Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2015 Sep;5(3):335-46.
doi: 10.1007/s13142-015-0324-1.

Building new computational models to support health behavior change and maintenance: new opportunities in behavioral research

Donna Spruijt-Metz  1 , Eric Hekler  2 , Niilo Saranummi  3 , Stephen Intille  4 , Ilkka Korhonen  5 , Wendy Nilsen  6 , Daniel E Rivera  2 , Bonnie Spring  7 , Susan Michie  8 , David A Asch  9 , Alberto Sanna  10 , Vicente Traver Salcedo  11 , Rita Kukakfa  12 , Misha Pavel  3
Affiliations

Building new computational models to support health behavior change and maintenance: new opportunities in behavioral research

Donna Spruijt-Metz et al. Transl Behav Med. 2015 Sep.

Abstract

Adverse and suboptimal health behaviors and habits are responsible for approximately 40 % of preventable deaths, in addition to their unfavorable effects on quality of life and economics. Our current understanding of human behavior is largely based on static "snapshots" of human behavior, rather than ongoing, dynamic feedback loops of behavior in response to ever-changing biological, social, personal, and environmental states. This paper first discusses how new technologies (i.e., mobile sensors, smartphones, ubiquitous computing, and cloud-enabled processing/computing) and emerging systems modeling techniques enable the development of new, dynamic, and empirical models of human behavior that could facilitate just-in-time adaptive, scalable interventions. The paper then describes concrete steps to the creation of robust dynamic mathematical models of behavior including: (1) establishing "gold standard" measures, (2) the creation of a behavioral ontology for shared language and understanding tools that both enable dynamic theorizing across disciplines, (3) the development of data sharing resources, and (4) facilitating improved sharing of mathematical models and tools to support rapid aggregation of the models. We conclude with the discussion of what might be incorporated into a "knowledge commons," which could help to bring together these disparate activities into a unified system and structure for organizing knowledge about behavior.

Keywords: Computational models of behavior; Connected health; Health-related behavior; Just-in-time adaptive interventions; Mobile health; Real-time interventions; mHealth.

PubMed Disclaimer

Figures

Fig. 1
Fig. 1
Faster to slower processes, adapted from [40]
Fig. 2
Fig. 2
Fluid analogy of social cognitive theory, adapted from [60]
Fig. 3
Fig. 3
Timescale separate model that builds on SCT fluid analogy
See this image and copyright information in PMC

References

    1. Schroeder SA. Shattuck lecture. We can do better—improving the health of the American people. New England Journal of Medicine. 2007;357(12):1221–1228. doi: 10.1056/NEJMsa073350. - DOI - PubMed
    1. Mokdad AH, et al. Correction: actual causes of death in the United States, 2000. JAMA. 2005;293(3):293–298. - PubMed
    1. Mokdad AH, et al. Actual causes of death in the United States, 2000. JAMA, The Journal of the American Medical Association. 2004;291(10):1238–1245. doi: 10.1001/jama.291.10.1238. - DOI - PubMed
    1. Keeney RL. Personal decisions are the leading cause of death, in Operations Research. 2008. p. 1335 + .
    1. Waters E, et al. Interventions for preventing obesity in children. Cochrane Database of Systematic Reviews. 2011 - PubMed