SQ4U — A computer tailored smoking relapse prevention program incorporating planning strategy assignments and multiple feedback time points after the quit-attempt: Development and design protocol

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Abstract

Background

The SQ4U (Stay Quit for You)-study aims to test the efficacy of two computer tailored smoking relapse prevention programs which incorporate planning strategy assignments and provide tailored feedback at multiple time points after the quit-attempt. The programs differ in the support provided after the quit-attempt. This paper aims to describe the development and design of SQ4U.

Methods/design

SQ4U-respondents were daily smokers in the 18–65 years age group, who were motivated to quit smoking and willing to make a quit-attempt within 1 month of registration. The study is a randomized controlled trial with three conditions: 1. Control group, 2. Action planning (AP) program, 3. Action planning plus (AP+) program. Respondents in the control group only filled out questionnaires. The AP program consisted of computer tailored baseline feedback based on the I-Change Model and six planning strategy assignments. The AP+ program provided the same program elements as the AP program, but was extended with tailored feedback at eleven time points after the quit-attempt. The feedback targeted (recovery) self-efficacy, planning and negative affect. There were two follow-up measurements at 6 and 12 months after baseline. User experiences and the efficacy of the programs in fostering seven-day point prevalence and continued abstinence were examined using a process evaluation and logistic regression analyses.

Discussion

The present paper outlines the development and design of the SQ4U-study. This study has the potential to provide a new effective computer tailored smoking relapse prevention program as well as insight into effective smoking relapse prevention strategies.

Introduction

Smoking relapse is an evident problem in the process of smoking cessation. A systematic review shows relapse rates of 49–76% in the first week and 80–90% in the first three months after the quit-attempt [1].

Several factors are associated with smoking relapse. The Relapse Prevention (RP) Model [2], [3] accentuates the role of covert (e.g. lifestyle imbalances and cravings) and immediate (e.g. high-risk situations) factors in the process of relapse. A range of empirical studies demonstrated the role of self-efficacy and identified a low level of self-efficacy as a reliable predictor of smoking relapse [4], [5], [6], [7], [8], [9], [10]. Furthermore, studies identified associations between smoking relapse and negative outcome expectancies of smoking [5], [10], lack of social support [11], [12], physical dependence [13], [14], [15], high craving levels [7], [16], [17], negative affect and stress [18], [19], [20], [21], [22]. A number of relapse prevention programs incorporating strategies to change these factors have been developed and tested. Many of these programs prevent relapse by utilizing behavioral approaches, mainly skill trainings aimed at identifying and coping with high-risk situations [23]. Other programs use pharmacological therapy. Yet, two literature reviews concluded that the efficacy of current smoking relapse prevention programs remains limited [23], [24].

The alarming relapse rates combined with the lack of effective prevention programs suggest the need for new approaches. We conducted the SQ4U-study and developed and tested a new relapse prevention approach consisting of three main elements.

First, planning strategies – which consist of preparatory planning and coping planning according to the Integrated Change Model – have recently shown their importance in fostering smoking cessation [25] and smoking abstinence [26], [27], [28], [29]. However, little attention has been given to the possible efficacy of combining these planning strategies in smoking relapse prevention programs. We incorporated preparatory and coping planning strategy assignments. The second element is the delivery mode of the prevention program. This needs to be modified for the needs of the quitter. Computer tailoring is a very personalized approach and computer feedback is assessment-based, focuses on the respondent and only addresses aspects that are relevant to the respondent [30], [31]. Moreover this strategy has been shown to meet the needs and interests of the respondent, to be more likely to be read and remembered and to have a high reach with relatively low costs [32], [33], [34], [35]. Computer tailored programs have shown to be promising tools in the field of smoking cessation [33], [36], [37], [38], [39]. Third, providing tailored feedback at multiple time points has shown to be more effective than a single tailoring point [40], [41], [42]. Yet, as far as we know, no specific computer tailored smoking relapse prevention program incorporating planning strategy assignments and multiple feedback points has been developed and/or tested.

The SQ4U-study aims to fulfill these needs by developing and testing the efficacy of two computer tailored smoking relapse prevention programs incorporating planning strategy assignments and providing tailored feedback at multiple time points after the quit-attempt. The programs differ in the support provided after the quit-attempt.

This paper describes the development of the SQ4U-program, the program elements and the design of the SQ4U-study.

Section snippets

Methods

Ethical approval for this study was obtained from the Medical Ethics Committee of the Maastricht Academic Hospital and Maastricht University (MEC 08-3-003; NL21414.068.08). The study is registered with the Dutch Trial Register (NTR1892).

Questionnaires

The baseline questionnaire was based on the I-Change Model and was experimentally tested in previous studies. The questionnaire included intention to quit, pros and cons of non-smoking, pros and cons of relapse, self-efficacy, recovery self-efficacy, social influence and preparatory planning [27], [33], [38], [43], [44], [45], [46]. Finally, we measured demographics, level of nicotine dependence [47], [48], perceived stress [49] and depression [50]. The questionnaire at the six and twelve month

Primary outcome variables

The outcome variables in this study were seven-day point-prevalence and continued abstinence at 6 and 12 months after baseline. The outcome variables were measured conforming to the definitions in Hughes et al. [53]. The respondents were asked whether they had smoked during the last 7 days (from follow-up) and since the quit-date to measure respectively seven-day point-prevalence and continued abstinence. Smoking during the last 7 days and after the quit-date was coded as relapse (0) and

Discussion

This paper describes the development of the SQ4U-programs, the program elements and the design of the SQ4U-study. The SQ4U-study aims to test the efficacy of the two described internet based smoking relapse prevention programs. Both programs include planning strategies. The two programs differ in the support provided after the quit-attempt (AP+ provided tailored feedback at multiple time points after the quit-attempt, while AP did not) and will be compared to a control program.

Conclusion

The SQ4U-study has the potential to provide a new effective computer tailored smoking relapse prevention program and to help us to gain insight into effective prevention strategies in the field of smoking relapse prevention. The behavioral effects of SQ4U will be reported in other papers.

Acknowledgments

This study was funded by the Dutch Organisation for Health Research and Innovation (grant number 6130-0030). We would like to thank Verina Servranck and Claire Jeukens for their contribution to the development and piloting of the SQ4U intervention materials. Finally, we would like to thank the respondents for their participation in the study.

References (58)

  • A. Hernández et al.

    Covariate adjustment in randomized controlled trials with dichotomous outcomes increases statistical power and reduces sample size requirements

    J Clin Epidemiol

    (2004)
  • J. Hughes et al.

    Shape of the relapse curve and long-term abstinence among untreated smokers

    Addiction

    (2004)
  • G.A. Marlatt et al.

    Relapse prevention, maintenance strategies in the treatment of addictive behaviors

  • G.A. Marlatt et al.

    Relapse prevention: maintenance strategies in the treatment of addictive behaviors

    (1985)
  • N. Amodei et al.

    Predictors of initial abstinence in smokers enrolled in a smoking cessation program

    Subst Use Misuse

    (2005)
  • A. Dijkstra et al.

    Residual outcome expectations and relapse in ex-smokers

    Health Psychol

    (2003)
  • C. Gwaltney

    Self-efficacy and smoking cessation: a meta-analysis

    Psychol Addict Behav

    (2009)
  • N. Herd et al.

    Predictors of smoking relapse by duration of abstinence: findings from the International Tobacco Control (ITC) Four Country Survey

    Addiction

    (2009)
  • J. Ockene

    Relapse and maintenance issues for smoking cessation

    Health Psychol

    (2000)
  • C.J. Gwaltney

    Dynamic self-efficacy and outcome expectancies: prediction of smoking lapse and relapse

    J Abnorm Psychol

    (2005)
  • D. Lawhon

    Longitudinal analysis of abstinence-specific social support and smoking cessation

    Health Psychol

    (2009)
  • A. Hyland

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

    Tob Control

    (2006)
  • S.L. Kenford

    Predicting relapse back to smoking: contrasting affective and physical models of dependence

    J Consult Clin Psychol

    (2002)
  • J.D. Killen et al.

    Craving is associated with smoking relapse: findings from three prospective studies

    Exp Clin Psychopharmacol

    (1997)
  • S. Shiffman

    A day at a time: predicting smoking lapse from daily urge

    J Abnorm Psychol

    (1997)
  • J.D. Kassel et al.

    Smoking, stress, and negative affect: correlation, causation, and context across stages of smoking

    Psychol Bull

    (2003)
  • S. Shiffman

    First lapses to smoking: within-subjects analysis of real-time reports

    J Consult Clin Psychol

    (1996)
  • P. Hajek

    Relapse prevention interventions for smoking cessation

    Cochrane Database Syst Rev

    (2009)
  • T. Lancaster

    Prevention of relapse after quitting smoking: a systematic review of trials

    Arch Intern Med

    (2006)
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    Trial registration: Dutch Trial Register NTR1892.

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