This paper is in the following e-collection/theme issue:

Surveillance Systems (466) Mobile Health (mhealth) (2982) mHealth for Data Collection and Research (981) Smoking Cessation (566) Prevention and Health Promotion (1015) GIS (Geographic Information Systems) Applications in Public Health and Spatial Epidemiology (113)

Published on in Vol 1, No 2 (2015): Jul-Dec

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

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

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

Authors of this article:

Jennifer Cantrell1, 2 Author Orcid Image ;   Ollie Ganz1, 3 Author Orcid Image ;   Vinu Ilakkuvan1, 3 Author Orcid Image ;   Michael Tacelosky4 Author Orcid Image ;   Jennifer Kreslake2 Author Orcid Image ;   Joyce Moon-Howard5 Author Orcid Image ;   Angela Aidala6 Author Orcid Image ;   Donna Vallone1, 5 Author Orcid Image ;   Andrew Anesetti-Rothermel7 Author Orcid Image ;   Thomas R. Kirchner2, 5, 8 Author Orcid Image
Article Authors Cited by (10) Tweetations (2) Metrics

Journals

  1. Kirchner T, Shiffman S. Spatio-temporal determinants of mental health and well-being: advances in geographically-explicit ecological momentary assessment (GEMA). Social Psychiatry and Psychiatric Epidemiology 2016;51(9):1211 View
  2. Bertz J, Epstein D, Preston K. Combining ecological momentary assessment with objective, ambulatory measures of behavior and physiology in substance-use research. Addictive Behaviors 2018;83:5 View
  3. McIntosh S, Pérez-Ramos J, Demment M, Vélez Vega C, Avendaño E, Ossip D, Dye T. Development and Implementation of Culturally Tailored Offline Mobile Health Surveys. JMIR Public Health and Surveillance 2016;2(1):e28 View
  4. Pedersen E, Firth C, Parker J, Shih R, Davenport S, Rodriguez A, Dunbar M, Kraus L, Tucker J, D'Amico E. Locating Medical and Recreational Cannabis Outlets for Research Purposes: Online Methods and Observational Study. Journal of Medical Internet Research 2020;22(2):e16853 View
  5. Kirchner T, Gao H, Lewis D, Anesetti-Rothermel A, Carlos H, House B. Individual Mobility and Uncertain Geographic Context: Real-time Versus Neighborhood Approximated Exposure to Retail Tobacco Outlets Across the US. Journal of Healthcare Informatics Research 2019;3(1):70 View
  6. English N, Anesetti-Rothermel A, Zhao C, Latterner A, Benson A, Herman P, Emery S, Schneider J, Rose S, Patel M, Schillo B. Image Processing for Public Health Surveillance of Tobacco Point-of-Sale Advertising: Machine Learning–Based Methodology. Journal of Medical Internet Research 2021;23(8):e24408 View
  7. Kirchner T, Guttentag A, Vantu A, Silver D. Documenting the Impact Potential of a Menthol Cigarette Ban at Point-of-Sale: A Photograph-Based Analysis of the Presence and Placement of Menthol Versus Regular Cigarette Packs on the Shelves of Tobacco Retail Outlets in New York City. Nicotine & Tobacco Research 2023;25(1):28 View
  8. Rose S, Anesetti-Rothermel A, Westneat S, van de Venne J, Folger S, Rahman B, Azam T, Zhou Y, Debnam C, Ribisl K, Cohn A. Inequitable Distribution of FTP Marketing by Neighborhood Characteristics: Further Evidence for Targeted Marketing. Nicotine & Tobacco Research 2022;24(4):484 View
  9. Torrens P. Data science for pedestrian and high street retailing as a framework for advancing urban informatics to individual scales. Urban Informatics 2022;1(1) View
  10. Rabiei R, Bastani P, Ahmadi H, Dehghan S, Almasi S. Developing public health surveillance dashboards: a scoping review on the design principles. BMC Public Health 2024;24(1) View