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Products found: 154
  • Exposure to state-funded anti-tobacco television advertising since the MSA, 1999-2012

    Oral presentation at the 8th Annual Conference on Health Communication, Marketing, and Media, Atlanta, GA.

  • Field Validation of Secondary Data Sources for Enumerating Retail Tobacco Outlets in a State without Tobacco Outlet Licensing

    Identifying tobacco retail outlets for U.S. FDA compliance checks or calculating tobacco outlet density is difficult in the 13 States without tobacco retail licensing or where licensing lists are unavailable for research. This study uses primary data collection to identify tobacco outlets in three counties in a non-licensing state and validate two commercial secondary data sources. We calculated sensitivity and positive predictive values (PPV) to examine the evidence of validity for two secondary data sources, and conducted a geospatial analysis to determine correct allocation to census tract. ReferenceUSA had almost perfect sensitivity (0.82) while Dun & Bradstreet (D&B) had substantial sensitivity (0.69) for identifying tobacco outlets; combined, sensitivity improved to 0.89. D&B identified fewer "false positives" with a PPV of 0.82 compared to 0.71 for ReferenceUSA. More than 90% of the outlets identified by ReferenceUSA were geocoded to the correct census tract. Combining two commercial data sources resulted in enumeration of nearly 90% of tobacco outlets in a three county area. Commercial databases appear to provide a reasonably accurate way to identify tobacco outlets for enforcement operations and density estimation.

  • Foster Care Smoke-free Home Kit

    A Foster Care Smoke-free Home Kit is available for use to educate foster families about the benefits of a smoke-free home. Please see flier for more information about the Smoke-free Foster Care kit.

  • 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.

  • 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.