American Spirit Pack Descriptors and Perceptions of Harm: A Crowdsourced Comparison of Modified Packs.

INTRODUCTION: In 2015, the Food and Drug Administration issued warnings to three tobacco manufacturers who label their cigarettes as "additive-free" and/or "natural" on the grounds that they make unauthorized reduced risk claims. The goal of this study was to examine US adults' perceptions of three American Spirit (AS) pack descriptors ("Made with Organic Tobacco," "100% Additive-Free," and "100% US Grown Tobacco") to assess if they communicate reduced risk. METHODS: In September 2012, three cross-sectional surveys were posted on Amazon Mechanical Turk. Adult participants evaluated the relative harm of a Marlboro Red pack versus three different AS packs with the descriptors "Made with Organic Tobacco," "100% Additive-Free," or "100% US Grown Tobacco" (Survey 1; n = 461); a Marlboro Red pack versus these AS packs modified to exclude descriptors (Survey 2; n = 857); and unmodified versus modified AS pack images (Survey 3; n = 1001). RESULTS: The majority of Survey 1 participants rated the unmodified AS packs as less harmful than the Marlboro Red pack; 35.4%-58.8% of Survey 2 participants also rated the modified (no claims) packs as less harmful than Marlboro Red. In these surveys, prior use of AS cigarettes was associated with reduced perceptions of risk (adjusted odds ratio [AOR] 1.59-2.40). "Made with Organic Tobacco" and "100% Additive-Free" were associated with reduced perceptions of risk when comparing the modified versus the unmodified AS packs (Survey 3). CONCLUSIONS: Data suggest that these AS pack descriptors communicate reduced harm messages to consumers. Findings have implications for regulatory actions related to product labeling and packaging. IMPLICATIONS: These findings provide additional evidence that the "Made with Organic Tobacco," "100% Additive-Free," and "100% US Grown" descriptors, as well as other aspects of the AS pack design, communicate reduced harm to non-, current, and former smokers. Additionally, they provide support for the importance of FDA's 2015 warning to Santa Fe Natural Tobacco Company on "100% Additive Free" as an unauthorized modified risk claim.

Implementation of a Multimodal Mobile System for Point-of-Sale Surveillance: Lessons Learned From Case Studies in Washington, DC, and New York City.

BACKGROUND: In tobacco control and other fields, point-of-sale surveillance of the retail environment is critical for understanding industry marketing of products and informing public health practice. Innovations in mobile technology can improve existing, paper-based surveillance methods, yet few studies describe in detail how to operationalize the use of technology in public health surveillance. OBJECTIVE: The aims of this paper are to share implementation strategies and lessons learned from 2 tobacco, point-of-sale surveillance projects to inform and prepare public health researchers and practitioners to implement new mobile technologies in retail point-of-sale surveillance systems. METHODS: From 2011 to 2013, 2 point-of-sale surveillance pilot projects were conducted in Washington, DC, and New York, New York, to capture information about the tobacco retail environment and test the feasibility of a multimodal mobile data collection system, which included capabilities for audio or video recording data, electronic photographs, electronic location data, and a centralized back-end server and dashboard. We established a preimplementation field testing process for both projects, which involved a series of rapid and iterative tests to inform decisions and establish protocols around key components of the project. RESULTS: Important components of field testing included choosing a mobile phone that met project criteria, establishing an efficient workflow and accessible user interfaces for each component of the system, training and providing technical support to fieldworkers, and developing processes to integrate data from multiple sources into back-end systems that can be utilized in real-time. CONCLUSIONS: A well-planned implementation process is critical for successful use and performance of multimodal mobile surveillance systems. Guidelines for implementation include (1) the need to establish and allow time for an iterative testing framework for resolving technical and logistical challenges; (2) developing a streamlined workflow and user-friendly interfaces for data collection; (3) allowing for ongoing communication, feedback, and technology-related skill-building among all staff; and (4) supporting infrastructure for back-end data systems. Although mobile technologies are evolving rapidly, lessons learned from these case studies are essential for ensuring that the many benefits of new mobile systems for rapid point-of-sale surveillance are fully realized.

National Enforcement of the FSPTCA at Point-of-Sale.

Objective: To describe patterns in the enforcement of the US Food and Drug Administration's current compliance check program. Methods: Data on retail violation rates (RVR) resulting from compliance checks were analyzed. Novel methods were developed to quantify violations and unify data on retail location and violation type. Results: As of July 2013, 42 states and 3 US territories conducted compliance checks. Ninety-six percent of warning letters and 100% of Civil Monetary Penalties addressed sales to minors. RVRs varied significantly over time (OR = 1.15) and between states (ICC = 0.18). Conclusions: The compliance checks database makes it possible to examine how retail enforcement is unfolding over time and place. Results reveal an emphasis on youth access violations, presenting opportunities for research on regulations designed to reduce youth access.

Cameras for Public Health Surveillance: A Methods Protocol for Crowdsourced Annotation of Point-of-Sale Photographs.

BACKGROUND: Photographs are an effective way to collect detailed and objective information about the environment, particularly for public health surveillance. However, accurately and reliably annotating (ie, extracting information from) photographs remains difficult, a critical bottleneck inhibiting the use of photographs for systematic surveillance. The advent of distributed human computation (ie, crowdsourcing) platforms represents a veritable breakthrough, making it possible for the first time to accurately, quickly, and repeatedly annotate photos at relatively low cost. OBJECTIVE: This paper describes a methods protocol, using photographs from point-of-sale surveillance studies in the field of tobacco control to demonstrate the development and testing of custom-built tools that can greatly enhance the quality of crowdsourced annotation. METHODS: Enhancing the quality of crowdsourced photo annotation requires a number of approaches and tools. The crowdsourced photo annotation process is greatly simplified by decomposing the overall process into smaller tasks, which improves accuracy and speed and enables adaptive processing, in which irrelevant data is filtered out and more difficult targets receive increased scrutiny. Additionally, zoom tools enable users to see details within photographs and crop tools highlight where within an image a specific object of interest is found, generating a set of photographs that answer specific questions. Beyond such tools, optimizing the number of raters (ie, crowd size) for accuracy and reliability is an important facet of crowdsourced photo annotation. This can be determined in a systematic manner based on the difficulty of the task and the desired level of accuracy, using receiver operating characteristic (ROC) analyses. Usability tests of the zoom and crop tool suggest that these tools significantly improve annotation accuracy. The tests asked raters to extract data from photographs, not for the purposes of assessing the quality of that data, but rather to assess the usefulness of the tool. The proportion of individuals accurately identifying the presence of a specific advertisement was higher when provided with pictures of the product's logo and an example of the ad, and even higher when also provided the zoom tool (χ(2) 2=155.7, P<.001). Similarly, when provided cropped images, a significantly greater proportion of respondents accurately identified the presence of cigarette product ads (χ(2) 1=75.14, P<.001), as well as reported being able to read prices (χ(2) 2=227.6, P<.001). Comparing the results of crowdsourced photo-only assessments to traditional field survey data, an excellent level of correspondence was found, with area under the ROC curves produced by sensitivity analyses averaging over 0.95, requiring on average 10 to 15 crowdsourced raters to achieve values of over 0.90. RESULTS: Further testing and improvement of these tools and processes is currently underway. This includes conducting systematic evaluations that crowdsource photograph annotation and methodically assess the quality of raters' work. CONCLUSIONS: Overall, the combination of crowdsourcing technologies with tiered data flow and tools that enhance annotation quality represents a breakthrough solution to the problem of photograph annotation, vastly expanding opportunities for the use of photographs rich in public health and other data on a scale previously unimaginable.