Optimized Behavioral Interventions: What Does System Identification and Control Engineering Have to Offer?

@article{Rivera2012OptimizedBI,
  title={Optimized Behavioral Interventions: What Does System Identification and Control Engineering Have to Offer?},
  author={Daniel E. Rivera},
  journal={IFAC Proceedings Volumes},
  year={2012},
  volume={45},
  pages={882-893}
}
  • D. Rivera
  • Published 1 July 2012
  • Psychology
  • IFAC Proceedings Volumes
Abstract The last decade has witnessed an increasing interest in applying systems science concepts for problems in behavioral health, and using these to inform the design, analysis, and implementation of optimized interventions. How can system identification and control engineering impact interventions for chronic, relapsing disorders such as drug abuse, cigarette smoking and obesity? The paper addresses this question by focusing on the problem of time-varying “adaptive” interventions. In an… 
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References

SHOWING 1-10 OF 48 REFERENCES
Using engineering control principles to inform the design of adaptive interventions: a conceptual introduction.
A dynamical systems model for improving gestational weight gain behavioral interventions
TLDR
A dynamical systems model is presented that describes how a behavioral intervention can influence weight gain during pregnancy and how the proper design of the intervention can counteract natural trends towards declines in healthy eating and reduced physical activity during the course of pregnancy.
Health behavior models in the age of mobile interventions: are our theories up to the task?
TLDR
Current theories appear inadequate to inform mobile intervention development as these interventions become more interactive and adaptive, and Dynamic feedback system theories of health behavior can be developed utilizing longitudinal data from mobile devices and control systems engineering models.
An Improved Formulation of Hybrid Model Predictive Control With Application to Production-Inventory Systems
TLDR
Improved model predictive control for linear hybrid systems described by mixed logical dynamical (MLD) models is considered, demonstrating that MPC for hybrid systems can be tuned for desired performance under demanding conditions involving noise and uncertainty.
A control engineering approach for designing an optimized treatment plan for fibromyalgia
TLDR
An approach to develop dynamical models and subsequently, hybrid model predictive control schemes for assigning optimal dosages of naltrexone as treatment for a chronic pain condition known as fibromyalgia is presented.
Model-on-Demand predictive control for nonlinear hybrid systems with application to adaptive behavioral interventions
TLDR
The proposed algorithm applies Model-on-Demand (MoD) estimation to generate a local linear approximation of the nonlinear hybrid system at each time step, using a small subset of data selected by an adaptive bandwidth selector.
A Conceptual Framework for Adaptive Preventive Interventions
TLDR
A conceptual framework for adaptive interventions is offered, principles underlying the design and evaluation of such interventions are discussed, and some areas where additional research is needed are reviewed.
Ecological momentary assessment.
TLDR
Ecological momentary assessment holds unique promise to advance the science and practice of clinical psychology by shedding light on the dynamics of behavior in real-world settings.
A dynamical model for describing behavioural interventions for weight loss and body composition change
TLDR
The model consists of a three-compartment energy balance integrated with a mechanistic psychological model inspired by the Theory of Planned Behaviour that describes how important variables in a behavioural intervention can influence healthy eating habits and increased physical activity over time.
Towards Patient-Friendly Input Signal Design for Optimized Pain Treatment Interventions
Abstract We examine some of the challenges associated with generating input signals for identifying dynamics in pain treatment interventions while imposing “patient-friendly” constraints on the
...
1
2
3
4
5
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