TY - JOUR
T1 - Using engineering control principles to inform the design of adaptive interventions
T2 - A conceptual introduction
AU - Rivera, Daniel E.
AU - Pew, Michael D.
AU - Collins, Linda M.
N1 - Funding Information:
Support for this work has been provided by the National Institute on Drug Abuse (NIDA) through a subcontract to Arizona State University (2778-ASU-DHHS-0075) from the Penn State University Methodology Center (prime award P50 DA010075).
PY - 2007/5
Y1 - 2007/5
N2 - The goal of this paper is to describe the role that control engineering principles can play in developing and improving the efficacy of adaptive, time-varying interventions. It is demonstrated that adaptive interventions constitute a form of feedback control system in the context of behavioral health. Consequently, drawing from ideas in control engineering has the potential to significantly inform the analysis, design, and implementation of adaptive interventions, leading to improved adherence, better management of limited resources, a reduction of negative effects, and overall more effective interventions. This article illustrates how to express an adaptive intervention in control engineering terms, and how to use this framework in a computer simulation to investigate the anticipated impact of intervention design choices on efficacy. The potential benefits of operationalizing decision rules based on control engineering principles are particularly significant for adaptive interventions that involve multiple components or address co-morbidities, situations that pose significant challenges to conventional clinical practice.
AB - The goal of this paper is to describe the role that control engineering principles can play in developing and improving the efficacy of adaptive, time-varying interventions. It is demonstrated that adaptive interventions constitute a form of feedback control system in the context of behavioral health. Consequently, drawing from ideas in control engineering has the potential to significantly inform the analysis, design, and implementation of adaptive interventions, leading to improved adherence, better management of limited resources, a reduction of negative effects, and overall more effective interventions. This article illustrates how to express an adaptive intervention in control engineering terms, and how to use this framework in a computer simulation to investigate the anticipated impact of intervention design choices on efficacy. The potential benefits of operationalizing decision rules based on control engineering principles are particularly significant for adaptive interventions that involve multiple components or address co-morbidities, situations that pose significant challenges to conventional clinical practice.
KW - Adaptive interventions
KW - Engineering process control
KW - Substance abuse prevention
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U2 - 10.1016/j.drugalcdep.2006.10.020
DO - 10.1016/j.drugalcdep.2006.10.020
M3 - Article
C2 - 17169503
AN - SCOPUS:34047187107
SN - 0376-8716
VL - 88
SP - S31-S40
JO - Drug and alcohol dependence
JF - Drug and alcohol dependence
IS - SUPPL. 2
ER -