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Withdrawal Symptom, Treatment Mechanism, and/or Side Effect? Developing an Explicit Measurement Model for Smoking Cessation Research.

ABSTRACT: INTRODUCTION:Assessment 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. METHODS:Two 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. RESULTS:A 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. CONCLUSIONS:The 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. IMPLICATIONS:This 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.

SUBMITTER: Tonkin SS

PROVIDER: S-EPMC7164574 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Withdrawal Symptom, Treatment Mechanism, and/or Side Effect? Developing an Explicit Measurement Model for Smoking Cessation Research.

Tonkin Sarah S SS Williams Trevor F TF Simms Leonard J LJ Tiffany Stephen T ST Mahoney Martin C MC Schnoll Robert A RA Cinciripini Paul M PM Hawk Larry W LW

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco 20200401 4

<h4>Introduction</h4>Assessment 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 probl ...[more]

PMID: 30535357

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Project description:Varenicline (Chantix) is a first-line treatment for smoking cessation but does not produce cessation in many individuals. It may be possible to improve abstinence by co-administering varenicline with other medications. Zonisamide (Zonegran) has a similar pharmacologic profile to topiramate, which has been shown to reduce smoking, but is better tolerated. This study evaluated whether combined zonisamide and varenicline reduced tobacco withdrawal and increased abstinence among smokers trying to quit, relative to varenicline and placebo.This was a double-blind, randomized, placebo-controlled pilot trial of zonisamide + varenicline versus placebo + varenicline for smoking cessation. Smokers received brief counseling and study medications, and completed weekly assessments for 10 consecutive weeks. The primary outcome was continuous abstinence rates (biochemically verified) during the final 4 weeks of treatment.Results are presented as intent-to-treat and completer analyses. Seventy-four individuals were enrolled; 45 completed the study. Overall, 14.9% (intent-to-treat) and 25.0% (completer) of participants maintained sustained abstinence during the final 4 weeks of treatment. There were no differences between groups for biochemically-verified smoking, but zonisamide + varenicline reduced self-reported smoking, nicotine withdrawal, and craving compared to placebo + varenicline.Zonisamide decreased nicotine withdrawal and craving, though not of sufficient magnitude to modify smoking behavior. The sample size was small and low rates of abstinence across groups suggest the study population was difficult to treat. Additional evaluation of zonisamide or other medications that increase GABA or decrease glutamate in larger or more diverse populations may yield positive clinical benefit for nicotine/tobacco cessation.This study provides support for layering novel medications with varenicline for smoking cessation, for investigating medications that target the GABA and glutamate system, and for assessing the contribution that reductions in nicotine withdrawal have on ultimate cessation outcomes.

Project description:BACKGROUND:Blended face-to-face and Web-based treatment is a promising way to deliver cognitive behavioral therapy. Since adherence has been shown to be a measure for treatment's acceptability and a determinant for treatment's effectiveness, in this study, we explored adherence to a new blended smoking cessation treatment (BSCT). OBJECTIVE:The objective of our study was to (1) develop an adequate method to measure adherence to BSCT; (2) define an adequate degree of adherence to be used as a threshold for being adherent; (3) estimate adherence to BSCT; and (4) explore the possible predictors of adherence to BSCT. METHODS:The data of patients (N=75) were analyzed to trace adherence to BSCT delivered at an outpatient smoking cessation clinic. In total, 18 patient activities (eg, using a Web-based smoking diary tool or responding to counselors' messages) were selected to measure adherence; the degree of adherence per patient was compared with quitting success. The minimum degree of adherence of patients who reported abstinence was examined to define a threshold for the detection of adherent patients. The number of adherent patients was calculated for each of the 18 selected activities; the degree of adherence over the course of the treatment was displayed; and the number of patients who were adherent was analyzed. The relationship between adherence and 33 person-, smoking-, and health-related characteristics was examined. RESULTS:The method for measuring adherence was found to be adequate as adherence to BSCT correlated with self-reported abstinence (P=.03). Patients reporting abstinence adhered to at least 61% of BSCT. Adherence declined over the course of the treatment; the percentage of adherent patients per treatment activity ranged from 82% at the start of the treatment to 11%-19% at the final-third of BSCT; applying a 61% threshold, 18% of the patients were classified as adherent. Marital status and social modeling were the best independent predictors of adherence. Patients having a partner had 11-times higher odds of being adherent (OR [odds ratio]=11.3; CI: 1.33-98.99; P=.03). For social modeling, graded from 0 (=partner and friends are not smoking) to 8 (=both partner and nearly all friends are smoking), each unit increase was associated with 28% lower odds of being adherent (OR=0.72; CI: 0.55-0.94; P=.02). CONCLUSIONS:The current study is the first to explore adherence to a blended face-to-face and Web-based treatment (BSCT) based on a substantial group of patients. It revealed a rather low adherence rate to BSCT. The method for measuring adherence to BSCT could be considered adequate because the expected dose-response relationship between adherence and quitting could be verified. Furthermore, this study revealed that marital status and social modeling were independent predictors of adherence. TRIAL REGISTRATION:Netherlands Trial Registry NTR5113; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5113 (Archived by WebCite at http://www.webcitation.org/71BAPwER8).

Dataset Information

Withdrawal Symptom, Treatment Mechanism, and/or Side Effect? Developing an Explicit Measurement Model for Smoking Cessation Research.

Publications

Withdrawal Symptom, Treatment Mechanism, and/or Side Effect? Developing an Explicit Measurement Model for Smoking Cessation Research.

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