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Cited by 3Advanced Control Systems OptimizationSubstance Abuse Treatment and OutcomesBehavioral Health and Interventions

A Risk-based Model Predictive Control Approach to Adaptive Interventions in Behavioral Health

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Zafra-Cabeza, Ascension, Rivera, Daniel E., Collins, Linda M., Ridao, Miguel A., Camacho, Eduardo F.·2006·Proceedings of the 45th IEEE Conference on Decision and Control
DOI 10.1109/cdc.2006.377686
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Abstract

This paper demonstrates how control systems engineering and risk management can be applied to problems in behavioral health through their application to the design and implementation of adaptive interventions. Adaptive interventions represent a promising approach to prevention and treatment of chronic, relapsing disorders, such as alcoholism, cigarette smoking, and drug abuse. The benefits of the proposed approach are presented in the development of risk-based model predictive control (MPC) algorithm for a hypothetical intervention inspired by two real-life programs: Fast Track, an intervention whose long-term goal is the prevention of conduct disorders in at-risk children, and Communities that Care, a risk-based prevention program for substance abuse. The tailoring or controlled variable of the adaptive intervention is a measure of parental functioning in the family of an at-risk child; the MPC-based algorithm decides on the appropriate frequency of counselor home visits, mentoring sessions, and the availability of after-school recreation activities by relying on a model that includes identifiable risks, their costs, and the cost/benefit assessment of mitigating actions. By systematically accounting for risks and adapting treatment components over time, an MPC approach as described in this paper has the potential to increase intervention potency and adherence while reducing waste, resulting in more effective interventions than conventional fixed treatment. MPC is particularly meaningful for the problem given some of its favorable properties, such as ease of constraint-handling, and its ability to scale to interventions involving multiple tailoring variables. Several simulations are conducted under conditions of varying disturbance magnitude to demonstrate the effectiveness of the algorithm

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  • Recent methodological work on adaptive interventions includes development of the SMART Trial and exploration of applying engineering control algorithms to adaptive behavioral interventions.

    “Recent methodological work on building and optimizing adaptive interventions has included development of the Sequential Multiple Assignment Randomized Trial (SMART Trial) (58) and exploration of the idea of applying control algorithms from engineering to adaptive behavioral interventions to improve their performance (38, 39).”

    From The Multiphase Optimization Strategy for Engineering Effective Tobacco Use Interventions (2011) · cites this paper as [39]

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Authors
Zafra-Cabeza, A., Rivera, D. E., Collins, L. M., Ridao, M. A., & Camacho, E. F.
Affiliations
  • Arizona State University (US)
  • Pennsylvania State University (US)
  • Universidad de Sevilla (ES)
ORCID
Venue
Proceedings of the 45th IEEE Conference on Decision and Control
Publisher
IEEE
Published
2006
Pages
673-678
ISSN
0191-2216 (ISSN-L)
DOI
10.1109/cdc.2006.377686
OpenAlex
W2070761144
Cited by
3
References
28
Citations by year
2022: 1
FWCI
0.53
Type
conference paper
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • IEEE Conference on Decision and Control (CDC) (publishedVersion)
  • LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by-nc-nd)
  • Deposito de Investigacion Universidad de Sevilla (University of Seville) (submittedVersion, cc-by-nc-nd)
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Optimization
  • Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
  • Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
Keywords
model predictive control, adaptive interventions, behavioral health, risk management, risk-based control, Fast Track program, Communities That Care, substance use prevention, parental functioning, vulnerable children, intervention tailoring, alcoholism, smoking, drug abuse

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