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Translational Behavioral Medicine
Erschienen in: Translational Behavioral Medicine 3/2015

01.09.2015 | Essay

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

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

Erschienen in: Translational Behavioral Medicine | Ausgabe 3/2015

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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.
Fußnoten
1
It is important to note the difference in what is being described as a model. The term “theory” has been defined variously across various disciplines, but is defined here as a formalized set of concepts that organize observations and inferences, and is meant to predict phenomena (41. Graziano, A. and M. Raulin, Research is a process of inquiry. Research methods: a process of inquiry, 4th Edition. Allyn & Bacon, Needham Heights, MA, 2000: p. 28–53. The term “model”, on the other hand, has been used by different disciplines to mean different things. There are conceptual models, conceived of as proposed causal linkages between a set of concepts believed to be related to a specific outcome (42. Eime, R.M., et al., A systematic review of the psychological and social benefits of participation in sport for children and adolescents: informing development of a conceptual model of health through sport. Int J Behav Nutr Phys Act, 2013. 10: p. 98.which is very similar to the definition of theory given here. There are statistical models, such as Structural Equation Models, a family of multivariate statistical techniques that incorporate factor analysis and path analysis (43. Weston, R. and P.A. Gore, A brief guide to structural equation modeling. The Counseling Psychologist, 2006. 34(5): p. 719–751. This paper proposes the development of computational models of behavior.
 
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Metadaten
Titel
Building new computational models to support health behavior change and maintenance: new opportunities in behavioral research
verfasst von
Donna Spruijt-Metz, MFA, PhD
Eric Hekler, PhD
Niilo Saranummi, PhD
Stephen Intille, PhD
Ilkka Korhonen, PhD
Wendy Nilsen, PhD
Daniel E. Rivera, PhD
Bonnie Spring, PhD
Susan Michie, PhD
David A. Asch, PhD
Alberto Sanna, PhD
Vicente Traver Salcedo, PhD
Rita Kukakfa, PhD
Misha Pavel, PhD
Publikationsdatum
01.09.2015
Verlag
Springer US
Erschienen in
Translational Behavioral Medicine / Ausgabe 3/2015
Print ISSN: 1869-6716
Elektronische ISSN: 1613-9860
DOI
https://doi.org/10.1007/s13142-015-0324-1

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