Development of a Control-Oriented Model of Social Cognitive Theory for Optimized mHealth Behavioral Interventions

Cesar A. Martin, Daniel Rivera, Eric B. Hekler, William T. Riley, Matthew Buman, Marc Adams, Alicia B. Magann

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


Mobile health technologies are contributing to the increasing relevance of control engineering principles in understanding and improving health behaviors, such as physical activity. Social cognitive theory (SCT), one of the most influential theories of health behavior, has been used as the conceptual basis for behavioral interventions for smoking cessation, weight management, and other health-related outcomes. This paper presents a control-oriented dynamical systems model of SCT based on fluid analogies that can be used in system identification and control design problems relevant to the design and analysis of intensively adaptive interventions. Following model development, a series of simulation scenarios illustrating the basic workings of the model are presented. The model's usefulness is demonstrated in the solution of two important practical problems: 1) semiphysical model estimation from data gathered in a physical activity intervention (the Mobile Interventions for Lifestyle Exercise and Eating at Stanford study) and 2) as a means for discerning the range of 'ambitious but doable' daily step goals in a closed-loop behavioral intervention aimed at sedentary adults. The model is the basis for ongoing experimental validation efforts and should encourage additional research in applying control engineering technologies to the social and behavioral sciences.

Original languageEnglish (US)
Article number8532116
Pages (from-to)331-346
Number of pages16
JournalIEEE Transactions on Control Systems Technology
Issue number2
StatePublished - Mar 2020


  • Behavioral interventions
  • control design
  • dynamical modeling
  • health behavior
  • system identification

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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