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A Novel Control Engineering Approach to Designing and Optimizing Adaptive Sequential Behavioral Interventions

Abstract Control engineering offers a systematic and efficient approach to optimizing the effectiveness of individually tailored treatment and prevention policies, also known as adaptive or ``just-in-time'' behavioral interventions. These types of interventions represent promising strategies for addressing many significant public health concerns. This dissertation explores the development of decision algorithms for adaptive sequential behavioral interventions using dynamical systems modeling, control engineering principles and formal optimization methods. A novel gestational weight gain (GWG) intervention involving multiple intervention components and featuring a pre-defined, clinically relevant set of sequence rules serves as an excellent e... (more)
Created Date 2014
Contributor Dong, Yuwen (Author) / Rivera, Daniel E (Advisor) / Dai, Lenore (Committee member) / Forzani, Erica (Committee member) / Rege, Kaushal (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Subject Chemical engineering / Behavioral sciences / Adaptive Intervention / Control Engineering / Dynamical Systems Modeling / Gestational Weight Gain / Model Predictive Control / Sequential Decision Making
Type Doctoral Dissertation
Extent 255 pages
Language English
Reuse Permissions All Rights Reserved
Note Doctoral Dissertation Chemical Engineering 2014
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis