Translational Behavioral Medicine

, Volume 5, Issue 3, pp 335–346 | Cite as

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

  • Donna Spruijt-Metz
  • Eric Hekler
  • Niilo Saranummi
  • Stephen Intille
  • Ilkka Korhonen
  • Wendy Nilsen
  • Daniel E. Rivera
  • Bonnie Spring
  • Susan Michie
  • David A. Asch
  • Alberto Sanna
  • Vicente Traver Salcedo
  • Rita Kukakfa
  • Misha Pavel
Essay

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

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

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Copyright information

© Society of Behavioral Medicine 2015

Authors and Affiliations

  • 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
  1. 1.University of Southern CaliforniaLos AngelesUSA
  2. 2.Arizona State UniversityTempeUSA
  3. 3.VTT Technical Research Centre of FinlandEspooFinland
  4. 4.Northeastern UniversityBostonUSA
  5. 5.Tampere University of TechnologyTampereFinland
  6. 6.National Institutes of HealthBethesdaUSA
  7. 7.Northwestern UniversityEvanstonUSA
  8. 8.University College LondonLondonUK
  9. 9.Wharton School, University of PennsylvaniaPhiladelphiaUSA
  10. 10.Scientific Institute Hospital San RaffaelleMilanoItaly
  11. 11.Valencia Polytechnical UniversityValenciaSpain
  12. 12.Columbia UniversityNew YorkUSA

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