Literature DB >> 8803366

Pros and cons of quitting, self-efficacy, and the stages of change in smoking cessation.

A Dijkstra1, H de Vries, M Bakker.   

Abstract

In The Netherlands, 34% of the population smoke, and 70% of these smokers are not planning to quit. The lower percentages in the U.S. population seem to reflect a difference in smoking culture. This study analyzes the pros and cons of quitting and self-efficacy expectation in the 5 stages of change in the Dutch population. The results are compared with the pattern of the pros and cons of smoking and self-efficacy expectations found in U.S. samples. The data show the hypothesized pattern: In the first 2 stages, the expected positive outcomes of quitting discriminated better between the stages than self-efficacy, whereas for later stages, self-efficacy was the better discriminator. This study shows that the stage typology is applicable to the Dutch population and that the pattern of the pros, cons, and self-efficacy is very similar to the pattern found in the U.S. populations.

Mesh:

Year:  1996        PMID: 8803366     DOI: 10.1037//0022-006x.64.4.758

Source DB:  PubMed          Journal:  J Consult Clin Psychol        ISSN: 0022-006X


  31 in total

1.  Predictors of smoking cessation among adult smokers in Malaysia and Thailand: findings from the International Tobacco Control Southeast Asia Survey.

Authors:  Lin Li; Ron Borland; Hua-Hie Yong; Geoffrey T Fong; Maansi Bansal-Travers; Anne C K Quah; Buppha Sirirassamee; Maizurah Omar; Mark P Zanna; Omid Fotuhi
Journal:  Nicotine Tob Res       Date:  2010-10       Impact factor: 4.244

2.  Individual-level predictors of cessation behaviours among participants in the International Tobacco Control (ITC) Four Country Survey.

Authors:  A Hyland; R Borland; Q Li; H-H Yong; A McNeill; G T Fong; R J O'Connor; K M Cummings
Journal:  Tob Control       Date:  2006-06       Impact factor: 7.552

3.  Young adults' judgments of the costs and benefits of smoking: The predictive efficacy of different outcome weightings in behavioral decision making.

Authors:  Amy M Voss; Marc T Kiviniemi
Journal:  Int J Adolesc Med Health       Date:  2007 Oct-Dec

4.  Improving understanding of the quitting process: psychological predictors of quit attempts versus smoking cessation maintenance among college students.

Authors:  Hyoung S Lee; Delwyn Catley; Kari Jo Harris
Journal:  Subst Use Misuse       Date:  2014-04-23       Impact factor: 2.164

5.  Abstinence expectancies and quit attempts.

Authors:  John R Hughes; Shelly Naud
Journal:  Addict Behav       Date:  2016-07-15       Impact factor: 3.913

6.  Rates and predictors of renewed quitting after relapse during a one-year follow-up among primary care patients.

Authors:  Krysten W Bold; Abdullah S Rasheed; Danielle E McCarthy; Thomas C Jackson; Michael C Fiore; Timothy B Baker
Journal:  Ann Behav Med       Date:  2015-02

7.  Efficacy of smoking prevention program 'Smoke-free Kids': study protocol of a randomized controlled trial.

Authors:  Marieke Hiemstra; Linda Ringlever; Roy Otten; Christine Jackson; Onno C P van Schayck; Rutger C M E Engels
Journal:  BMC Public Health       Date:  2009-12-21       Impact factor: 3.295

8.  Individual-level factors associated with intentions to quit smoking among adult smokers in six cities of China: findings from the ITC China Survey.

Authors:  Guoze Feng; Yuan Jiang; Qiang Li; Hua-Hie Yong; Tara Elton-Marshall; Jilan Yang; Lin Li; Natalie Sansone; Geoffrey T Fong
Journal:  Tob Control       Date:  2010-10       Impact factor: 7.552

9.  Partner's influences and other correlates of prenatal alcohol use.

Authors:  Nickie Y van der Wulp; Ciska Hoving; Hein de Vries
Journal:  Matern Child Health J       Date:  2015-04

Review 10.  Why won't our patients stop smoking? The power of nicotine addiction.

Authors:  David M Mannino
Journal:  Diabetes Care       Date:  2009-11       Impact factor: 19.112

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