Technologies to Measure and Modify Physical Activity and Eating Environments

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Context

The explosion of technologic advances in information capture and delivery offers unparalleled opportunities to assess and modify built and social environments in ways that can positively impact health behaviors. This paper highlights some potentially transformative current and emerging trends in the technology arena applicable to environmental context−based assessment and intervention relevant to physical activity and dietary behaviors.

Evidence acquisition

A team of experts convened in 2013 to discuss the main issues related to technology use in assessing and changing built environments for health behaviors particularly relevant to obesity prevention. Each expert was assigned a specific domain to describe, commensurate with their research and expertise in the field, along with examples of specific applications. This activity was accompanied by selective examination of published literature to cover the main issues and elucidate relevant applications of technologic tools and innovations in this field.

Evidence synthesis

Decisions concerning which technology examples to highlight were reached through discussion and consensus-building among the team of experts. Two levels of impact are highlighted: the “me” domain, which primarily targets measurement and intervention activities aimed at individual-level behaviors and their surrounding environments; and the “we” domain, which generally focuses on aggregated data aimed at groups and larger population segments and locales.

Conclusions

The paper ends with a set of challenges and opportunities for significantly advancing the field. Key areas for progress include data collection and expansion, managing technologic considerations, and working across sectors to maximize the population potential of behavioral health technologies.

Introduction

The advent of the personal computer, mobile communication devices, and related electronic innovations has heralded previously unheard of opportunities for impacting personal and population health. Among such technologic advances are the assessment, integration, and interpretation of massive amounts of diverse information about individuals (e.g., capture of real-time physiologic responses across a range of biological systems), as well as the environment (e.g., geographic information system [GIS] and global positioning system [GPS]). Complementing these advances have been innovations in communication media that have substantively changed the ways in which people live, work, and play.

Technologic innovation has left virtually no scientific domain untouched, including the health behavior arena. For more than a decade, technologic innovations have contributed to understanding and improving eating and activity behaviors and the social and built environmental determinants that shape them.1

The purpose of this paper is to highlight current and emerging trends in health behavior−relevant built environment assessment and intervention, with an emphasis on applications to active living and healthy eating. A team of experts was convened in 2013 for this purpose. Although this article is not exhaustive and is a selective examination of published literature, it covers a number of the major technologic developments that are being applied in studying and improving built and social environments related to eating and activity. In this context, environment is conceptualized broadly as “the circumstances, objects, or conditions by which one is surrounded … as well as the aggregate of social and cultural conditions that influence the life of an individual or community” (Merriam-Webster Dictionary, www.m-w.com).

Two general levels of impact are highlighted: the “me” domain, which targets measurement and intervention activities aimed primarily at individual-level behaviors and their surrounding environments; and the “we” domain, which incorporates aggregated data aimed at groups and larger population segments and locales.2 These two domains, although not mutually exclusive, have grown out of different traditions and objectives. The article ends with challenges and opportunities concerning the most promising avenues for harnessing technology to promote potentially paradigm-shifting science in the obesity prevention and health behavior−environmental arenas.

Section snippets

The “Me” Domain: Person-Level Contexts and Behaviors

The “me” domain, rooted in the “Quantified Self” movement and similar consumer- or patient-driven self-awareness practices,3 captures individuals’ personal contexts and perceptions of their behaviors, health, and environments, typically in what can approximate real time. The increasing availability of smartphones and other mobile and wearable health- and behavior-related devices provides many opportunities for assessing a broad range of behaviors, health statuses, social interactions, and the

Targeting the “Me” Domain

Despite an explosion of mobile apps aimed at individual health promotion and disease management,46 relatively few have been evaluated systematically for scientific accuracy, efficacy, and long-term behavioral maintenance and use (examples in “me” and “we” domains shown in Table 1). Reviews of apps aimed at physical activity and dietary change indicate that, although promising for their wide reach, customized messages, and continuity, rigorous evaluation of the sustained effectiveness of such

Other Emerging Technologies in the Field

Given that the current article was not meant to be an exhaustive review, other emerging technology platforms with potential to significantly shape the health behavior and obesity prevention fields could not be discussed in detail. Among the types of potentially transformative technology platforms that await further development and testing are Google Glass, Apple’s Healthbook, and Android Wear. These represent just a few of the innovative technologies that hold promise for changing the ways in

Acknowledgments

The work on this paper was supported in part by Public Health Service Grant No. R01HL109222 (King) and National Science Foundation grant No. IIS1237174 (Patrick). This work was also supported by Grant No. 2010-85215-20659 from the Agriculture and Food Research Initiative of the U.S. Department of Agriculture, National Institute of Food and Agriculture. These funding groups had no role in any aspect of this manuscript. The authors gratefully acknowledge the contributions of Amy Hillier, PhD in

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