United States. Standardized units were created. Unit market share and growth rates were calculated for top brands and flavors in the periods before and after JUUL's mint removal. Average prices within brand and product type were calculated. RESULTS: Following JUUL's removal of mint in November 2019, JUUL's market share dropped from over 66% in Florida and the United States to 37.1% (Florida) and 55.1% (United States). In January 2020, the second leading brands were Puff Bar (15.0%) in Florida and Vuse (18.1%) in the United States. Mint market share decreased and share of all other flavor categories increased, particularly menthol and concept. Total ENDS sales increased in Florida but decreased in the United States. Average prices of ENDS devices decreased. CONCLUSIONS: While JUUL's actions led to a decline in its sales, Puff Bar emerged and menthol and concept flavors experienced growth. Findings also demonstrate how changes by influential brands differentially affect purchase patterns at the national and state level. IMPLICATIONS: These findings support the growing body of evidence that tobacco industry self-regulation, with selective flavor removal by the leading ENDS brand in this case, is insufficient to reduce total ENDS sales, including sales of flavored products which are preferred by youth. Results suggest that brand and flavor substitution compensated for the removal of mint JUUL pods. Understanding changes to the ENDS market in response to industry actions, at both the state and national level, can inform future regulation and interventions. These findings can also inform efforts to prevent and reduce youth ENDS use.

Identifying Electronic Nicotine Delivery System Brands and Flavors on Instagram: Natural Language Processing Analysis.

BACKGROUND: Electronic nicotine delivery system (ENDS) brands, such as JUUL, used social media as a key component of their marketing strategy, which led to massive sales growth from 2015 to 2018. During this time, ENDS use rapidly increased among youths and young adults, with flavored products being particularly popular among these groups. OBJECTIVE: The aim of our study is to develop a named entity recognition (NER) model to identify potential emerging vaping brands and flavors from Instagram post text. NER is a natural language processing task for identifying specific types of words (entities) in text based on the characteristics of the entity and surrounding words. METHODS: NER models were trained on a labeled data set of 2272 Instagram posts coded for ENDS brands and flavors. We compared three types of NER models-conditional random fields, a residual convolutional neural network, and a fine-tuned distilled bidirectional encoder representations from transformers (FTDB) network-to identify brands and flavors in Instagram posts with key model outcomes of precision, recall, and F1 scores. We used data from Nielsen scanner sales and Wikipedia to create benchmark dictionaries to determine whether brands from established ENDS brand and flavor lists were mentioned in the Instagram posts in our sample. To prevent overfitting, we performed 5-fold cross-validation and reported the mean and SD of the model validation metrics across the folds. RESULTS: For brands, the residual convolutional neural network exhibited the highest mean precision (0.797, SD 0.084), and the FTDB exhibited the highest mean recall (0.869, SD 0.103). For flavors, the FTDB exhibited both the highest mean precision (0.860, SD 0.055) and recall (0.801, SD 0.091). All NER models outperformed the benchmark brand and flavor dictionary look-ups on mean precision, recall, and F1. Comparing between the benchmark brand lists, the larger Wikipedia list outperformed the Nielsen list in both precision and recall. CONCLUSIONS: Our findings suggest that NER models correctly identified ENDS brands and flavors in Instagram posts at rates competitive with, or better than, others in the published literature. Brands identified during manual annotation showed little overlap with those in Nielsen scanner data, suggesting that NER models may capture emerging brands with limited sales and distribution. NER models address the challenges of manual brand identification and can be used to support future infodemiology and infoveillance studies. Brands identified on social media should be cross-validated with Nielsen and other data sources to differentiate emerging brands that have become established from those with limited sales and distribution.

An Experimental Study of Nicotine Warning Statements in E-cigarette Tweets.

INTRODUCTION: It is unclear whether warnings on electronic cigarette (e-cigarette) advertisements required by the US Food and Drug Administration (FDA) will apply to social media. Given the key role of social media in marketing e-cigarettes, we seek to inform FDA decision making by exploring how warnings on various tweet content influence perceived healthiness, nicotine harm, likelihood to try e-cigarettes, and warning recall. METHODS: In this 2 × 4 between-subjects experiment participants viewed a tweet from a fictitious e-cigarette brand. Four tweet content versions (e-cigarette product, e-cigarette use, e-cigarette in social context, unrelated content) were crossed with two warning versions (absent, present). Adult e-cigarette users (N = 994) were recruited via social media ads to complete a survey and randomized to view one of eight tweets. Multivariable regressions explored effects of tweet content and warning on perceived healthiness, perceived harm, and likelihood to try e-cigarettes, and tweet content on warning recall. Covariates were tobacco and social media use and demographics. RESULTS: Tweets with warnings elicited more negative health perceptions of the e-cigarette brand than tweets without warnings (p < .05). Tweets featuring e-cigarette products (p < .05) or use (p < .001) elicited higher warning recall than tweets featuring unrelated content. CONCLUSIONS: This is the first study to examine warning effects on perceptions of e-cigarette social media marketing. Warnings led to more negative e-cigarette health perceptions, but no effect on perceived nicotine harm or likelihood to try e-cigarettes. There were differences in warning recall by tweet content. Research should explore how varying warning content (text, size, placement) on tweets from e-cigarette brands influences health risk perceptions. IMPLICATIONS: FDA's 2016 ruling requires warnings on advertisements for nicotine-containing e-cigarettes, but does not specify whether this applies to social media. This study is the first to examine how e-cigarette warnings in tweets influence perceived healthiness and harm of e-cigarettes, which is important because e-cigarette brands are voluntarily including warnings on Twitter and Instagram. Warnings influenced perceived healthiness of the e-cigarette brand, but not perceived nicotine harm or likelihood to try e-cigarettes. We also saw higher recall of warning statements for tweets featuring e-cigarettes. Findings suggest that expanding warning requirements to e-cigarette social media marketing warrants further exploration and FDA consideration.

Effect of menthol cigarette and other menthol tobacco product bans on tobacco purchases in the RTI iShoppe virtual convenience store.

OBJECTIVE: To test how a potential US ban of menthol products or replacement with 'green' products and ads could influence tobacco purchases. METHODS: US adult menthol smokers (N=1197) were recruited via an online panel and randomly assigned to complete a shopping task in one of four versions (experimental conditions) of the RTI iShoppe virtual store: (1) no ban, (2) replacement of menthol cigarettes and ads with green replacement versions, (3) menthol cigarette ban and (4) all menthol tobacco product ban. Logistic regressions assessed the effect of condition on tobacco purchases. RESULTS: Participants in the menthol cigarette ban (OR=0.67, 95% CI 0.48 to 0.92) and all menthol product ban conditions (OR=0.60, 95% CI 0.43 to 0.83) were less likely to purchase cigarettes of any type than participants in the no ban condition. Participants in the green replacement (OR=1.74, 95% CI 1.13 to 2.70), menthol cigarette ban (OR=3.40, 95% CI 2.14 to 5.41) and all menthol product ban conditions (OR=3.14, 95% CI 1.97 to 5.01) were more likely to purchase a cigarette brand different from their usual brand than participants in the no ban condition. CONCLUSIONS: Our findings suggest that menthol bans could have great public health impact by reducing cigarette purchases. However, tobacco marketing strategies, such as creating green (or other replacement) versions of menthol cigarettes, may undermine public health benefits of a menthol ban by prompting purchases of non-menthol cigarettes. Our findings highlight the importance of taking tobacco marketing tactics into consideration in tobacco product regulation.

Antismoking Advertisements and Price Promotions and Their Association With the Urge to Smoke and Purchases in a Virtual Convenience Store: Randomized Experiment.

BACKGROUND: Point of sale (POS) advertising is associated with smoking initiation, current smoking, and relapse among former smokers. Price promotion bans and antismoking advertisements (ads) are 2 possible interventions for combating POS advertising. OBJECTIVE: The purpose of this analysis was to determine the influence of antismoking ads and promotions on urges to smoke and tobacco purchases. METHODS: This analysis examined exposure to graphic (graphic images depicting physical consequences of tobacco use) and supportive (pictures of and supportive messages from former smokers) antismoking ads and promotions in a virtual convenience store as predictors of urge to smoke and buying tobacco products among 1200 current cigarette smokers and 800 recent quitters recruited via a Web-based panel (analytical n=1970). We constructed linear regression models for urge to smoke and logistic regression models for the odds of purchasing tobacco products, stratified by smoking status. RESULTS: The only significant finding was a significant negative relationship between exposure to supportive antismoking ads and urge to smoke among current smokers (beta coefficient=-5.04, 95% CI -9.85 to -0.22; P=.04). There was no significant relationship between graphic antismoking ads and urge to smoke among current smokers (coefficient=-3.77, 95% CI -8.56 to 1.02; P=.12). Neither relationship was significant for recent quitters (graphic: coefficient=-3.42, 95% CI -8.65 to 1.81; P=.15 or supportive: coefficient=-3.82, 95% CI -8.99 to 1.36; P=.20). There were no significant differences in urge to smoke by exposure to promotions for current smokers (coefficient=-1.06, 95% CI -4.53 to 2.41; P=.55) or recent quitters (coefficient=1.76, 95% CI -2.07 to 5.59; P=.37). There were also no differences in tobacco purchases by exposure to graphic (current smokers: coefficient=0.93, 95% CI 0.67 to 1.29; P=.66 and recent quitters: coefficient=0.73, 95% CI 0.44 to 1.19; P=.20) or supportive (current smokers: coefficient=1.05, 95% CI 0.75 to 1.46; P=.78 and recent quitters: coefficient=0.73, 95% CI 0.45 to 1.18; P=.20) antismoking ads or price promotions (current smokers: coefficient=1.09, 95% CI 0.86 to 1.38; P=.49 and recent quitters: coefficient=0.90, 95% CI 0.62 to 1.31; P=.60). CONCLUSIONS: The results of this analysis support future research on the ability of supportive antismoking ads to reduce urges to smoke among current cigarette smokers. Research on urges to smoke has important tobacco control implications, given the relationship between urge to smoke and smoking cigarettes, time to next smoke, and amount smoked.

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.

Antismoking Ads at the Point of Sale: The Influence of Ad Type and Context on Ad Reactions.

Efforts are underway to educate consumers about the dangers of smoking at the point of sale (POS). Research is limited about the efficacy of POS antismoking ads to guide campaign development. This study experimentally tests whether the type of antismoking ad and the context in which ads are viewed influence people's reactions to the ads. A national convenience sample of 7,812 adult current smokers and recent quitters was randomized to 1 of 39 conditions. Participants viewed one of the four types of antismoking ads (negative health consequences-graphic, negative social consequences-intended emotive, benefits of quitting-informational, benefits of quitting-graphic) in one of the three contexts (alone, next to a cigarette ad, POS tobacco display). We assessed participants' reactions to the ads, including perceived effectiveness, negative emotion, affective dissonance, and motivational reaction. Graphic ads elicited more negative emotion and affective dissonance than benefits of quitting ads. Graphic ads elicited higher perceived effectiveness and more affective dissonance than intended emotive ads. Antismoking ads fared best when viewed alone, and graphic ads were least influenced by the context in which they were viewed. These results suggest that in developing POS campaigns, it is important to consider the competitive pro-tobacco context in which antismoking ads will be viewed.

Quantifying how smokers value attributes of electronic cigarettes.

INTRODUCTION: Rates of electronic cigarette (e-cigarette) use have increased quickly among US adults (3.3% in 2010 to 8.5% in 2013) and youth (4.5% in 2013 to 13.4% in 2014). As state and local governments consider regulatory policies, understanding what smokers believe about e-cigarettes and how they value e-cigarettes is important. METHODS: Using data from a convenience sample of Florida adult smokers (N=765), we investigated the value smokers place on specific attributes of e-cigarettes (availability of flavours, effectiveness of e-cigarettes as a cessation aid, healthier alternative to regular cigarettes, ability to use e-cigarettes in public places) by asking smokers how much they would be willing to pay for e-cigarettes with and without each of these attributes. RESULTS: For cigarette-only and dual users, losing the ability to use an e-cigarette as a quit aid and losing the harm reduction of an e-cigarette significantly reduced the price respondents were willing to pay for an e-cigarette. For cigarette-only users, not being able to use an e-cigarette indoors and losing flavours also significantly reduced the price respondents were willing to pay for an e-cigarette. CONCLUSION: Our results suggest that smokers value multiple attributes of e-cigarettes. Our valuation measures also appear to align with smokers' beliefs about e-cigarettes.

Identifying e-cigarette vape stores: description of an online search methodology.

BACKGROUND: Although the overall impact of Electronic Nicotine Delivery Systems (ENDS) on public health is unclear, awareness, use, and marketing of the products have increased markedly in recent years. Identifying the increasing number of 'vape stores' that specialise in selling ENDS can be challenging given the lack of regulatory policies and licensing. This study assesses the utility of online search methods in identifying ENDS vape stores. METHODS: We conducted online searches in Google Maps, Yelp, and YellowPages to identify listings of ENDS vape stores in Florida, and used a crowdsourcing platform to call and verify stores that primarily sold ENDS to consumers. We compared store listings generated from the online search and crowdsourcing methodology to list licensed tobacco and ENDS retailers from the Florida Department of Business and Professional Regulation. RESULTS: The combined results from all three online sources yielded a total of 403 ENDS vape stores. Nearly 32.5% of these stores were on the state tobacco licensure list, while 67.5% were not. Accuracy of online results was highest for Yelp (77.6%), followed by YellowPages (77.1%) and Google (53.0%). CONCLUSIONS: Using the online search methodology we identified more ENDS vape stores than were on the state tobacco licensure list. This approach may be a promising strategy to identify and track the growth of ENDS vape stores over time, especially in states without a systematic licensing requirement for such stores.

Comparing Twitter and Online Panels for Survey Recruitment of E-Cigarette Users and Smokers.

BACKGROUND: E-cigarettes have rapidly increased in popularity in recent years, driven, at least in part, by marketing and word-of-mouth discussion on Twitter. Given the rapid proliferation of e-cigarettes, researchers need timely quantitative data from e-cigarette users and smokers who may see e-cigarettes as a cessation tool. Twitter provides an ideal platform for recruiting e-cigarette users and smokers who use Twitter. Online panels offer a second method of accessing this population, but they have been criticized for recruiting too few young adults, among whom e-cigarette use rates are highest. OBJECTIVE: This study compares effectiveness of recruiting Twitter users who are e-cigarette users and smokers who have never used e-cigarettes via Twitter to online panelists provided by Qualtrics and explores how users recruited differ by demographics, e-cigarette use, and social media use. METHODS: Participants were adults who had ever used e-cigarettes (n=278; male: 57.6%, 160/278; age: mean 34.26, SD 14.16 years) and smokers (n=102; male: 38.2%, 39/102; age: mean 42.80, SD 14.16 years) with public Twitter profiles. Participants were recruited via online panel (n=190) or promoted tweets using keyword targeting for e-cigarette users (n=190). Predictor variables were demographics (age, gender, education, race/ethnicity), e-cigarette use (eg, past 30-day e-cigarette use, e-cigarette puffs per day), social media use behaviors (eg, Twitter use frequency), and days to final survey completion from survey launch for Twitter versus panel. Recruitment method (Twitter, panel) was the dependent variable. RESULTS: Across the total sample, participants were recruited more quickly via Twitter (incidence rate ratio=1.30, P=.02) than panel. Compared with young adult e-cigarette users (age 18-24 years), e-cigarette users aged 25 to 34 years (OR 0.01, 95% CI 0.00-0.60, P=.03) and 35 to 44 years (OR 0.01, 95% CI 0.00-0.51, P=.02) were more likely to be recruited via Twitter than panel. Smokers aged 35 to 44 years were less likely than those aged 18 to 24 years to be recruited via Twitter than panel (35-44: OR 0.03, 95% CI 0.00-0.49, P=.01). E-cigarette users who reported a greater number of e-cigarette puffs per day were more likely to be recruited via Twitter than panel compared to those who reported fewer puffs per day (OR 1.12, 95% CI 1.05-1.20, P=.001). With each one-unit increase in Twitter usage, e-cigarette users were 9.55 times (95% CI 2.28-40.00, P=.002) and smokers were 4.91 times (95% CI 1.90-12.74, P=.001) as likely to be recruited via Twitter than panel. CONCLUSIONS: Twitter ads were more time efficient than an online panel in recruiting e-cigarette users and smokers. In addition, Twitter provided access to younger adults, who were heavier users of e-cigarettes and Twitter. Recruiting via social media and online panel in combination offered access to a more diverse population of participants.

Does Digital Ad Exposure Influence Information-Seeking Behavior Online? Evidence From the 2012 Tips From Former Smokers National Tobacco Prevention Campaign.

BACKGROUND: Measuring the impact of online health campaigns is challenging. Ad click-through rates are traditionally used to measure campaign reach, but few Internet users ever click on ads. Alternatively, self-reported exposure to digital ads would be prone to recall bias. Furthermore, there may be latency effects whereby people do not click on ads when exposed but visit the promoted website or conduct campaign-related searches later. Online panels that unobtrusively collect panelists' Web behavior data and link ad exposure to website visits and searches can more reliably assess the impact of digital ad exposure. From March to June 2012, the Centers for Disease Control and Prevention aired the national Tips From Former Smokers (Tips 2012) media campaign designed to encourage current smokers to quit. Advertisements ran across media channels, and the digital ads directed users to the Tips 2012 campaign website. OBJECTIVE: Our aim was to examine whether exposure to Tips 2012 digital ads influenced information-seeking behaviors online. METHODS: ComScore mined its panelists' Web behavior data for unique codes that would indicate exposure to Tips 2012 ads, regardless of whether panelists clicked the ad or not. A total of 15,319 US adults were identified as having been exposed to a Tips 2012 campaign ad. An equal number of unexposed adults (N=15,319) were identified and matched on demographics and Internet use behavior to the exposed group. Panelists' Web behavior data were mined for up to 4 weeks after initial Tips 2012 ad exposure to determine whether they visited the Tips 2012 campaign website or other cessation-related websites (eg, nicotine replacement therapy site) or conducted searches for campaign-related topics (eg, quit smoking). RESULTS: The proportion of exposed adults visiting the Tips 2012 sites increased from 0.4% in Week 1 to 0.9% 4 weeks after ad exposure, and these rates were significantly higher than in the unexposed group (0.1% in Week 1 to 0.4% in Week 4, P<.001) across all weeks examined. The proportion of exposed panelists visiting other cessation websites increased from 0.2% in Week 1 to 0.3% 4 weeks after initial ad exposure, and these rates were significantly higher than in the unexposed group (0.0% in Week 1 to 0.2% in Week 4, P=.001 to P=.019) across all weeks examined. There were no significant differences in searches for campaign-related topics between the exposed and unexposed group during most of the weeks examined. CONCLUSIONS: These results suggest that online ad exposure is associated with confirmed visits to the Tips 2012 campaign sites and visits to other cessation websites and that these information-seeking behaviors occur up to several weeks after ad exposure. Web behavior data from online panels are useful for examining exposure and behavioral responses to digital campaign ads.

Does Digital Video Advertising Increase Population-Level Reach of Multimedia Campaigns? Evidence From the 2013 Tips From Former Smokers Campaign.

BACKGROUND: Federal and state public health agencies in the United States are increasingly using digital advertising and social media to promote messages from broader multimedia campaigns. However, little evidence exists on population-level campaign awareness and relative cost efficiencies of digital advertising in the context of a comprehensive public health education campaign. OBJECTIVE: Our objective was to compare the impact of increased doses of digital video and television advertising from the 2013 Tips From Former Smokers (Tips) campaign on overall campaign awareness at the population level. We also compared the relative cost efficiencies across these media platforms. METHODS: We used data from a large national online survey of approximately 15,000 US smokers conducted in 2013 immediately after the conclusion of the 2013 Tips campaign. These data were used to compare the effects of variation in media dose of digital video and television advertising on population-level awareness of the Tips campaign. We implemented higher doses of digital video among selected media markets and randomly selected other markets to receive similar higher doses of television ads. Multivariate logistic regressions estimated the odds of overall campaign awareness via digital or television format as a function of higher-dose media in each market area. All statistical tests used the .05 threshold for statistical significance and the .10 level for marginal nonsignificance. We used adjusted advertising costs for the additional doses of digital and television advertising to compare the cost efficiencies of digital and television advertising on the basis of costs per percentage point of population awareness generated. RESULTS: Higher-dose digital video advertising was associated with 94% increased odds of awareness of any ad online relative to standard-dose markets (P<.001). Higher-dose digital advertising was associated with a marginally nonsignificant increase (46%) in overall campaign awareness regardless of media format (P=.09). Higher-dose television advertising was associated with 81% increased odds of overall ad awareness regardless of media format (P<.001). Increased doses of television advertising were also associated with significantly higher odds of awareness of any ad on television (P<.001) and online (P=.04). The adjusted cost of each additional percentage point of population-level reach generated by higher doses of advertising was approximately US $440,000 for digital advertising and US $1 million for television advertising. CONCLUSIONS: Television advertising generated relatively higher levels of overall campaign awareness. However, digital video was relatively more cost efficient for generating awareness. These results suggest that digital video may be used as a cost-efficient complement to traditional advertising modes (eg, television), but digital video should not replace television given the relatively smaller audience size of digital video viewers.

Crowdsourcing data collection of the retail tobacco environment: case study comparing data from crowdsourced workers to trained data collectors.

OBJECTIVE: To assess whether crowdsourcing is a viable option for conducting surveillance of point of sale (POS) tobacco marketing practices. METHODS: We posted jobs to an online crowdsourcing platform to audit 194 Florida licensed tobacco retailers over a 3-week period. During the same period, trained data collectors conducted audits at the same retail locations. Data were collected on cigarette advertising, cigarette promotions and product availability (electronic cigarettes, snus and dissolvables). We compared data collected by crowdsourced workers and trained staff and computed frequencies, percent agreement and inter-rater reliability. Photographs of e-cigarettes and exterior cigarette advertisements submitted by crowdsourced workers were used to validate responses. RESULTS: Inter-rater reliability between crowdsourced and trained data collectors was moderate to high for coding exterior cigarette advertisements, product availability and some tobacco promotions, but poor to fair when coding presence of sales and interior cigarette advertisements. Photos submitted by crowdsourced workers confirmed e-cigarette availability that was missed by trained data collectors in three stores. CONCLUSIONS: Crowdsourcing may be a promising form of data collection for some POS tobacco measures. Future studies should examine the cost-effectiveness of crowdsourcing compared with traditional trained data collectors and assess which POS measures are most amenable to crowdsourcing.

Adult smokers' receptivity to a television advert for electronic nicotine delivery systems.

OBJECTIVE: The aim of the present work was to examine adult smokers' awareness of and receptivity to an electronic nicotine delivery system (ENDS) television advert, and whether viewing the advert influenced urge to smoke and intention to try ENDS. METHODS: A television advert for ENDS brand blu eCigs was shown to an online convenience sample of 519 Florida adult smokers. We measured current smokers' awareness of and receptivity to the advert, and whether seeing the advert influenced their thoughts about smoking or quitting, urge to smoke and intention to try ENDS. Results were stratified by prior ENDS use. RESULTS: Approximately 62.3% of current smokers were aware of the advert. Smokers found the advert informative (73.8%), attention grabbing (67.5%) and innovative (64.5%), with prior ENDS users rating the advert more favourably than non-users. Seeing the advert elicited an urge to smoke (mean 42.1, SD=1.9) and thoughts about smoking cigarettes (75.8%) as well as quitting (74.6%). Prior END users were significantly more likely than non-users to report thinking about smoking cigarettes after seeing the advert (P<0.05). Most smokers said ENDS were 'made for people like them' (88.6%) and they would try ENDS in the future (66.0%). CONCLUSIONS: Smokers are receptive to ENDS television adverts and report intention to try ENDS after viewing the advert. Future studies should monitor ENDS advertising and examine how exposure to ENDS adverts influences smokers' use of ENDS, dual use with cigarettes and cessation behaviour.

Using Twitter Data to Gain Insights into E-cigarette Marketing and Locations of Use: An Infoveillance Study.

BACKGROUND: Marketing and use of electronic cigarettes (e-cigarettes) and other electronic nicotine delivery devices have increased exponentially in recent years fueled, in part, by marketing and word-of-mouth communications via social media platforms, such as Twitter. OBJECTIVE: This study examines Twitter posts about e-cigarettes between 2008 and 2013 to gain insights into (1) marketing trends for selling and promoting e-cigarettes and (2) locations where people use e-cigarettes. METHODS: We used keywords to gather tweets about e-cigarettes between July 1, 2008 and February 28, 2013. A randomly selected subset of tweets was manually coded as advertising (eg, marketing, advertising, sales, promotion) or nonadvertising (eg, individual users, consumers), and classification algorithms were trained to code the remaining data into these 2 categories. A combination of manual coding and natural language processing methods was used to indicate locations where people used e-cigarettes. Additional metadata were used to generate insights about users who tweeted most frequently about e-cigarettes. RESULTS: We identified approximately 1.7 million tweets about e-cigarettes between 2008 and 2013, with the majority of these tweets being advertising (93.43%, 1,559,508/1,669,123). Tweets about e-cigarettes increased more than tenfold between 2009 and 2010, suggesting a rapid increase in the popularity of e-cigarettes and marketing efforts. The Twitter handles tweeting most frequently about e-cigarettes were a mixture of e-cigarette brands, affiliate marketers, and resellers of e-cigarette products. Of the 471 e-cigarette tweets mentioning a specific place, most mentioned e-cigarette use in class (39.1%, 184/471) followed by home/room/bed (12.5%, 59/471), school (12.1%, 57/471), in public (8.7%, 41/471), the bathroom (5.7%, 27/471), and at work (4.5%, 21/471). CONCLUSIONS: Twitter is being used to promote e-cigarettes by different types of entities and the online marketplace is more diverse than offline product offerings and advertising strategies. E-cigarettes are also being used in public places, such as schools, underscoring the need for education and enforcement of policies banning e-cigarette use in public places. Twitter data can provide new insights on e-cigarettes to help inform future research, regulations, surveillance, and enforcement efforts.

Influence of point-of-sale tobacco displays and graphic health warning signs on adults: evidence from a virtual store experimental study.

OBJECTIVES: We tested the impact of banning tobacco displays and posting graphic health warning signs at the point of sale (POS). METHODS: We designed 3 variations of the tobacco product display (open, enclosed [not visible], enclosed with pro-tobacco ads) and 2 variations of the warning sign (present vs absent) with virtual store software. In December 2011 and January 2012, we randomized a national convenience sample of 1216 adult smokers and recent quitters to 1 of 6 store conditions and gave them a shopping task. We tested for the main effects of the enclosed display, the sign, and their interaction on urge to smoke and tobacco purchase attempts. RESULTS: The enclosed display significantly lowered current smokers' (B = -7.05; 95% confidence interval [CI] = -13.20, -0.91; P < .05) and recent quitters' (Β = -6.00, 95% CI = -11.00, -1.00; P < .01) urge to smoke and current smokers' purchase attempts (adjusted odds ratio = 0.06; 95% CI = 0.03, 0.11; P < .01). The warning sign had no significant main effect on study outcomes or interaction with enclosed display. CONCLUSIONS: These data show that POS tobacco displays influence purchase behavior. Banning them may reduce cues to smoke and unplanned tobacco purchases.

Multiple tobacco product use among adults in the United States: cigarettes, cigars, electronic cigarettes, hookah, smokeless tobacco, and snus.

OBJECTIVE: Noncigarette tobacco products are increasingly popular. Researchers need to understand multiple tobacco product use to assess the effects of these products on population health. We estimate national prevalence and examine risk factors for multiple product use. METHOD: We calculated prevalence estimates of current use patterns involving cigarettes, cigars, electronic cigarettes, hookah, smokeless tobacco, and snus using data from the 2012 RTI National Adult Tobacco Survey (N=3627), a random-digit-dial telephone survey of adults aged 18 and over. Associations between use patterns (exclusive single product and multiple products) and demographic characteristics were examined using Pearson chi-square tests and logistic regression. RESULTS: 32.1% of adults currently use 1 or more tobacco products; 14.9% use cigarettes exclusively, and 6.6% use one noncigarette product exclusively, 6.9% use cigarettes with another product (dual use), 1.3% use two noncigarette products, and 2.4% use three or more products (polytobacco use). Smokers who are young adult, male, never married, reside in the West, and made prior quit attempts were at risk for multiple product use. CONCLUSIONS: Over 10% of U.S. adults use multiple tobacco products. A better understanding of multiple product use involving combustible products, like cigars and hookah, is needed. Multiple product use may be associated with past quit attempts.

The use of social media by state tobacco control programs to promote smoking cessation: a cross-sectional study.

BACKGROUND: The promotion of evidence-based cessation services through social media sites may increase their utilization by smokers. Data on social media adoption and use within tobacco control programs (TCPs) have not been reported. OBJECTIVE: This study examines TCP use of and activity levels on social media, the reach of TCP sites, and the level of engagement with the content on sites. METHODS: A cross-sectional descriptive study of state TCP social media sites and their content was conducted. RESULTS: In 2013, 60% (30/50) of TCPs were using social media. Approximately one-quarter (26%, 13/50) of all TCPs used 3 or more social media sites, 24% (12/50) used 2, and 10% (5/50) used 1 site. Overall, 60% (30/50) had a Facebook page, 36% (18/50) had a Twitter page, and 40% (20/50) had a YouTube channel. The reach of social media was different across each site and varied widely by state. Among TCPs with a Facebook page, 73% (22/30) had less than 100 likes per 100,000 adults in the state, and 13% (4/30) had more than 400 likes per 100,000 adults. Among TCPs with a Twitter page, 61% (11/18) had less than 10 followers per 100,000 adults, and just 1 state had more than 100 followers per 100,000 adults. Seven states (23%, 7/30) updated their social media sites daily. The most frequent social media activities focused on the dissemination of information rather than interaction with site users. Social media resources from a national cessation media campaign were promoted infrequently. CONCLUSIONS: The current reach of state TCP social media sites is low and most TCPs are not promoting existing cessation services or capitalizing on social media's interactive potential. TCPs should create an online environment that increases participation and 2-way communication with smokers to promote free cessation services.

Influence of retail cigarette advertising, price promotions, and retailer compliance on youth smoking-related attitudes and behaviors.

CONTEXT: Exposure to retail tobacco marketing is associated with youth smoking, but most studies have relied on self-reported measures of exposure, which are prone to recall bias. OBJECTIVE: To examine whether exposure to retail cigarette advertising, promotions, and retailer compliance is associated with youth smoking-related outcomes using observational estimates of exposure. DESIGN: Data on retail cigarette advertising and promotions were collected from a representative sample of licensed tobacco retailers in New York annually since 2004. County-level estimates of retail cigarette advertising and promotions and retailer compliance with youth access laws were calculated and linked to the New York Youth Tobacco Survey, administered to 54,671 middle and high school students in 2004, 2006, and 2008. Regression models examined whether cigarette advertising, promotions, and retailer compliance were associated with youth's awareness of retail cigarette advertising, attitudes about smoking, susceptibility to smoking, cigarette purchasing behaviors, and smoking behaviors. RESULTS: Living in counties with more retail cigarette advertisements is associated with youth having positive attitudes about smoking (odds ratio [OR] = 1.10, 95% confidence interval [CI] = 1.03-1.19, P < .01). Living in counties with more retail cigarette promotions is associated with youth current smoking (OR = 1.57, 95% CI = 1.01-2.44, P < .05). Living in counties with higher retailer compliance with youth access laws is associated with higher odds of youth being refused cigarettes when attempting to buy in stores (OR = 1.12, 95% CI = 1.01-1.25, P < .05) and lower odds of retail stores being youth's usual source of cigarettes (OR = 0.88, 95% CI = 0.80-0.97, P < .01). CONCLUSIONS: Strong retailer compliance programs and policies that eliminate cigarette advertising and promotions may help reduce youth smoking.

An Investigation of Age-Differentiated Conversations About Electronic Nicotine Delivery Systems on Reddit.

Introduction: This study analyzes age-differentiated Reddit conversations about ENDS. Methods: This study combines 2 methods to (1) predict Reddit users' age into 2 categories (13-20 years [underage] and 21-54 years [of legal age]) using a machine learning algorithm and (2) qualitatively code ENDS-related Reddit posts within the 2 groups. The 25 posts with the highest karma score (number of upvotes minus number of downvotes) for each keyword search (i.e., query) and each predicted age group were qualitatively coded. Results: Of 9, the top 3 topics that emerged were flavor restriction policies, Tobacco 21 policies, and use. Opposition to flavor restriction policies was a prominent subcategory for both groups but was more common in the 21-54 group. The 13-20 group was more likely to discuss opposition to minimum age laws as well as access to flavored ENDS products. The 21-54 group commonly mentioned general vaping use behavior. Conclusions: Users predicted to be in the underage group posted about different ENDS-related topics on Reddit than users predicted to be in the of-legal-age group.