Computer technologies have created ever-expanding opportunities to assess and deliver health information to individuals, groups, and populations (i.e., electronic health or eHealth). Information technologies are being developed and used to specifically examine cancer-related health behaviors and states. Mobile phones and other portable health information technologies, in particular, offer unprecedented opportunities to improve the health of the U.S. population and reach traditionally underserved subgroups (i.e. mobile health or mHealth). At the Health Behavior Research Branch (HBRB), we encourage the development and scientific evaluation of information technologies related to physical activity, diet, obesity/energy balance, and sun protective behaviors. In addition, the development and advancement of related research methodologies (e.g., real-time data capture, geospatial analysis of global positioning system tools, etc.) is encouraged. The primary goals of HBRB’s focus on eHealth/mHealth research are to 1) improve the reliability, validity, and usability of health behavior assessment tools; 2) encourage the development of technologies that can produce positive health behavior change; and 3) facilitate the understanding of mechanisms related to health behaviors and cancer using innovative information technologies.
Reports & Publications
American Journal of Preventive Medicine (May 2007, Volume 32, Issue 5, Supplement, Pages 71-138). Supplement: Critical Issues in eHealth Research.
American Journal of Preventive Medicine (January 2010, Volume 38, Issue 1, Pages 85-109). Special Issue: eHealth Research and Patient-Centered Care: Examining Theory, Methods, and Application
The Science of Real-Time Data Capture – edited book
Discusses the state of the science of real-time data capture and its application to health and cancer research. It provides a conceptual framework for ecological momentary assessments (EMA) and discusses health-related topics where ecological momentary assessments have been applied. In addition, future directions in real-time data capture assessment, interventions, methodology, and technology are discussed.
Mâsse, LC, Wilson, M, & Baranowski, T (Eds.) (2006). Item Response Modeling in Health Education and Health Behavior Research. Health Education Research, Vol. 21, Suppl. 1