The Pace of Technologic Change: Implications for Digital Health Behavior Intervention Research
Section snippets
The Technologic Infrastructure for Health Is Changing
Digital technologies are increasingly pervasive in all aspects of daily life and the ease with which digital tools are adopted is in part because of the malleability and adaptability of digital technologies. The Internet and Web Architectures that underlie this digital revolution are fundamentally minimalistic and modular and allow for decentralized growth based on minimal commonality. Mobile and wireless technologies, including cellular systems, embedded cameras, smartphones, and the Internet
These Changes Support the Ability to Handle Highly Complex, Multilayered Issues in Health
Concurrent with advances in information technology are three major trends in public health and medicine:
- 1
the emergence of chronic diseases as the main causes of poor health, disability, and death;
- 2
an increased understanding of the multiple influences on health, including the genome, microbiome, health behaviors, social influences, and the environment; and
- 3
collaborative, self, and social health management.
The combination of these poses both an unprecedented challenge to traditional health care and
Health Behavior Research: New Data, Research Designs, and Methods
Technologic advances now illuminate what has been long theorized about behavior, that it is influenced at multiple levels—genetic, biological, social, environmental—and that these influences are reciprocal, dynamic, and temporally based.43, 44 Thus, the complexity of understanding behavior strains current scientific methods and processes—something that is labeled “data poor.” A data-poor science requires researchers first to specify the questions, design the study to answer these questions, and
Conclusions
This is a time of three major trends: increasing capabilities inherent in communication, computing, and data science; unsustainable growth in the complexity and cost of health care; and a movement to a more user-centered and collaborative approach to health promotion and health care. As outlined in this paper, the first and third trends can be leveraged to help address the second if public health is open to incorporating models of research and practice that are already being used in other
Acknowledgments
This 2016 theme section of the American Journal of Preventive Medicine is supported by funding from the NIH Office of Behavioral and Social Sciences Research (OBSSR) to support the dissemination of research on digital health interventions, methods, and implications for preventive medicine.
This paper is one of the outputs of two workshops, one supported by the Medical Research Council (MRC)/National Institute for Health Research (NIHR) Methodology Research Program (PI Susan Michie), the OBSSR
References (78)
- et al.
The Internet of Things: a survey
Comput Networks
(2010) - et al.
A content analysis of popular smartphone apps for smoking cessation
Am J Prev Med
(2013) - et al.
Mobile health technology evaluation: the mHealth evidence workshop
Am J Prev Med
(2013) - et al.
A smart mirror to promote a healthy lifestyle
Biosyst Eng
(2015) - et al.
A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010
Lancet
(2012) - et al.
Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010
Lancet
(2012) - et al.
Prevention of chronic disease in the 21st century: elimination of the leading preventable causes of premature death and disability in the USA
Lancet (London, England)
(2014) - et al.
Energy-balance studies reveal associations between gut microbes, caloric load, and nutrient absorption in humans
Am J Clin Nutr
(2011) - et al.
Using engineering control principles to inform the design of adaptive interventions: a conceptual introduction
Drug Alcohol Depend
(2007) - et al.
Mobile and wireless technologies in health behavior and the potential for intensively adaptive interventions
Curr Opin Psychol
(2015)
A randomized controlled trial on the role of support in Internet-based problem solving therapy for depression and anxiety
Behav Res Ther
Automated interventions for multiple health behaviors using conversational agents
Patient Educ Couns
Continuous evaluation of evolving behavioral intervention technologies
Am J Prev Med
mHealth App Developer Economics
Mobile Health Market Report 2013-2017
Weight loss—there is an app for that! But does it adhere to evidence-informed practices?
Transl Behav Med
Apps of steel: are exercise apps providing consumers with realistic expectations?: a content analysis of exercise apps for presence of behavior change theory
Health Educ Behav
Smartphones for smarter delivery of mental health programs: a systematic review
J Med Internet Res
Mobile health: revolutionizing healthcare through transdisciplinary research
Computer (Long Beach Calif)
Social Physics: How Good Ideas Spread: The Lessons From a New Science
small data, where n = me
Commun ACM
Realizing effective behavioral management of health: the metamorphosis of behavioral science methods
IEEE Pulse
Green paper on Citizen Science for Europe: towards a society of empowered citizens and enhanced research
Socientize Consort
Behavioral functionality of mobile apps in health interventions: a systematic review of the literature
JMIR mHealth uHealth
The law of attrition
J Med Internet Res
Understanding and promoting engagement with digital behavior change interventions
Am J Prev Med
Designing and undertaking a health economics study of digital health interventions
Am J Prev Med
Evaluating digital health interventions: key questions and approaches
Am J Prev Med
Developing and refining models and theories suitable for digital health interventions
Am J Prev Med
Recent trends in chronic disease, impairment and disability among older adults in the United States
BMC Geriatr
Prescription Drug Use Among Midlife and Older Americans
Best Care at Lower Cost: The Path to Continuously Learning Health Care in America - Institute of Medicine
Despite substantial progress in EHR adoption, health information exchange and patient engagement remain low in office settings
Health Aff (Millwood)
National health expenditure projections, 2013-23: faster growth expected with expanded coverage and improving economy
Health Aff (Millwood)
Objective vs. self-reported physical activity and sedentary time: effects of measurement method on relationships with risk biomarkers
PLoS One
The human microbiome project
Nature
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This article is part of a theme section titled Digital Health: Leveraging New Technologies to Develop, Deploy, and Evaluate Behavior Change Interventions.