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Comparative dynamics of four smoking withdrawal symptom scales.

ABSTRACT: To examine the association of person-specific trajectories of withdrawal symptoms of urge-to-smoke, negative affect, physical symptoms and hunger during the first 7 days after smoking cessation with abstinence at end of treatment (EOT) and at 6 months.? Hierarchical linear modeling (HLM) was used to model person-specific trajectory parameters (level, slope, curvature and volatility) for withdrawal symptoms.? University-based smoking cessation trials.? Treatment-seeking smokers in clinical trials of transdermal nicotine versus nicotine spray (n?=?514) and bupropion versus placebo (n?=?421).? Self-reported withdrawal symptoms for 7 days after the planned quit date, and 7-day point prevalence and continuous abstinence at EOT and 6 months.? In regressions that included trajectory parameters for one group of withdrawal symptoms, both urge-to-smoke and negative affect were predictive of abstinence while physical symptoms and hunger were generally not predictive. In stepwise regressions that included the complete set of trajectory parameters across withdrawal symptoms (for urge-to-smoke, negative affect, physical symptoms and hunger), with a single exception only the trajectory parameters for urge-to-smoke were predictive. Area under the receiver operator characteristic curve was 0.594 for covariates alone, and 0.670 for covariates plus urge-to-smoke trajectory parameters.? Among a number of different withdrawal symptoms (urge-to-smoke, negative affect, physical symptoms and hunger) urge-to-smoke trajectory parameters (level, slope and volatility) over the first 7 days of smoking cessation show the strongest prediction of both short- and long-term relapse. Other withdrawal symptoms increase the predictive ability by negligible amounts.

SUBMITTER: Javitz HS

PROVIDER: S-EPMC3394903 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

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Comparative dynamics of four smoking withdrawal symptom scales.

Javitz Harold S HS Lerman Caryn C Swan Gary E GE

Addiction (Abingdon, England) 20120417 8

<h4>Aims</h4> To examine the association of person-specific trajectories of withdrawal symptoms of urge-to-smoke, negative affect, physical symptoms and hunger during the first 7 days after smoking cessation with abstinence at end of treatment (EOT) and at 6 months.<h4>Design</h4> Hierarchical linear modeling (HLM) was used to model person-specific trajectory parameters (level, slope, curvature and volatility) for withdrawal symptoms.<h4>Setting</h4> University-based smoking cessation trials. ...[more]

PMID: 22321019

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Project description:IntroductionAssessment of withdrawal symptoms, treatment mechanisms, and side effects is central to understanding and improving smoking cessation interventions. Though each domain is typically assessed separately with widely used questionnaires to separately assess each domain (eg, Minnesota Nicotine Withdrawal Scale = withdrawal; Questionnaire of Smoking Urges-Brief = craving; Positive and Negative Affect Schedule = affect; symptom checklist = side effects), there are substantial problems with this implicit "one questionnaire equals one construct" measurement model, including item overlap across questionnaires. This study sought to clarify the number and nature of constructs assessed during smoking cessation by developing an explicit measurement model.MethodsTwo subsamples were randomly created from 1246 smokers in a clinical trial. Exploratory and confirmatory factor analyses were conducted to identify and select a model that best represented the data. Measurement invariance was assessed to determine if the factors and their content were consistent prior to and during the quit. Improvement in construct overlap within this model was compared against the implicit measurement model using correlational analyses.ResultsA 5-factor measurement model composed of negative affect, somatic symptoms, sleep problems, positive affect, and craving fits the data well prior to and during quitting. All factor content except somatic symptoms was consistent over time. Correlational analyses indicated that the 5-factor model attenuated construct overlap compared to the implicit model.ConclusionsThe models generated from data-driven approaches (eg, the 5-factor model) reduced overlap and better represented the constructs underlying these measures. This approach created distinct, stable constructs that span over measures of side effects and potential treatment mechanisms.ImplicationsThis study demonstrated that measures assessing treatment mechanisms, withdrawal symptoms, and side effects contain problematic overlap that reduces the clarity of these key constructs. The use of data-driven approaches showed that these measures do not map on to their posited latent constructs (eg, the Minnesota Nicotine Withdrawal Scale does not yield a withdrawal factor). Rather, these measures form distinct, basic processes that may represent more meaningful constructs for future research on cessation and treatment. Assessments designed to individually examine these processes may improve the study of treatment mechanisms.

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Comparative dynamics of four smoking withdrawal symptom scales.

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Comparative dynamics of four smoking withdrawal symptom scales.

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