Literature DB >> 32556210

Predictive Power of Dependence Measures for Quitting Smoking. Findings From the 2016 to 2018 ITC Four Country Smoking and Vaping Surveys.

Michael Le Grande1, Ron Borland1, Hua-Hie Yong2, K Michael Cummings3, Ann McNeill4, Mary E Thompson5, Geoffrey T Fong6,7,8.   

Abstract

INTRODUCTION: To test whether urges to smoke and perceived addiction to smoking have independent predictive value for quit attempts and short-term quit success over and above the Heaviness of Smoking Index (HSI). AIMS AND METHODS: Data were from the International Tobacco Control Four Country Smoking and Vaping Wave 1 (2016) and Wave 2 (2018) surveys. About 3661 daily smokers (daily vapers excluded) provided data in both waves. A series of multivariable logistic regression models assessed the association of each dependence measure on odds of making a quit attempt and at least 1-month smoking abstinence.
RESULTS: Of the 3661 participants, 1594 (43.5%) reported a quit attempt. Of those who reported a quit attempt, 546 (34.9%) reported short-term quit success. Fully adjusted models showed that making quit attempts was associated with lower HSI (adjusted odds ratio [aOR] = 0.81, 95% confidence interval [CI] = 0.73 to 0.90, p < .001), stronger urges to smoke (aOR = 1.08, 95% CI = 1.04 to 1.20, p = .002), and higher perceived addiction to smoking (aOR = 0.52, 95% CI = 0.32 to 0.84, p = .008). Lower HSI (aOR = 0.57, 95% CI = 0.40 to 0.87, p < .001), weaker urges to smoke (aOR = 0.85, 95% CI = 0.76 to 0.95, p = .006), and lower perceived addiction to smoking (aOR = 0.55, 95% CI = 0.32 to 0.91, p = .021) were associated with greater odds of short-term quit success. In both cases, overall R2 was around 0.5.
CONCLUSIONS: The two additional dependence measures were complementary to HSI adding explanatory power to smoking cessation models, but variance explained remains small. IMPLICATIONS: Strength of urges to smoke and perceived addiction to smoking may significantly improve prediction of cessation attempts and short-term quit success over and above routinely assessed demographic variables and the HSI. Stratification of analyses by age group is recommended because the relationship between dependence measures and outcomes differs significantly for younger (aged 18-39) compared to older (aged older than 40) participants. Even with the addition of these extra measures of dependence, the overall variance explained in predicting smoking cessation outcomes remains very low. These measures can only be thought of as assessing some aspects of dependence. Current understanding of the factors that ultimately determine quit success remains limited.
© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Year:  2021        PMID: 32556210      PMCID: PMC7822098          DOI: 10.1093/ntr/ntaa108

Source DB:  PubMed          Journal:  Nicotine Tob Res        ISSN: 1462-2203            Impact factor:   4.244


  33 in total

Review 1.  Methods of the International Tobacco Control (ITC) Four Country Survey.

Authors:  M E Thompson; G T Fong; D Hammond; C Boudreau; P Driezen; A Hyland; R Borland; K M Cummings; G B Hastings; M Siahpush; A M Mackintosh; F L Laux
Journal:  Tob Control       Date:  2006-06       Impact factor: 7.552

2.  How should we define light or intermittent smoking? Does it matter?

Authors:  Corinne G Husten
Journal:  Nicotine Tob Res       Date:  2009-02-20       Impact factor: 4.244

3.  Just blowing smoke? Social desirability and reporting of intentions to quit smoking.

Authors:  Alexander Persoskie; Wendy L Nelson
Journal:  Nicotine Tob Res       Date:  2013-07-24       Impact factor: 4.244

4.  Measuring the heaviness of smoking: using self-reported time to the first cigarette of the day and number of cigarettes smoked per day.

Authors:  T F Heatherton; L T Kozlowski; R C Frecker; W Rickert; J Robinson
Journal:  Br J Addict       Date:  1989-07

5.  The Cigarette Dependence Scale and Heaviness of Smoking Index as predictors of smoking cessation after 10weeks of nicotine replacement therapy and at 6-month follow-up.

Authors:  Laurie Zawertailo; Sabrina Voci; Peter Selby
Journal:  Addict Behav       Date:  2017-11-27       Impact factor: 3.913

6.  Predicting smoking cessation with self-reported measures of nicotine dependence: FTQ, FTND, and HSI.

Authors:  L T Kozlowski; C Q Porter; C T Orleans; M A Pope; T Heatherton
Journal:  Drug Alcohol Depend       Date:  1994-02       Impact factor: 4.492

7.  The Fagerström Test for Nicotine Dependence: a revision of the Fagerström Tolerance Questionnaire.

Authors:  T F Heatherton; L T Kozlowski; R C Frecker; K O Fagerström
Journal:  Br J Addict       Date:  1991-09

8.  Want, need and habit as drivers of smoking behaviour: A preliminary analysis.

Authors:  Luis Wehbe; Harveen Kaur Ubhi; Robert West
Journal:  Addict Behav       Date:  2017-07-19       Impact factor: 3.913

9.  Urge to smoke over 52 weeks of abstinence.

Authors:  Michael Ussher; Emma Beard; Gboyega Abikoye; Peter Hajek; Robert West
Journal:  Psychopharmacology (Berl)       Date:  2012-09-30       Impact factor: 4.530

10.  Smokers' strategies across social grades to minimise the cost of smoking in a period with annual tax increases: evidence from a national survey in England.

Authors:  Mirte Ag Kuipers; Timea Partos; Ann McNeill; Emma Beard; Anna B Gilmore; Robert West; Jamie Brown
Journal:  BMJ Open       Date:  2019-06-25       Impact factor: 2.692

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  3 in total

1.  Age-Related Interactions on Key Theoretical Determinants of Smoking Cessation: Findings from the ITC Four Country Smoking and Vaping Surveys (2016-2020).

Authors:  Michael Le Grande; Ron Borland; Hua-Hie Yong; Ann McNeill; Geoffrey Fong; K Michael Cummings
Journal:  Nicotine Tob Res       Date:  2022-03-26       Impact factor: 5.825

2.  Age as a predictor of quit attempts and quit success in smoking cessation: findings from the International Tobacco Control Four-Country survey (2002-14).

Authors:  Lauren Arancini; Ron Borland; Michael Le Grande; Mohammadreza Mohebbi; Seetal Dodd; Olivia M Dean; Michael Berk; Ann McNeill; Geoffrey T Fong; K Michael Cummings
Journal:  Addiction       Date:  2021-03-23       Impact factor: 7.256

3.  The Predictive Utility of Valuing the Future for Smoking Cessation: Findings from the ITC 4 Country Surveys.

Authors:  Ron Borland; Michael Le Grande; Bryan W Heckman; Geoffrey T Fong; Warren K Bickel; Jeff S Stein; Katherine A East; Peter A Hall; Kenneth Michael Cummings
Journal:  Int J Environ Res Public Health       Date:  2022-01-06       Impact factor: 4.614

  3 in total

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