Control systems engineering for understanding and optimizing smoking cessation interventions

Kevin P. Timms, Daniel E. Rivera, Linda M. Collins, Megan E. Piper

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

Cigarette smoking remains a major public health issue. Despite a variety of treatment options, existing intervention protocols intended to support attempts to quit smoking have low success rates. An emerging treatment framework, referred to as adaptive interventions in behavioral health, addresses the chronic, relapsing nature of behavioral health disorders by tailoring the composition and dosage of intervention components to an individual's changing needs over time. An important component of a rapid and effective adaptive smoking intervention is an understanding of the behavior change relationships that govern smoking behavior and an understanding of intervention components' dynamic effects on these behavioral relationships. As traditional behavior models are static in nature, they cannot act as an effective basis for adaptive intervention design. In this article, behavioral data collected daily in a smoking cessation clinical trial is used in development of a dynamical systems model that describes smoking behavior change during cessation as a self-regulatory process. Drawing from control engineering principles, empirical models of smoking behavior are constructed to reflect this behavioral mechanism and help elucidate the case for a control-oriented approach to smoking intervention design.

Original languageEnglish (US)
Title of host publication2013 American Control Conference, ACC 2013
Pages1964-1969
Number of pages6
StatePublished - Sep 11 2013
Event2013 1st American Control Conference, ACC 2013 - Washington, DC, United States
Duration: Jun 17 2013Jun 19 2013

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2013 1st American Control Conference, ACC 2013
CountryUnited States
CityWashington, DC
Period6/17/136/19/13

Fingerprint

Systems engineering
Control systems
Drawing (graphics)
Health
Public health
Dynamical systems
Chemical analysis

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Timms, K. P., Rivera, D. E., Collins, L. M., & Piper, M. E. (2013). Control systems engineering for understanding and optimizing smoking cessation interventions. In 2013 American Control Conference, ACC 2013 (pp. 1964-1969). [6580123] (Proceedings of the American Control Conference).
Timms, Kevin P. ; Rivera, Daniel E. ; Collins, Linda M. ; Piper, Megan E. / Control systems engineering for understanding and optimizing smoking cessation interventions. 2013 American Control Conference, ACC 2013. 2013. pp. 1964-1969 (Proceedings of the American Control Conference).
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Timms, KP, Rivera, DE, Collins, LM & Piper, ME 2013, Control systems engineering for understanding and optimizing smoking cessation interventions. in 2013 American Control Conference, ACC 2013., 6580123, Proceedings of the American Control Conference, pp. 1964-1969, 2013 1st American Control Conference, ACC 2013, Washington, DC, United States, 6/17/13.

Control systems engineering for understanding and optimizing smoking cessation interventions. / Timms, Kevin P.; Rivera, Daniel E.; Collins, Linda M.; Piper, Megan E.

2013 American Control Conference, ACC 2013. 2013. p. 1964-1969 6580123 (Proceedings of the American Control Conference).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Timms KP, Rivera DE, Collins LM, Piper ME. Control systems engineering for understanding and optimizing smoking cessation interventions. In 2013 American Control Conference, ACC 2013. 2013. p. 1964-1969. 6580123. (Proceedings of the American Control Conference).