Translational Behavioral Medicine: Practice, Policy, Research
Call for Papers for Special Issue on Smartphones, Sensors, and Social Networks
Submission Deadline November 15, 2012
Editors of the Special Section:
Sherry Pagoto, PhD, University of Massachusetts Medical School
Gary Bennett, PhD, Duke University
Traditional health behavior change interventions have long been limited by high expense, patient burden, and poor adherence. As health professionals, our access to intervene upon patients’ behavior is constrained by current models of health care which limit care provision to face-to-face visits provided on a weekly schedule or less frequently. Limited access to patients limits our ability to gain an accurate understanding of the antecedents and consequences of behavior, and to intervene in the moments when patients most need help.
Computing technology including mobile phones, sensors, and online social networks – by being available in real time – are being explored as ways to enhance our ability to understand health behavior and more effectively intervene upon it. mHealth, the application of mobile technology to health, has reached its tipping point. A rapidly growing body of research evidence demonstrates the efficacy of mHealth approaches across a wide range of conditions, populations, and settings. mHealth has also attracted a parallel explosion of industry attention.
An extremely diverse group of companies are capitalizing on the mHealth market, which is projected to reach $23 billion in revenues by 2017. Sensing technologies are also rapidly being developed to gather behavioral, physiological, and contextual data that can then be used to predict behavior or deliver “just-in-time” interventions. Finally, online social networking, a service that allows individuals to interact and communicate with other users without geographical, physical, or logistical barriers has now been used for health surveillance, disseminating information and innovations, and health behavior intervention. The potential of these technologies to impact health behavior change has yet to be fully realized. The purpose of this special issue is to draw papers from academicians, clinicians, and industry professionals who are developing, testing, and/or researching the efficacy of these technologies for health behavior change.
Given that opportunities for academic-industry communication and collaboration have been too infrequent, we have seen relatively limited translation of evidence-based mHealth approaches into the real-world settings that are largely served by industry. We suspect that collaboration between industry and the research community might accelerate the growth of the mHealth market and improve the health of patients and populations.
There are important barriers to such collaborations which we hope are explored and discussed further in this special issue. We hope to attract high quality contributions relating to the opportunities and challenges associated with stimulating academic-industry partnerships and creating evidence-based technology-based approaches to health behavior change. We acknowledge differences in the type of data that is collected by academics and industry professionals and aim to be a forum for both types of data, while acknowledging the strengths and limitations of each. Traditional research reports are sought, but also case studies characterizing real world translation efforts, implementation challenges, and academic-industry partnerships are strongly encouraged.
Additionally, synopses of practical tools and strategies, applications, and approaches are of interest. Selected manuscripts will be published together with commentaries in this special section of Translational Behavioral Medicine.
Abstract submission to before November 15 is highly encouraged.