A system identification approach for improving behavioral interventions based on Social Cognitive Theory

Mobile and wireless health (mHealth) interventions offer the opportunity for applying control engineering and system identification concepts in behavioral change settings. Social Cognitive Theory provides a recognized theoretical framework that can be applied to explain changes in behavior over time. Based on earlier work describing a dynamical model of this theory, a semi-physical system identification approach is developed in this paper for interventions associated with improving physical activity. An initial informative experiment that relies on prior knowledge from similar interventions is first designed to obtain basic insights regarding the dynamics of the system. Based on these results a second, optimized experiment is developed which solves a constrained optimization problem to find the intervention component profiles needed to mirror a desired behavioral pattern and to provide sufficient information that allows a more precise estimation of the parameters. A simulation study is presented to illustrate the design procedure.