Literature DB >> 12199822

Have we lost our way? The need for dynamic formulations of smoking relapse proneness.

Thomas M Piasecki1, Michael C Fiore, Danielle E McCarthy, Timothy B Baker.   

Abstract

Current smoking cessation treatments seem to differ from one another in the proportion of ex-smokers who survive the first few days of the quit attempt. After this initial effect, parallel relapse processes appear to unfold in all treatment groups; no available treatments seem to alter the nature of this late relapse process. True relapse prevention will require that we obtain a better understanding of the forces contributing to relapse across the span of the cessation attempt. A working model of dynamic relapse processes may be necessary before treatments can be improved. In this paper, we suggest that the conceptual model of relapse proneness (RP) described originally by the National Working Conference on Smoking Relapse can serve as an ecumenical organizational framework that may be used to integrate and conceptualize relapse data in ways that could generate new strategies for relapse research and inform treatment design. As an illustration, we sketch a preliminary model of RP which postulates that physical withdrawal, stressors/temptations, and cessation fatigue each make independent, time-shifted contributions to relapse risk. A new round of descriptive research focused on relapse proneness processes may be a prerequisite for improving existing smoking cessation interventions.

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Year:  2002        PMID: 12199822     DOI: 10.1046/j.1360-0443.2002.00216.x

Source DB:  PubMed          Journal:  Addiction        ISSN: 0965-2140            Impact factor:   6.526


  75 in total

Review 1.  New methods for tobacco dependence treatment research.

Authors:  Timothy B Baker; Robin Mermelstein; Linda M Collins; Megan E Piper; Douglas E Jorenby; Stevens S Smith; Bruce A Christiansen; Tanya R Schlam; Jessica W Cook; Michael C Fiore
Journal:  Ann Behav Med       Date:  2011-04

2.  Role of α7- and β4-containing nicotinic acetylcholine receptors in the affective and somatic aspects of nicotine withdrawal: studies in knockout mice.

Authors:  Astrid K Stoker; Berend Olivier; Athina Markou
Journal:  Behav Genet       Date:  2011-10-19       Impact factor: 2.805

3.  Longer duration of smoking abstinence is associated with waning cessation fatigue.

Authors:  Bryan W Heckman; K Michael Cummings; Jonathan J K Stoltman; Jennifer Dahne; Ron Borland; Geoffrey T Fong; Matthew J Carpenter
Journal:  Behav Res Ther       Date:  2018-11-23

4.  Modeling the complexity of post-treatment drinking: it's a rocky road to relapse.

Authors:  Katie Witkiewitz; G Alan Marlatt
Journal:  Clin Psychol Rev       Date:  2007-01-18

5.  Indicators of cigarette smoking dependence and relapse in former smokers who vape compared with those who do not: findings from the 2016 International Tobacco Control Four Country Smoking and Vaping Survey.

Authors:  Ann McNeill; Pete Driezen; Sara C Hitchman; K Michael Cummings; Geoffrey T Fong; Ron Borland
Journal:  Addiction       Date:  2019-08-15       Impact factor: 6.526

6.  Modeling complexity of EMA data: time-varying lagged effects of negative affect on smoking urges for subgroups of nicotine addiction.

Authors:  Mariya Shiyko; Pamela Naab; Saul Shiffman; Runze Li
Journal:  Nicotine Tob Res       Date:  2013-08-03       Impact factor: 4.244

7.  Heaviness of smoking predicts smoking relapse only in the first weeks of a quit attempt: findings from the International Tobacco Control Four-Country Survey.

Authors:  Hua-Hie Yong; Ron Borland; James Balmford; Andrew Hyland; Richard J O'Connor; Mary E Thompson; Matthew J Spittal
Journal:  Nicotine Tob Res       Date:  2013-10-24       Impact factor: 4.244

8.  Individual and combined effects of multiple high-risk triggers on postcessation smoking urge and lapse.

Authors:  Cho Y Lam; Michael S Businelle; Carrie J Aigner; Jennifer B McClure; Ludmila Cofta-Woerpel; Paul M Cinciripini; David W Wetter
Journal:  Nicotine Tob Res       Date:  2013-12-09       Impact factor: 4.244

9.  Bayesian inference for smoking cessation with a latent cure state.

Authors:  Sheng Luo; Ciprian M Crainiceanu; Thomas A Louis; Nilanjan Chatterjee
Journal:  Biometrics       Date:  2009-01-23       Impact factor: 2.571

10.  The quitting rollercoaster: how recent quitting history affects future cessation outcomes (data from the International Tobacco Control 4-country cohort study).

Authors:  Timea R Partos; Ron Borland; Hua-Hie Yong; Andrew Hyland; K Michael Cummings
Journal:  Nicotine Tob Res       Date:  2013-03-14       Impact factor: 4.244

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