ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at firstname.lastname@example.org.
- 2 English
- 2 Public
- Model Predictive Control
- 2 Behavioral sciences
- 1 Adaptive Intervention
- 1 Chemical engineering
- 1 Control Engineering
- 1 Control Systems Engineering
- 1 Dynamical Systems Modeling
- 1 Electrical engineering
- 1 Emerging Control Applications
- 1 Gestational Weight Gain
- 1 Low physical activity behavioral interventions
- 1 Modeling Human Behavior
- 1 Sequential Decision Making
- 1 System Identification
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 example of a sequential behavioral intervention; it is examined in …
- Dong, Yuwen, Rivera, Daniel E, Dai, Lenore, et al.
- Created Date
Behavioral health problems such as physical inactivity are among the main causes of mortality around the world. Mobile and wireless health (mHealth) interventions offer the opportunity for applying control engineering concepts in behavioral change settings. Social Cognitive Theory (SCT) is among the most influential theories of health behavior and has been used as the conceptual basis of many behavioral interventions. This dissertation examines adaptive behavioral interventions for physical inactivity problems based on SCT using system identification and control engineering principles. First, a dynamical model of SCT using fluid analogies is developed. The model is used throughout the dissertation to evaluate …
- Martin Moreno, Cesar Antonio, Rivera, Daniel E, Hekler, Eric B, et al.
- Created Date