Matthew E. Eggers

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.

Exploring Differences in Youth Perceptions of the Effectiveness of Electronic Cigarette Television Advertisements

INTRODUCTION Studies suggest that exposure to televised electronic cigarette (e-cigarette) advertising contributes to the recent increase in e-cigarette use among youth. This study examines the relationship between perceptions of e-cigarette advertisements and attitudes toward and intentions to use e-cigarettes among youth who had never used e-cigarettes. METHODS In May 2014, we conducted an online survey of 5020 youth aged 13 to 17. Participants were randomly assigned to answer questions about their attitudes toward and intentions to use e-cigarettes before or after viewing e-cigarette advertisements. Perceived effectiveness (PE) of advertisements was measured after ad exposure. Ordinary least squares models were used to assess the relationship between PE and study outcomes. RESULTS Among never e-cigarette users, greater PE was associated with more positive attitudes toward e-cigarettes (b = 0.74, P < .001) and intentions to use e-cigarettes (b = 0.16, P < .001). Findings suggest that PE is predictive of outcomes controlling for study condition, youth demographics, and media use variables. CONCLUSIONS After ad exposure, youth who have never used e-cigarettes previously perceive e-cigarettes as cooler, more fun, healthier, and more enjoyable. Youth who thought the ads were more effective were more likely to have a positive attitude toward e-cigarettes and greater intention to try e-cigarettes in the future. Restricting televised e-cigarette advertising may reduce e-cigarette initiation among youth. IMPLICATIONS Previous studies demonstrate that, among adults, PE is antecedent to actual ad effectiveness across a range of behaviors. To our knowledge, this is the first study to document the relationship between PE and advertising effectiveness among youth. It provides evidence that PE may be a useful tool to quantify the potential influence of advertising on youth-advertising that, in this case, is designed to market a consumer good that may be harmful to youth but that may also be used to develop public health campaigns.

Youth use of electronic vapor products and blunts for administering cannabis

BACKGROUND The positive association between youth use of cannabis and tobacco is well-established, and reports show that some youth are using electronic vapor products (EVPs) to administer cannabis. This study examines the prevalence and correlates of youth consumption of cannabis via EVP and how this compares with co-use of cannabis with cigars (blunts) among a large statewide sample of youth. METHODS We used data from the Florida Youth Tobacco Survey (FYTS), a school-based, pencil-and-paper questionnaire given to Florida middle and high school students (N=12,320). We conducted weighted descriptive analyses and logistic regressions examining prevalence and correlates of EVP/cannabis and blunt use. RESULTS Ever EVP/cannabis use was lower among middle school students (3.4%) than high school students (11.5%). Blunt use was reported by 6.0% of middle school and 24.1% of high school students. Approximately one-third of youth who had ever administered cannabis via either mode reported using both EVP/cannabis and blunts. EVP/cannabis and blunt use were both associated with lower school performance and use of other tobacco products. EVP/cannabis use did not vary by race/ethnicity, but blunt use was higher among black and Hispanic youth than white, non-Hispanic youth. DISCUSSION A substantial percentage of youth in a statewide sample are using EVPs and blunts to administer cannabis, and overlap between these use patterns is common. Differences in the demographic risk profile for EVP/cannabis and blunt use suggest that EVPs may provide a novel route of administration for delivering cannabis that appeals to groups not otherwise susceptible to using cannabis via blunts.

Compliance with a Sales Policy on Flavored Non-cigarette Tobacco Products

Objectives We assessed the effect of the New York City (NYC) policy restricting sales of flavored non-cigarette tobacco products on retail sales using a quasi-experimental comparison design. We also studied possible cross-border purchasing and product substitution by consumers. Methods We compiled retail scanner data for January 2010-January 2014 for NYC, a proximal comparison area (PCA) surrounding NYC, and the US. We used regression models to assess trends in sales of flavored cigars, smokeless tobacco (SLT), loose tobacco (RYO), and total cigars in all areas. Results Sales of flavored cigars (-22.3%), SLT (-97.6%), and RYO (-42.5%) declined following policy implementation (all ps < .01). Flavored cigar sales declined nonsignificantly in the comparison areas. An average 7.4% reduction in total cigar sales was seen in NYC following the policy (p < .01), as cigar sales increased 12% nationally, suggesting that NYC consumers did not substitute flavored cigars with non-flavored varieties. Conclusions Implementation of the NYC policy was associated with significant reductions in sales of all restricted products, both absolutely and relative to comparison areas. Despite persistent sales of flavored cigars, overall cigar sales in NYC declined following the policy, although more intensive enforcement is needed to ensure greater policy compliance.

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.