DocumentCode :
185096
Title :
A dynamical systems model of Social Cognitive Theory
Author :
Martin, Cesar A. ; Rivera, Daniel E. ; Riley, William T. ; Hekler, Eric B. ; Buman, Matthew P. ; Adams, Marc A. ; King, Abby C.
Author_Institution :
Control Syst. Eng. Lab. (CSEL), Arizona State Univ., Tempe, AZ, USA
fYear :
2014
fDate :
4-6 June 2014
Firstpage :
2407
Lastpage :
2412
Abstract :
Social Cognitive Theory (SCT) is among the most influential theories of health behavior and has been used as the conceptual basis of interventions for smoking cessation, weight management, and other related health outcomes. SCT and other related theories were developed primarily to explain differences between individuals, but explanatory theories of within-person behavioral variability are increasingly needed to support new technology-driven interventions that can adapt over time for each person. This paper describes a dynamical system model of SCT using a fluid analogy scheme. A series of simulations were performed to explore and better understand SCT. The model incorporates a nonlinear feature called habituation, an important feature of behavioral response resulting from continuous stimulus. It also illustrates how control systems engineering principles provide a promising approach for advancing health behavior theory development, and for guiding the design of more potent and efficient effective interventions.
Keywords :
cognition; health care; SCT; behavioral response; continuous stimulus; control systems engineering principles; dynamical system model; dynamical systems model; explanatory theory; fluid analogy scheme; habituation; health behavior theory development; nonlinear feature; smoking cessation; social cognitive theory; technology-driven intervention; weight management; within-person behavioral variability; Adaptation models; Context; Control systems; Data models; Educational institutions; Mathematical model; Biomedical; Emerging control applications; Modeling and simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
ISSN :
0743-1619
Print_ISBN :
978-1-4799-3272-6
Type :
conf
DOI :
10.1109/ACC.2014.6859463
Filename :
6859463
Link To Document :
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