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Introduction: Adoption of rigorous standards for reporting treatment fidelity is essential for advancing discovery, validation, and implementation of behavioral treatments. Whereas the NIH Behavior Change Consortium (BCC) developed an assessment tool to assess the quality of reporting and monitoring of treatment fidelity across health behavior change interventions, it has not yet been applied specifically to treatment fidelity in behavioral tobacco treatment trials.Aims and Methods: We conducted a scoping review of peer-reviewed, clinical trials of behavioral adult tobacco treatment interventions published in English between 2006 and 2018. Using the BCC treatment fidelity checklist, articles were coded for the presence or absence of various treatment fidelity strategies within each of 5 domains: Design, Training, Delivery, Receipt, and Enactment. Eligible articles (N = 755) were coded by two independent coders.Results: The proportion of reporting strategies varied within the fidelity domains, ranging from 5.2% to 96.3% in Design, 1.9% to 24.9% in Training, 2.6% to 32.3% in Delivery, 5.2% to 44.3% in Receipt, and 6.7% to 43.2% in Enactment. The mean proportion of adherence to treatment fidelity strategies within each domain was: Design (68%), Training (14%), Delivery (15%), Receipt (16%), and Enactment (25%). Only 11 studies achieved ≥80% reporting across >1 fidelity domain. There was no evidence for improvement in fidelity reporting across the 13-year time frame from the initial BCC publication to the present.Conclusions: These findings illustrate the lack of consistency in fidelity reporting in tobacco treatment trials and underscore the challenges faced in evaluating rigor and reproducibility, as well as interpretation and dissemination of findings. Recommendations are made for improving fidelity reporting in tobacco treatment trials.Implications: The SRNT Treatment Research Network sponsored a scoping review to summarize the current state of reporting treatment fidelity and make recommendations for best practices in reporting fidelity in tobacco treatment trials. The review identified a lack of consistency in fidelity reporting, illustrating the challenges faced in evaluating rigor, and reproducibility, as well as interpretation and dissemination of findings. [ABSTRACT FROM AUTHOR]

Significance: Increased rates of smoking cessation will be essential to maximize the population benefit of low-dose CT screening for lung cancer. The NCI's Smoking Cessation at Lung Examination (SCALE) Collaboration includes eight randomized trials, each assessing evidence-based interventions among smokers undergoing lung cancer screening (LCS). We examined predictors of trial enrollment to improve future outreach efforts for cessation interventions offered to older smokers in this and other clinical settings.Methods: We included the six SCALE trials that randomized individual participants. We assessed demographics, intervention modalities, LCS site and trial administration characteristics, and reasons for declining.Results: Of 6285 trial- and LCS-eligible individuals, 3897 (62%) declined and 2388 (38%) enrolled. In multivariable logistic regression analyses, Blacks had higher enrollment rates (OR 1.5, 95% CI 1.2,1.8) compared to Whites. Compared to "NRT Only" trials, those approached for "NRT + prescription medication" trials had higher odds of enrollment (OR 6.1, 95% CI 4.7,7.9). Regarding enrollment methods, trials using "Phone + In Person" methods had higher odds of enrollment (OR 1.6, 95% CI 1.2,1.9) compared to trials using "Phone Only" methods. Some of the reasons for declining enrollment included "too busy" (36.6%), "not ready to quit" (8.2%), "not interested in research" (7.7%), and "not interested in the intervention offered" (6.2%).Conclusion: Enrolling smokers in cessation interventions in the LCS setting is a major priority that requires multiple enrollment and intervention modalities. Barriers to enrollment provide insights that can be addressed and applied to future cessation interventions to improve implementation in LCS and other clinical settings with older smokers.Implications: We explored enrollment rates and reasons for declining across six smoking cessation trials in the lung cancer screening setting. Offering multiple accrual methods and pharmacotherapy options predicted increased enrollment across trials. Enrollment rates were also greater among Blacks compared to Whites. The findings offer practical information for the implementation of cessation trials and interventions in the lung cancer screening context and other clinical settings, regarding intervention modalities that may be most appealing to older, long-term smokers. [ABSTRACT FROM AUTHOR]

Background: Guidelines recommend offering cessation interventions to smokers eligible for lung cancer screening, but there is little data comparing specific cessation approaches in this setting. We compared the benefits and costs of different smoking cessation interventions to help screening programs select specific cessation approaches.Methods: We conducted a societal-perspective cost-effectiveness analysis using a Cancer Intervention and Surveillance Modeling Network model simulating individuals born in 1960 over their lifetimes. Model inputs were derived from Medicare, national cancer registries, published studies, and micro-costing of cessation interventions. We modeled annual lung cancer screening following 2014 US Preventive Services Task Force guidelines plus cessation interventions offered to current smokers at first screen, including pharmacotherapy only or pharmacotherapy with electronic and/or web-based, telephone, individual, or group counseling. Outcomes included lung cancer cases and deaths, life-years saved, quality-adjusted life-years (QALYs) saved, costs, and incremental cost-effectiveness ratios.Results: Compared with screening alone, all cessation interventions decreased cases of and deaths from lung cancer. Compared incrementally, efficient cessation strategies included pharmacotherapy with either web-based cessation ($555 per QALY), telephone counseling ($7562 per QALY), or individual counseling ($35 531 per QALY). Cessation interventions continued to have costs per QALY well below accepted willingness to pay thresholds even with the lowest intervention effects and was more cost-effective in cohorts with higher smoking prevalence.Conclusion: All smoking cessation interventions delivered with lung cancer screening are likely to provide benefits at reasonable costs. Because the differences between approaches were small, the choice of intervention should be guided by practical concerns such as staff training and availability. [ABSTRACT FROM AUTHOR]

Introduction: In smoking cessation clinical trials, timeline followback (TLFB) interviews are widely used to track daily cigarette consumption. However, there are no standard tools for calculating abstinence based on TLFB data. Individual research groups have to develop their own calculation tools, which is not only time- and resource-consuming but might also lead to variability in the data processing and calculation procedures.Aims and Methods: To address these issues, we developed a novel open-source Python package named abstcal to calculate abstinence using TLFB data. This package provides data verification, duplicate and outlier detection, missing-data imputation, integration of biochemical verification data, and calculation of a variety of definitions of abstinence, including continuous, point-prevalence, and prolonged abstinence.Results: We verified the accuracy of the calculator using data derived from a clinical smoking cessation study. To improve the package's accessibility, we have made it available as a free web app.Conclusions: The abstcal package is a reliable abstinence calculator with open-source access, providing a shared validated online tool to the addiction research field. We expect that this open-source abstinence calculation tool will improve the rigor and reproducibility of smoking and addiction research by standardizing TLFB-based abstinence calculation.Implications: Abstinence calculation is an essential task in any smoking intervention study. However, there have not been standard open-source tools available to the researchers. This commentary describes a Python-based package called abstcal that can calculate abstinence from TLFB data, a common methodology to collect smoking consumption data in research settings. The package supports the calculation of point-prevalence, prolonged, and continuous abstinence. Importantly, the package has a web app interface that allows researchers to use the tool without any coding experience. This tool will facilitate smoking research by providing a standardized and easy-to-use abstinence calculation tool. [ABSTRACT FROM AUTHOR]

Introduction: Varenicline and bupropion are two effective smoking cessation pharmacotherapies. Researchers have hypothesized that they might be effective, in part, because they reduce cue reactivity and cue-induced cravings. Here, we used event-related potentials (ERPs) to directly measure brain responses to cigarette-related and other motivationally relevant images during a pharmacologically aided quit attempt.Methods: Smokers involved in a 12-week placebo-controlled double-blind clinical trial of smoking cessation medications (varenicline, bupropion, placebo) took part in the study. We assessed participants at two time points: 24 h (n = 140) and 4 weeks (n = 176) after the quit date. At both sessions, we measured the amplitude of the late positive potential (LPP), an ERP component reliably associated with motivational relevance, and self-reported tonic craving using the brief version of the Questionnaire of Smoking Urges (QSU-Brief).Results: At both sessions, emotional and cigarette-related images evoked significantly larger LPPs than neutral images. Neither drug type nor smoking abstinence altered this effect at either session. At both sessions, varenicline and bupropion significantly reduced self-reported tonic craving relative to the placebo condition.Conclusions: While both varenicline and bupropion reduced self-reported tonic craving, neither medication altered the amplitude of the LPP to cigarette-related or emotional pictures in smokers attempting to quit. These medications may influence abstinence by means other than by reducing neuroaffective responses to cigarette-related cues. Smokers should be prepared for the likelihood that even after several weeks of successful abstinence, once treatment ends, cigarette-related cues may remain motivationally relevant and trigger cravings that might lead to relapse.Implications: Bupropion and varenicline do not alter electrophysiological responses, as measured by the LPP, to cigarette-related and emotional images. These findings help explain why cigarette-related cues can trigger relapse when smoking cessation medication treatments end. [ABSTRACT FROM AUTHOR]

Neurobiological models of addiction posit that drug use can alter reward processes in two ways: (1) by increasing the motivational relevance of drugs and drug-related cues and (2) by reducing the motivational relevance of non-drug-related rewards. Here, we discuss the results from a series of neuroimaging studies in which we assessed the extent to which these hypotheses apply to nicotine dependence. In these studies, we recorded smokers’ and nonsmokers’ brain responses to a wide array of motivationally relevant visual stimuli that included pleasant, unpleasant, cigarette-related, and neutral images. Based on these findings, we highlight the flaws of the traditional cue reactivity paradigm and we conclude that responses to non-drug-related motivationally relevant stimuli should be used to appropriately gauge the motivational relevance of cigarette-related cues and to identify smokers attributing higher motivational relevance to drug-related cues than to non-drug-related rewards. Identifying these individuals is clinically relevant as they achieve lower rates of long-term smoking abstinence when attempting to quit. Finally, we show how this approach may be extended beyond nicotine dependence to inform theoretical and clinical research in the study of obesity.Implications: The cue reactivity paradigm (ie, comparing responses evoked by drug-related cues to those evoked by neutral cues) cannot provide conclusive information about the motivational relevance of drug-related cues. Responses to non-drug-related motivationally relevant stimuli should be used to appropriately gauge the level of motivational relevance that substance-dependent individuals attribute to drug-related cues. [ABSTRACT FROM AUTHOR]

Introduction: Smoking during pregnancy poses known risks to fetal and infant development. Women who continue to smoke during pregnancy exhibit higher levels of nicotine dependence than women who quit. Increased understanding of the construct of nicotine dependence in pregnant smokers may aid in the development of effective treatments. Research has suggested that nicotine dependence is a multifaceted construct, driven not only by withdrawal and tolerance processes, but also by reinforcement, sensory, and contextual processes. The Wisconsin inventory of smoking dependence motives (WISDM-68) assesses 13 varied smoking motives in order to assess processes that may lead to nicotine dependence. Methods: The factor structure of the WISDM-68 was explored using an ethnically diverse sample of 294 pregnant women who had been screened and/or enrolled in a smoking cessation treatment study. Confirmatory analyses were conducted with previously published models. An exploratory factor analysis and exploratory structural equation modeling (ESEM) were conducted to develop and validate a measurement model for the WISDM-68 in this sample. Results: Previously established models were not a good fit for the present data. Using ESEM, a 9-factor model exhibiting both predictive and concurrent validity emerged. Two factors predicted abstinence 6 months posttreatment. Several factors were associated with smoking heaviness, the Fagerström test for cigarette dependence and time to first cigarette. Conclusions: In contrast to previously published studies, a 9-factor model best characterizes the WISDM in the present sample. These findings may reflect smoking motivations unique to young, pregnant women who continue to smoke during pregnancy. [ABSTRACT FROM AUTHOR]