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Products found: 170
  • Four hundred and sixty brands of e-cigarettes and counting: implications for product regulation

    Introduction E-cigarettes are largely unregulated and internet sales are substantial. This study examines how the online market for e-cigarettes has changed over time: in product design and in marketing messages appearing on websites. Methods Comprehensive internet searches of English-language websites from May–August 2012 and December 2013–January 2014 identified brands, models, flavours, nicotine strengths, ingredients and product claims. Brands were divided into older and newer groups (by the two searches) for comparison. Results By January 2014 there were 466 brands (each with its own website) and 7764 unique flavours. In the 17 months between the searches, there was a net increase of 10.5 brands and 242 new flavours per month. Older brands were more likely than newer brands to offer cigalikes (86.9% vs 52.1%, p<0.01), and newer brands more likely to offer the more versatile eGos and mods (75.3% vs 57.8%, p<0.01). Older brands were significantly more likely to claim that they were healthier and cheaper than cigarettes, were good substitutes where smoking was banned and were effective smoking cessation aids. Newer brands offered more flavours per brand (49 vs 32, p<0.01) and were less likely to compare themselves with conventional cigarettes. Conclusions The number of e-cigarette brands is large and has been increasing. Older brands tend to highlight their advantages over conventional cigarettes while newer brands emphasise consumer choice in multiple flavours and product versatility.

  • From "vape" tricks to brand promotion: Assessing YouTube video content related to electronic cigarettes

    SRNT, Chicago, IL, 2016. From "vape" tricks to brand promotion: Assessing YouTube video content related to electronic cigarettes. Paper Session #21, Saturday, March 5.

  • 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. While the number of studies using social data is growing rapidly, few such 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 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: 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 – 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. Next we 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 electronic 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. Discussions: This paper sets forth a conceptual framework for the filtering and quality evaluation of social data that addresses several common challenges, moving 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.

  • HMCollab approach to social data: How digital can inform your campaign and what social media can tell us about tobacco behavior

    Szczypka G (2017, March). HMCollab approach to social data: How digital can inform your campaign and what social media can tell us about tobacco behavior. National Conference on Tobacco or Health, Austin, TX.

  • How do U.S. adults find out about electronic cigarettes? Implications for public health messages.

    Poster presentation at the Society for Research on Nicotine and Tobacco Annual Meeting, Seattle, WA.

  • How does goal orientation impact e-cigarette use?

    Lead author: Jessica Pepper. Oral presentation at the Society of Behavioral Medicine Annual Meeting & Scientific Sessions, San Antonio, TX.

  • How much cigarette tax avoidance is there in the US? Different estimates from smoker surveys and physical pack collection methods

    Surveys consistently reveal a substantially lower rate of cigarette tax avoidance than physical pack collections. We document and compare the avoidance rates from the two methods and explore potential explanations for differences in the findings.

  • How risky are e-cigarettes? Smokers' beliefs about the health risks of multiple tobacco products

    Lead author: Jessica Pepper. Oral presentation at the Society of Behavioral Medicine Annual Meeting & Scientific Sessions, San Antonio, TX.

  • How risky is it to use e-cigarettes? Smokers' beliefs about their health risks from using novel and traditional tobacco products.

    We sought to understand smokers’ perceived likelihood of health problems from using cigarettes and four non-cigarette tobacco products (NCTPs: e-cigarettes, snus, dissolvable tobacco, and smokeless tobacco). A US national sample of 6,607 adult smokers completed an online survey in March 2013. Participants viewed e-cigarette use as less likely to cause lung cancer, oral cancer, or heart disease compared to smoking regular cigarettes (all p < .001). This finding was robust for all demographic groups. Participants viewed using NCTPs other than e-cigarettes as more likely to cause oral cancer than smoking cigarettes but less likely to cause lung cancer. The dramatic increase in e-cigarette use may be due in part to the belief that they are less risky to use than cigarettes, unlike the other NCTPs. Future research should examine trajectories in perceived likelihood of harm from e-cigarette use and whether they affect regular and electronic cigarette use.

  • How U.S. adults describe various tobacco products and marijuana: The successes and failures of tobacco industry marketing and public health

    Poster: Berg, C. J. & Lewis, M. (2014, November). How U.S. adults describe various tobacco products and marijuana: The successes and failures of tobacco industry marketing and public health. Presentation at the 2014 American Public Health Association Annual Meeting. New Orleans, Louisiana.