Evidence map›Paper›PMID 28922651›Full record

ArticleDrug and alcohol dependence2017

Evaluating the effect of smoking cessation treatment on a complex dynamical system.

Korkut Bekiroglu, Michael A Russell, Constantino M Lagoa, Stephanie T Lanza, Megan E Piper

Abstract read
In one paragraph

Article in Drug and alcohol dependence, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Antidepressants for smoking cessation.The Cochrane database of systematic reviews · 2020
    Pooled it
  3. Pooled it
  4. The Network Structure of Tobacco Withdrawal in a Community Sample of Smokers Treated With Nicotine Patch and Behavioral Counseling.Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2020
    Trial
  5. Tobacco withdrawal system recovery time assessed during smoking satiety predicts smoking behavior change among individuals who smoke cigarettes daily.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Antidepressants for smoking cessation.The Cochrane database of systematic reviews · 2023
    Review
  10. Article
  11. Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Korkut BekirogluDepartment of Electrical Engineering and The Methodology Center, The Pennsylvania State University, United States.
Michael A RussellDepartment of Biobehavioral Health and The Methodology Center, The Pennsylvania State University, United States. Electronic address: mar60@psu.edu.
Constantino M LagoaDepartment of Electrical Engineering and The Methodology Center, The Pennsylvania State University, United States.
Stephanie T LanzaDepartment of Biobehavioral Health and The Methodology Center, The Pennsylvania State University, United States.
Megan E PiperCenter for Tobacco Research and Intervention, University of Wisconsin School of Medicine and Public Health, United States.

Funding

Testing Relapse Recovery Intervention ComponentsP01CA180945 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI COOK, JESSICA MEGAN · 2014 to 2023
$23.0M
Pilot, Mentoring, and Professional Development CoreP50DA039838 · NIDA · PENNSYLVANIA STATE UNIVERSITY, THE · PI COLLINS, LINDA M · 2015 to 2019
$13.9M
Advancing Tobacco Research by Integrating Systems Science and Mixture ModelsR01CA168676 · NCI · PENNSYLVANIA STATE UNIVERSITY, THE · PI LANZA, STEPHANIE T · 2012 to 2014
$498k
NCI NIH HHS P01 CA180945NCI NIH HHS R01 CA168676NIDA NIH HHS P50 DA039838
6 · The paper itself

Abstract

objectiveTo understand the dynamic relations among tobacco withdrawal symptoms to inform the development of effective smoking cessation treatments. Dynamical system models from control engineering are introduced and utilized to evaluate complex treatment effects. We demonstrate how dynamical models can be used to examine how distinct withdrawal-related processes are related over time and how treatment influences these relations.

methodIntensive longitudinal data from a randomized placebo-controlled smoking cessation trial (N=1504) are used to estimate a dynamical model of withdrawal-related processes including momentary craving, negative affect, quitting self-efficacy, and cessation fatigue for each of six treatment conditions (nicotine patch, nicotine lozenge, bupropion, patch + lozenge, bupropion + lozenge, and placebo).

resultsEstimation and simulation results show that (1) withdrawal measurements are interrelated over time, (2) nicotine patch + nicotine lozenge showed reduced cessation fatigue and enhanced self-efficacy in the long-term while bupropion + nicotine lozenge was more effective at reducing negative affect and craving, and (3) although nicotine patch + nicotine lozenge had a better initial effect on cessation fatigue and self-efficacy, nicotine lozenge had a stronger effect on negative affect and nicotine patch had a stronger impact on craving.

conclusionsThis approach can be used to provide new evidence illustrating (a) the total impact of treatment conditions (via steady state values) and (b) the total initial impact (via rate of initial change values) on smoking-related outcomes for separate treatment conditions, noting that the conditions that produce the largest change may be different than the conditions that produce the fastest change.

Indexed as

Tobacco Use Cessation DevicesBupropionCravingDrug Therapy, CombinationFatigueHumansNicotineSmoking CessationSubstance Withdrawal SyndromeTabletsTreatment OutcomeBupropionNicotineTabletsDynamical modeling for smoking cessation studyDynamical systems modelsIntensive longitudinal dataSmoking cessation treatmentWithdrawal

Identifiers

PMID28922651
PMCPMC5901658

What OpenQuestion holds

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Registered trials

None linked

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.