Elsevier

Addictive Behaviors

Volume 39, Issue 9, September 2014, Pages 1318-1324
Addictive Behaviors

Predictors of successful and unsuccessful quit attempts among smokers motivated to quit

https://doi.org/10.1016/j.addbeh.2014.04.017Get rights and content

Highlights

  • Many smokers do not attempt to quit or relapse soon after their quit attempt.

  • We investigated the predictors of successful and unsuccessful quit attempts.

  • Different factors played a role in predicting quit attempts and their success.

  • Intention to quit only played a role in predicting quit attempts.

  • Self-efficacy was the main factor predicting quit attempt success.

Abstract

Introduction

Despite their positive motivation to quit, many smokers do not attempt to quit or relapse soon after their quit attempt. This study investigated the predictors of successful and unsuccessful quit attempts among smokers motivated to quit smoking.

Methods

We conducted secondary data analysis among respondents motivated to quit within 6 months, randomized to the control group (N = 570) of a Web-based smoking cessation intervention study. Using chi-square tests and ANOVA with Tukey post hoc comparisons, we investigated baseline differences by smoking status (successful quitter/relapse/persistent smoker) assessed after 6 weeks (N = 214). To identify independent predictors of smoking status, multivariate multinomial logistic regression analyses were conducted.

Results

Successful quitters at 6-week follow-up (26%) had reported significantly higher baseline levels of self-efficacy than relapsers (45%) and persistent smokers (29%). Furthermore, both successful quitters and relapsers had reported a significantly higher baseline intention to quit than persistent smokers and successful quitters had reported significantly more preparatory planning at baseline than persistent smokers. Results from regression analyses showed that smokers' baseline intention to quit positively predicted quit attempts reported after 6 weeks, while self-efficacy positively predicted quit attempt success.

Conclusions

Different factors appear to play a role in predicting quit attempts and their success. Whereas intention to quit only appeared to play a role in predicting quit attempts, self-efficacy was the main factor predicting quit attempt success. More research is needed to determine the role of preparatory planning and plan enactment and to investigate whether these findings can be replicated on the long term.

Introduction

Effective interventions exist to aid smokers in the process of smoking cessation (Lancaster and Stead, 2005, Lancaster and Stead, 2008, Lancaster et al., 2000). These interventions mostly target smokers motivated to quit, as a positive motivation to quit is considered a necessary prerequisite for smokers to actually quit smoking (Hyland et al., 2006, Norman et al., 1999, Vangeli et al., 2011). This is not surprising as, next to intervention developers, smokers themselves also believe that is necessary to be motivated to quit smoking before it is worthwhile trying (Balmford & Borland, 2008). Despite using the motivation to quit as an inclusion criterion, however, smoking cessation intervention studies still show that many smokers do not make a quit attempt during the study period, or do make a quit attempt but relapse to smoking soon after their attempt (Hoving et al., 2010, Smit et al., 2012, Te Poel et al., 2009). It is therefore important to not only identify the predictors of undertaking a quit attempt, but also to investigate the predictors of quit attempt success among smokers participating in smoking cessation intervention studies.

A systematic review investigating the predictors of attempts to quit smoking and their success found that having made a quit attempt in the past year and motivation to quit were highly predictive of quit attempts whereas only measures of tobacco dependence were consistently predictive of the success of these attempts (Vangeli et al., 2011). Similarly, a study among Canadian young adults found that intention to quit predicted quit attempts, whereas low addiction levels and high self-efficacy levels predicted 30-day smoking abstinence (Diemert, Bondy, Brown, & Manske, 2013). In other previous studies, self-efficacy has also been found to be an important predictor of quit attempts' success (Gwaltney et al., 2009, Ockene et al., 2000, Vangeli et al., 2011). Most of these studies, however, only included respondents from general population samples of smokers. Though, for intervention developers, it might be most informative to know whether these results are generalizable to samples of smokers who voluntarily participate in smoking cessation intervention studies and can be expected to have at least some motivation to quit smoking. Some studies conducted among smokers participating in smoking cessation intervention studies identified lower nicotine dependence (Bailey, Bryson, & Killen, 2011) as a predictor of quit attempts, and gender (Bailey et al., 2011), higher self-efficacy levels (Elfeddali, Bolman, Candel, Wiers, & de Vries, 2012b), the use of bupropion (Hoving, Mudde, & de Vries, 2006) and preparatory planning (Elfeddali et al., 2012b, Hoving et al., 2006) as predictors of smoking abstinence.

Yet, as the evidence to date on the predictors of quit attempts and their success among smokers motivated to quit is ambiguous, the present study aimed to identify the predictors of successful and unsuccessful quit attempts assessed after a 6-week follow-up period among smokers motivated to quit within 6 months. In this study, we used the Integrated Change (I-Change) Model (De Vries et al., 2003, Fig. 1) as a theoretical framework. According to the I-Change Model (De Vries et al., 2003), the most proximal predictor of behavior is the intention to perform this behavior, which is predicted by three motivational constructs: attitude, consisting of the perceived advantages (pros) and disadvantages (cons) of the behavior; perceived social influence, including perceived social norms, social modeling and social pressure; and self-efficacy, or a person's level of confidence to perform the behavior. The I-Change Model (De Vries et al., 2003) also includes several pre-motivational and post-motivational factors and it recognizes the gap between intention and behavior (e.g. (Armitage & Conner, 2001)). While perceived barriers to change might increase this intention–behavior gap, ability factors as skills and the formation of action plans (including both preparatory planning and coping planning) are assumed to bridge this gap. Based on the I-Change Model and previous research findings, we hypothesized that cognitive factors such as attitude, social influence, self-efficacy and the intention to quit smoking would predict initial behavior change, or attempts to quit smoking, and that ability factors such as action planning, (perceived) skills and barriers (e.g. the level of nicotine dependence), would predict the success of these attempts.

Section snippets

Methods

Secondary analyses were conducted among respondents in the no-intervention control group (N = 570) of a randomized controlled trial (RCT) investigating the effectiveness of a Web-based computer-tailored smoking cessation program.

Sample characteristics and correlation matrix

The sample consisted of respondents with an average age of 48.4 years (SD = 12.2). Almost half of the sample had a medium level of education and about half of the respondents were male. Moreover, respondents had an average addiction level of 5.2 (SD = 2.4) and reported on average six (SD = 23) previous quit attempts.

The inter-correlations amongst predictor variables are presented in Table 1; even though many significant inter-correlations were identified, no signs of multicollinearity between any

Discussion

This study aimed to identify the predictors of successful and unsuccessful quit attempts as assessed after a 6-week follow-up period among smokers motivated to quit within 6 months.

Role of funding sources

This study was supported by the Dutch Cancer Society (UM 2007-3834) and a personal grant the first author received from CAPHRI School for Public Health and Primary Care. Neither of these funding sources had any role in the study design, collection, analyses or interpretation of data, writing the manuscript and the decision to submit the manuscript for publication.

Contributors

E.S.S., C.H. and H.d.V. developed the concept and design of the study. E.S.S. designed the questionnaires and collected data. H.d.V. and C.H. provided support during the development of intervention materials and execution of the study. E.S.S., C.H. and H.d.V. significantly contributed to writing this manuscript, while R.W. and K.S.O. were involved in revising the manuscript. All authors have read and approved the final version of the manuscript.

Conflict of interest

Hein de Vries is the scientific director of Vision2Health, a company that licenses evidence-based innovative computer-tailored health communication tools. Robert West undertakes research and consultancy for the following developers and manufacturers of smoking cessation treatments: Pfizer, J&J, McNeill, GSK, Nabi, Novartis and Sanofi-Aventis. Robert West also has a share in the patent of a novel nicotine delivery device. Ciska Hoving, Karen Schelleman-Offermans and Eline Smit have no conflicts

Acknowledgments

The authors would like to thank all participating smokers for their participation. Besides, the first author would like to thank the members of the monthly Health Communication Research group meeting for their constructive feedback on an earlier version of this paper.

References (33)

  • L.M. Diemert et al.

    Young adult smoking cessation: Predictors of quit attempts and abstinence

    American Journal of Public Health

    (2013)
  • I. Elfeddali et al.

    Preventing smoking relapse via Web-based computer-tailored feedback: A randomized controlled trial

    Journal of Medical Internet Research

    (2012)
  • I. Elfeddali et al.

    The role of self-efficacy, recovery self-efficacy, and preparatory planning in predicting short-term smoking relapse

    British Journal of Health Psychology

    (2012)
  • G. Eysenbach

    The law of attrition

    Journal of Medical Internet Research

    (2005)
  • K. Fagerstrom

    Determinants of tobacco use and renaming the FTND to the Fagerstrom Test for Cigarette Dependence

    Nicotine and Tobacco Research

    (2012)
  • C.J. Gwaltney et al.

    Self-efficacy and smoking cessation: A meta-analysis

    Psychology of Addictive Behaviors

    (2009)
  • Cited by (95)

    • Health Behavior

      2022, Comprehensive Clinical Psychology, Second Edition
    View all citing articles on Scopus
    View full text