ArticleProceedings of the ... American Control Conference. American Control Conference2013
Control Systems Engineering for Understanding and Optimizing Smoking Cessation Interventions.
Article in Proceedings of the ... American Control Conference. American Control Conference, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Toward Participatory Precision Health With Co-Designed Recommendations: Systematic Review of Just-in-Time Adaptive Interventions in Adolescents and Young Adults.Journal of medical Internet research · 2026Pooled it
- A dynamical systems approach to understanding self-regulation in smoking cessation behavior change.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2014Trial
- Just-in-time adaptive interventions for adolescent and young adult health and well-being: protocol for a systematic review.BMJ open · 2024Article
- Towards a Smart Smoking Cessation App: A 1D-CNN Model Predicting Smoking Events.Sensors (Basel, Switzerland) · 2020Article
- Personalized models of physical activity responses to text message micro-interventions: A proof-of-concept application of control systems engineering methods.Psychology of sport and exercise · 2019Article
- Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support.Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2018Article
- A Text Message Intervention with Adaptive Goal Support to Reduce Alcohol Consumption Among Non-Treatment-Seeking Young Adults: Non-Randomized Clinical Trial with Voluntary Length of Enrollment.JMIR mHealth and uHealth · 2018Article
- Evaluating the effect of smoking cessation treatment on a complex dynamical system.Drug and alcohol dependence · 2017Article
- Building new computational models to support health behavior change and maintenance: new opportunities in behavioral research.Translational behavioral medicine · 2015Article
- From Big Data to Knowledge in the Social Sciences.The Annals of the American Academy of Political and Social Science · 2015Article
- Continuous-Time System Identification of a Smoking Cessation Intervention.International journal of control · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.