Full length articleRepeated measures latent class analysis of daily smoking in three smoking cessation studies
Introduction
As with many drugs of abuse, relapse remains the most common outcome of attempts to quit smoking (Fiore et al., 2008). Success in quitting is typically measured in binary terms and at discrete time-points (Hughes et al., 2003). This approach is useful in assessing the health impact of smoking cessation treatments, but masks the pathways by which individuals change. Person-centered analysis of abstinence in the first weeks of quitting may reveal meaningful heterogeneity in responses to treatment and aid in identifying risk and protective factors associated with different paths to abstinence or relapse to smoking.
Relapse has long been recognized as a nonlinear process (Brandon et al., 2007, Shiffman, 1989) requiring nonlinear analytical approaches. In a recent effort to describe patterns of abstinence during a smoking cessation attempt, a repeated measures latent class analysis (RMLCA) of daily smoking in 1433 adult smokers from a trial of five active pharmacotherapies and placebo medication (Piper et al., 2009) yielded five latent classes (McCarthy et al., 2015). The most common patterns were stable success or failure in quitting. Less common patterns indicated unstable patterns of behavior during the first 27-days post-quit, with some establishing initially high probabilities of abstinence and then relapsing, others reducing the frequency of smoking early in the quit attempt, and others reporting initial smoking but then markedly increasing abstinence. The latent classes differed in six-month abstinence rates, suggesting that monitoring early smoking patterns may help identify individuals at high risk of longer-term smoking.
Modeling change patterns may facilitate treatment evaluation and refinement. Comparing treatments based on their ability to promote early change patterns may tell us more than will the evaluation of distal outcomes. This process approach may also suggest ways to identify individuals who do not initially respond to treatment and who may benefit from adaptive interventions (Rose and Behm, 2014).
Although most smokers who attempt to quit smoking will ultimately relapse, this homogeneity of the distal outcome (relapse) masks considerable heterogeneity of the smoking relapse process (McCarthy et al., 2006). Identifying stable risk and protective factors associated with particular change processes may foster development of treatment-matching protocols to boost cessation success (Witkiewitz et al., 2010). An RMLCA (McCarthy et al., 2015) showed that latent classes of smokers differed in nicotine dependence, smoking history, initial quitting confidence, sleep problems, and ethnic identification. It is important to replicate such findings to identify candidate variables for inclusion in treatment algorithms.
The current study aims to replicate our previous analysis (McCarthy et al., 2015) in three independent smoking cessation studies (Shiffman et al., 1996, Shiffman et al., 1997, McCarthy et al., 2008a, McCarthy et al., 2008b) and extend it to new treatment conditions. All studies offered treatment (counseling, patch, and/or bupropion) to smokers motivated to quit and assessed smoking status both in real time using ecological momentary assessment (EMA; Stone and Shiffman, 1994) via palmtop computer, and frequent time-line follow-back (TLFB) assessments. Daily abstinence status in the first 27 days of a quit attempt was analyzed using RMLCA to identify the latent classes of abstinence patterns in each study. Analyses addressed relations between 3-month outcomes, treatments, and relapse-relevant covariates and latent class.
Based on results from the six-arm pharmacotherapy trial (McCarthy et al., 2015), we hypothesized that high-dose nicotine patch treatment would facilitate early quitting, whereas bupropion would support recovery from early smoking. Based on an earlier study of counseling effects on lapse reactions (McCarthy et al., 2010), we expected counseling to promote recovery pattern. We also hypothesized that known relapse risk factors including gender, racial minority status, nicotine dependence, quitting confidence, and baseline craving and affective distress would be associated with membership in latent abstinence classes across studies, but did not make a priori hypotheses about cross-study variation in these relations.
Section snippets
Methods
The design and sample characteristics of each of the three studies are summarized in Table 1, Table 2. Each of these studies has been described previously (e.g., Study 1: Shiffman et al., 1996; Study 2: Shiffman et al., 2006; Study 3: McCarthy et al., 2008a, McCarthy et al., 2008b). All three studies provided: treatment to adult daily smokers motivated to quit smoking at no-cost, compensation for participation, and palmtop computers to record experiences and behaviors up to nine times per day.
Unconditional models
Based on an examination of fit indices, model rho parameters (daily abstinence probabilities within classes), and gamma parameters (latent class prevalences), we retained a 5-class model in all three studies and a pooled analysis (Table 3). Fig. 1a–c display the daily abstinence probabilities and prevalences by latent class for each study and Fig. 1d shows the pooled results. As in McCarthy et al. (2015), we have labeled the classes Early Quitters for those who maintain a high probability of
Discussion
The current results replicate a previous RMLCA of smoking status in the first 27 days of a quit attempt (McCarthy et al., 2015) and extend knowledge regarding treatment effects on latent abstinence patterns early in the quitting process. Results of three independent studies converged on a five-class solution: early and stable abstinence, stable reduction, early success followed by relapse, early struggle followed by improvement, or failure to change. Early stable abstinence and reduction are
Contributors
D. E. McCarthy contributed to the conceptualization of the project, prepared data for analysis, and drafted the manuscript. L. Ebssa conducted data analyses, prepared tables and figures, and assisted in the writing of the manuscript. K. Witkiewitz contributed to the conceptualization of the project, provided expert guidance regarding data analysis, and assisted in writing the manuscript. S. Shiffman contributed to the conceptualization of the project, contributed two datasets for analysis,
Conflict of interest
GlaxoSmithKline donated active and placebo medication for the randomized clinical trial of bupropion SR and counseling and the high-dose patch study re-analyzed in the present paper. Dr. McCarthy has received discounts on nicotine lozenge purchases from GlaxoSmithKline in the past. GlaxoSmithKline played no role in the design, implementation, analysis, or reporting of the studies. Dr. Shiffman has consulted to GlaxoSmithKline on smoking and smoking cessation, and currently consults with
Role of funding source
This work was supported by National Institute on Drug Abuse Grant R01DA033303 awarded to Drs. McCarthy and Shiffman. The data for this study were collected as part of previously reported studies and clinical trials (Shiffman et al., 1996 supported by grant R01DA6084 from the National Institute on Drug Abuse; Shiffman et al., 1997 supported by grant R01DA6084 from the National Institute on Drug Abuse; McCarthy et al., 2008a, McCarthy et al., 2008b supported by grants P50CA084724 from the
Acknowledgements
We wish to thank Timothy B. Baker, Michael C. Fiore, and the staff at the Center for Tobacco Research and Intervention in the Department of Medicine at the University of Wisconsin School of Medicine and Public Health for sharing data for this project.
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