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Most individuals who try to quit smoking will not succeed even if they use evidence-based treatment. Qualitative methods can help identify cessation treatments' limitations and suggest adaptations to increase treatment success.Rapid qualitative analysis was conducted on data from 125 adults who smoked daily (48% female; 44% White) and participated in a smoking cessation trial and completed qualitative interviews 2 weeks prequit, reporting on changes they needed to make to quit, and 100 adults (50% female; 49% White) who completed a second interview 2 weeks postquit, reporting changes they had made.The anticipated changes reported prequit (in order of frequency) were as follows: identify smoking triggers (without a coping plan), focus on benefits of quitting, reduce exposure to others smoking, make other health changes, reduce exposure to nonsocial smoking cues, and reduce alcohol consumption. Many participants were unable to identify specific changes that would aid their cessation success. Changes reported postquit included the following: use the 4 D strategies (delay, drink water, deep breathing, distract), reduce exposure to nonsocial smoking cues, focus on benefits of quitting, change daily routine, make other health changes, reduce exposure to others smoking, and get support from loved ones. Most changes reported postquit were consistent with clinical practice guidelines; however, use of cessation medication was the least reported theme.Prior to quitting, over a third of participants were unable to identify changes to increase cessation success. Those who could focus on triggers and cues for smoking. Postquit, participants reported using cessation strategies encouraged during study cessation counseling. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

E-cigarette use (vaping) among adults has increased, and various patterns of concurrent smoking and vaping (i.e., "dual use") have emerged. Understanding dual use is important for mitigating tobacco-related harm. This narrative review summarizes recent research on dual use, including prevalence and types of dual use, sociodemographic and psychiatric characteristics, nicotine dependence, reasons for dual use, harm perceptions, toxicant exposure, trajectories of dual use, and emerging treatments for dual use.Nearly half of e-cigarette users concurrently use cigarettes, and many smoke more frequently than they use e-cigarettes. This is concerning because dual users are exposed to both cigarette and potential e-cigarette toxicants and the data are mixed regarding the ability of e-cigarettes to promote smoking cessation.Further work is needed to identify ways to increase complete smoking abstinence and optimize harm reduction among dual users, including strategies to encourage e-cigarette cessation after stopping smoking.

Introduction Cross-sectional surveys found behavioral heterogeneity among dual users of combustible and electronic cigarettes. Yet, prior classification did not reflect dynamic interactions between cigarette and e-cigarette consumption, which may reveal changes in product-specific dependence. The contexts of dual use that could inform intervention were also understudied. Methods This study conducted secondary analysis on 13 waves of data from 227 dual users who participated in a 2-year observational study. The k-means method for joint trajectories of cigarette and e-cigarette consumption was adopted to identify the subtypes of dual users. The time-varying effect model was used to characterize the subtype-specific trajectories of cigarette and e-cigarette dependence. The subtypes were also compared in terms of use contexts. Results The four clusters were identified: light dual users, predominant vapers, heavy dual users, and predominant smokers. Although heavy dual users and predominant smokers both smoked heavily at baseline, by maintaining vaping at the weekly to daily level the heavy dual users were able to considerably reduce cigarette use. Yet, the heavy dual users’ drop in cigarette dependence was not as dramatic as their drop in cigarette consumption. Predominant vapers appeared to engage in substitution, as they decreased their smoking and increased their e-cigarette dependence. They were also more likely to live in environments with smoking restrictions and report that their use of e-cigarettes reduced cigarette craving and smoking frequency. Conclusions Environmental constraints can drive substitution behavior and the substitution behavior is able to be sustained if people find the substitute to be effective. Implications This study characterizes subtypes of dual users based on the dynamic interactions between cigarette use and e-cigarette use as well as product-specific trajectories of dependence. The subtypes differ in not only sociodemographic characteristics but also contexts of cigarette and e-cigarette use. Higher motivation to use e-cigarettes to quit smoking and less permissive environment for smoking may promote substitution of cigarettes by e-cigarettes.

OBJECTIVE: To examine dependence on combustible and e-cigarettes among users of both products (dual users), which may provide important insights into long-term use patterns. METHODS: Dual users (smoking daily for 3 months, using e-cigarettes at least once/week for the past month; N=256; 45% women, 71% White, mean age 39.0 years) not interested in quitting either product, participated in a longitudinal, 2-year, observational study. At baseline, participants completed measures of combustible and e-cigarette dependence (Fagerstrom Test of Cigarette Dependence [FTCD], e-FTCD, Wisconsin Inventory of Smoking Dependence Motives [WISDM], e-WISDM, Penn State Cigarette Dependence Index [PS-CDI], and PS-ECDI) and carried a study smartphone for 2 weeks to record cigarette and e-cigarette use events. RESULTS: Most measures of dependence were product specific (e.g., FTCD and e-FTCD were not correlated, r=−0.003) and predicted product-specific outcomes (e.g., long-term use of that product). However, individuals used the two products for some of the same secondary dependence motives (e.g., weight control, cognitive and affective enhancement). These secondary, or instrumental, motives predicted use of both products at 1 year. Which product was used first in the morning was strongly related to product dependence scores and likelihood of continued product use at 1 year. CONCLUSIONS: Amongst dual users of combustible and e-cigarettes, measures of e-cigarette and cigarette dependence tended to be unrelated to one another but dual users tended to use both products for the same instrumental motives. Which product is used first in the morning may serve as a valuable measure of relative dependence on the two products. PUBLIC HEALTH SIGNIFICANCE: This study illustrates that dependence on combustible and electronic cigarettes may not be related among adults who both smoke and vape. Which product they use first thing after they wake up indicates which product they are more dependent upon.

The increase in the use of mobile and wearable devices now allows dense assessment of mediating processes over time. For example, a pharmacological intervention may have an effect on smoking cessation via reductions in momentary withdrawal symptoms. We define and identify the causal direct and indirect effects in terms of potential outcomes on the mean difference and odds ratio scales, and present a method for estimating and testing the indirect effect of a randomized treatment on a distal binary variable as mediated by the nonparametric trajectory of an intensively measured longitudinal variable (e.g., from ecological momentary assessment). Coverage of a bootstrap test for the indirect effect is demonstrated via simulation. An empirical example is presented based on estimating later smoking abstinence from patterns of craving during smoking cessation treatment. We provide an R package, funmediation, available on CRAN, to conveniently apply this technique. We conclude by discussing possible extensions to multiple mediators and directions for future research., 50 pgs., 4 figures

AIMS To understand dual users' cigarette and e-cigarette use patterns including the contexts in which they vape vs smoke and to understand how environmental and internal contexts and smoking patterns differ between dual users and exclusive smokers. DESIGN Longitudinal observational trial. SETTING Research center in Wisconsin, USA. PARTICIPANTS Adult dual users (n=162) and adults who exclusively smoked (n=143), with no plans to quit smoking or vaping in the next 30 days MEASUREMENTS: Participants carried smartphones for 2 weeks at baseline to record each use event for the two products and report on the context of their product use. Percent of mornings where participants vaped first vs. smoked were used to compute e-cigarette dependence. FINDINGS Hierarchical linear regression models with random slopes and intercepts examined the within- and between-subject effects of context on the likelihood of vaping (vs. smoking); significant fixed effects were tested for moderation by e-cigarette dependence. Dual users reported significantly more puffs/cigarette (mean (M)=13.1, standard deviation (SD)=10.2) than puffs/vape event (M=11.7, SD=11.5; p=0.01). E-cigarette dependence moderated the influence of social cues (t-ratio=2.4, p=0.02) and smoking restrictions (t-ratio=3.1, p=0.003) on the likelihood of vaping versus smoking (odds ratio (OR)=2.30, p=0.02). Context was more related to which product was used in those of low versus higher e-cigarette dependence. Reports of strong cravings to smoke and positive expectancies for cigarettes were associated with reduced likelihood of vaping whereas strong cravings to vape and positive vaping expectancies were related to increased likelihood of vaping. CONCLUSIONS Among dual users of cigarettes and e-cigarettes with no motivation to quit, vaping appears to be related to internal cues and more highly linked with social contexts and smoking restrictions (i.e., under stronger external stimulus control) among those with low to moderate e-cigarette dependence compared with high e-cigarette dependence. These findings illustrate the importance of contextual factors in tobacco product use amongst dual users with the influence of context being reduced at high levels of e-cigarette dependence.

BACKGROUND Tobacco smoking is a major independent risk factor for chronic disease, and the prevalence of smoking among people with behavioral health disorders is 2-fold in comparison with the general population. Smoking rates remain high for various subgroups within the Latine community, the largest ethnic minority group in the United States. Acceptance and commitment therapy (ACT) is a theoretically sound and clinically validated therapeutic approach for several behavioral health conditions with growing evidence of its effectiveness for smoking cessation. Unfortunately, the evidence of ACT effectiveness for smoking cessation among Latine individuals is scarce, and none of the existing studies have tested a culturally targeted intervention for this population. OBJECTIVE This study aims to address the co-occurrence of smoking and mood-related challenges among Latine adults via the development and testing of a culturally tailored ACT-based wellness program: Project PRESENT. METHODS This study entails 2 phases. Phase 1 consists of the intervention development. Phase 2 entails the pilot testing of the behavioral intervention along with the administration of baseline and follow-up measures to 38 participants. Primary outcomes include feasibility of recruitment and retention, and treatment acceptability. Secondary outcomes are smoking status and depression and anxiety scores at end of treatment and 1-month follow-up. RESULTS This study received institutional review board approval. Phase 1 outputs were the health counselors’ treatment manual and participant guide. Recruitment was completed in 2021. Phase 2 outcomes will be determined after project implementation and data analyses are complete, which are expected by May 2023. CONCLUSIONS Findings from this study will determine the feasibility and acceptability of an ACT-based, culturally relevant intervention for Latine adults who smoke and have probable depression and/or anxiety. We expect feasibility of recruitment, retention and treatment acceptability, and reductions in smoking status, depression, and anxiety. If feasible and acceptable, the study will inform large-scale trials, which will ultimately contribute to narrowing the gap between research and clinical practice for the co-occurrence of smoking and psychological distress among Latine adults. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/44146

Tobacco smoking imposes a staggering burden on public health, underscoring the urgency of developing a deeper understanding of the processes that maintain addiction. Clinical and experience-sampling data highlight the importance of anxious withdrawal symptoms, but the underlying neurobiology has remained elusive. Work in animals implicates the central extended amygdala (EAc), but the translational relevance of these discoveries remains speculative. Here we leveraged a randomized trial design, well-established threat-anticipation paradigm, and multidimensional battery of assessments to understand the consequences of 24-hour nicotine abstinence. The threat-anticipation paradigm had the expected consequences, amplifying subjective distress and arousal, and recruiting the canonical threat-anticipation network. Abstinence increased smoking urges and withdrawal symptoms, and potentiated threat-evoked distress, but had negligible consequences for EAc threat reactivity, raising questions about the translational relevance of prominent animal and human models of addiction. These observations provide a framework for conceptualizing nicotine abstinence and withdrawal, with implications for basic, translational, and clinical science.

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.

OBJECTIVE Recognizing smoking as a risk factor for rheumatoid arthritis (RA) severity, the present study was undertaken to evaluate patient- and health care-level predictors of smoking cessation in patients with RA to guide implementation of smoking cessation interventions. METHODS Electronic health record data from 2 health systems were abstracted for patients with at least 2 International Classification of Disease diagnosis codes for RA between 2005 and 2016. Patients missing smoking statuses or with

Background: To fully characterize the risk for dementia associated with cigarette smoking, studies must consider competing risks that hinder the observation of dementia or modify the chance that dementia occurs (i.e., death). Extant research examining the competing risks fails to account for the occurrence of death following dementia, limiting our understanding of the relation between smoking and dementia. Objective: Examine the impact of smoking status, lifetime smoking exposure, and duration of abstinence on incident dementia, death following dementia, and death without dementia. Methods: Multi-state models estimated hazard ratios (HR) for 95% confidence interval (CI) of 10,681 cognitively healthy adults for transition from baseline to dementia, baseline to death, and dementia to death based on smoking status, lifetime cigarette exposure, and abstinence duration. Results: Compared to never smokers, current smokers had increased risk of dementia (HR = 1.66; 95% CI 1.18– 2.32; p = 0.004), and death from baseline (HR = 2.98; 95% CI 2.24– 3.98; p

Introduction Existing e-cigarette dependence scales are mainly validated based on retrospective overall consumption or perception. Further, given that the majority of adult e-cigarette users also use combustible cigarettes, it is important to determine whether e-cigarette dependence scales capture the product-specific dependence. This study fills in the current knowledge gaps by validating e-cigarette dependence scales using novel indices of dynamic patterns of e-cigarette use behaviors and examining the association between dynamic patterns of smoking and e-cigarette dependence among dual users. Methods Secondary analysis was conducted on the 2-week ecological momentary assessment data from 116 dual users. The Smoothly Clipped Absolute Deviation penalty (SCAD) was adopted to select important indices for dynamic patterns of consumption or craving and estimate their associations with e-cigarette dependence scales. Results The fitted linear regression models support the hypothesis that higher e-cigarette dependence is associated with higher levels of e-cigarette consumption and craving as well as lower instability of e-cigarette consumption. Controlling for dynamic patterns of vaping, dual users with lower e-cigarette dependence tend to report higher day-to-day dramatic changes in combustible cigarette consumption but not higher average levels of smoking. Conclusions We found that more stable use patterns are related to higher levels of dependence, which has been demonstrated in combustible cigarettes and we have now illustrated in e-cigarettes. Furthermore, the e-cigarette dependence scales may capture the product-specific average consumption but not product-specific instability of consumption. Implications This study provides empirical support for three e-cigarette dependence measures: PS-ECDI, e-FTCD, and e-WISDM, based on dynamic patterns of e-cigarette consumption and craving revealed by EMA data that have great ecological validity. This is the first study that introduces novel indices of dynamic patterns and demonstrates their potential applications in vaping research.

The assessment of tobacco withdrawal is important for both research and clinical purposes. This study describes the psychometric development of a revised version of the 28-item Wisconsin Smoking Withdrawal Scale (WSWS; Welsch et al., Experimental and Clinical Psychopharmacology, 1999, 7, p. 354). Because the different contexts of use sometimes permit only brief assessment, this revision has produced both a brief and longer form using an updated pool of candidate items. For the revised Wisconsin Smoking Withdrawal Scale 2 (WSWS2), a candidate pool of 37 items was developed to measure nine putative withdrawal constructs. The stem and wording of items were revised as was the response scale. Data for psychometric analyses were derived from three smoking cessation randomized clinical trials conducted at the University of Wisconsin Center for Tobacco Research and Intervention. Dimensionality, internal consistency, and item characteristic analyses of the candidate items were conducted in a derivation sample to ascertain the factor structure and to identify items that could be used in the WSWS2 scales. Confirmatory factor analyses (CFAs) of reduced item sets and factor structure were conducted in two validation samples along with reliability and validity analyses. Derivation and validation sample analyses yielded a longer version of the WSWS2 (WSWS2-L) with 19 items and six subscales (Craving, Negative Affect, Hunger, Sleep, Restlessness, and Concentration) and a brief 6-item version (WSWS2-B). In validation sample analyses, both the WSWS2-L and the WSWS2-B demonstrated good reliability and validity as well as good fit in CFAs. The WSWS2-L and WSWS2-B possess improved construct coverage, fewer items, and other enhancements relative to the WSWS. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Background Tobacco smoking is a major independent risk factor for chronic disease, and the prevalence of smoking among people with behavioral health disorders is 2-fold in comparison with the general population. Smoking rates remain high for various subgroups within the Latine community, the largest ethnic minority group in the United States. Acceptance and commitment therapy (ACT) is a theoretically sound and clinically validated therapeutic approach for several behavioral health conditions with growing evidence of its effectiveness for smoking cessation. Unfortunately, the evidence of ACT effectiveness for smoking cessation among Latine individuals is scarce, and none of the existing studies have tested a culturally targeted intervention for this population. Objective This study aims to address the co-occurrence of smoking and mood-related challenges among Latine adults via the development and testing of a culturally tailored ACT-based wellness program: Project PRESENT. Methods This study entails 2 phases. Phase 1 consists of the intervention development. Phase 2 entails the pilot testing of the behavioral intervention along with the administration of baseline and follow-up measures to 38 participants. Primary outcomes include feasibility of recruitment and retention, and treatment acceptability. Secondary outcomes are smoking status and depression and anxiety scores at end of treatment and 1-month follow-up. Results This study received institutional review board approval. Phase 1 outputs were the health counselors’ treatment manual and participant guide. Recruitment was completed in 2021. Phase 2 outcomes will be determined after project implementation and data analyses are complete, which are expected by May 2023. Conclusions Findings from this study will determine the feasibility and acceptability of an ACT-based, culturally relevant intervention for Latine adults who smoke and have probable depression and/or anxiety. We expect feasibility of recruitment, retention and treatment acceptability, and reductions in smoking status, depression, and anxiety. If feasible and acceptable, the study will inform large-scale trials, which will ultimately contribute to narrowing the gap between research and clinical practice for the co-occurrence of smoking and psychological distress among Latine adults. International Registered Report Identifier (IRRID) DERR1-10.2196/44146

ObjectiveThe current study examined indicators of dependence among youth cigarette smokers and e-cigarette users in Canada, England and the USA, including changes between 2017 and 2019.MethodsData are from repeated cross-sectional online surveys conducted in 2017, 2018 and 2019 with national samples of youth aged 16–19 years, in Canada (n=12 018), England (n=11 362) and the USA (n=12 110). Measures included perceived addiction to cigarettes/e-cigarettes, frequency of experiencing strong urges to smoke/use an e-cigarette, plans to quit smoking/using e-cigarettes and past attempts to quit. Logistic regression models were fitted to examine differences between countries and changes over time.ResultsThe proportion of ever-users who vaped frequently was significantly higher in 2019 compared with 2017 for all outcomes in each country. Between 2017 and 2019, the proportion of past 30-day vapers reporting strong urges to vape on most days or more often increased in each country (Canada: 35.3%, adjusted OR (AOR) 1.69, 95% CI 1.20 to 2.38; England: 32.8%, AOR 1.55, 1.08 to 2.23; USA: 46.1%, AOR 1.88, 1.41 to 2.50), along with perceptions of being ‘a little’ or ‘very addicted’ to e-cigarettes (Canada: 48.3%, AOR 1.99, 1.44 to 2.75; England: 40.1%, AOR 1.44, 1.03 to 2.01; USA: 53.1%, AOR 1.99, 1.50 to 2.63). Indicators of dependence among smokers were consistently greater than e-cigarette users, although differences had narrowed by 2019, particularly in Canada and the USA.ConclusionsPrevalence of dependence symptoms among young e-cigarette users increased between 2017 and 2019, more so in Canada and the USA compared with England. Dependence symptom prevalence was lower for e-cigarettes than smoking; however, the gap has narrowed over time.

A recently developed network perspective on tobacco withdrawal posits that withdrawal symptoms causally influence one another across time, rather than simply being indicators of a latent syndrome. Evidence supporting a network perspective would shift the focus of tobacco withdrawal research and intervention toward studying and treating individual withdrawal symptoms and intersymptom associations. Here we construct and examine temporal tobacco withdrawal networks that describe the interplay among withdrawal symptoms across time using experience-sampling data from 1,210 participants (58.35% female, 86.24% White) undergoing smoking cessation treatment. We also construct person-specific withdrawal networks and capture individual differences in the extent to which withdrawal symptom networks promote the spread of symptom activity through the network across time using impulse response analysis. Results indicate substantial moment-to-moment associations among withdrawal symptoms, substantial between-person differences in withdrawal network structure, and reductions in the interplay among withdrawal symptoms during combination smoking cessation treatment. Overall, findings suggest the utility of a network perspective and also highlight challenges associated with the network approach stemming from vast between-person differences in symptom networks. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Introduction It is uncertain whether e-cigarettes facilitate smoking cessation in the real world. We aimed to understand whether and how transitions among cigarette, e-cigarette, and dual use are associated with sociodemographics, dependence measures, and biomarkers. Aims and Methods We followed 380 adult daily cigarette users and dual users every 2 months for up to 2 years. We estimated transition rates between noncurrent, cigarette-only, e-cigarette-only, and dual use states using a multistate transition model. We estimated univariable hazard ratios (HR) for demographics, dependence measures for cigarettes and e-cigarettes, biomarkers, spousal or partner behaviors, and other measures. Results We estimated that participants transitioned from cigarette-only to e-cigarette-only through a period of dual use. Dual users ceased smoking (transitioning to e-cigarette-only use) at a greater rate than cigarette-only users did (HR 2.44, 95% CI: 1.49, 4.02). However, of the 60% of dual users estimated to transition to single product use in 1 year, 83% would transition to cigarette-only use and only 17% to e-cigarette-only use. E-cigarette dependence measures were generally associated with reduced e-cigarette cessation rather than enhanced cigarette cessation. E-cigarette users motivated by harm or toxicity reduction or because of restrictions on where or when they could smoke had reduced rates of smoking relapse. Cigarette dependence and spousal smoking were barriers to cigarette cessation for dual users, while using e-cigarettes first in the morning, motivation to quit smoking, and sensory, social, and emotional enjoyment of e-cigarettes (secondary dependence motives) were facilitators of smoking cessation among dual users. Conclusions Tobacco control policy and interventions may be informed by the barriers and facilitators of product transitions. Implications Although e-cigarettes have the potential to promote smoking cessation, their real-world impact is uncertain. In this cohort, dual users were more likely to quit smoking than cigarette-only users, but the overall impact was small because most dual users returned to cigarette-only use. Moreover, e-cigarette dependence promoted continued dual use rather than smoking cessation. Yet, high motivation to quit smoking and the sensory, social, and emotional enjoyment of e-cigarettes facilitated smoking cessation in dual users. Better understanding the barriers and facilitators of transitions can help to develop regulations and interventions that lead to more effective use of e-cigarettes for smoking cessation.

Tobacco smoking is a major determinant of preventable morbidity and mortality worldwide. More than a billion people smoke, and without major increases in cessation, at least half will die prematurely from tobacco-related complications. In addition, people who smoke have a significant reduction in their quality of life. Neurobiological findings have identified the mechanisms by which nicotine in tobacco affects the brain reward system and causes addiction. These brain changes contribute to the maintenance of nicotine or tobacco use despite knowledge of its negative consequences, a hallmark of addiction. Effective approaches to screen, prevent and treat tobacco use can be widely implemented to limit tobacco's effect on individuals and society. The effectiveness of psychosocial and pharmacological interventions in helping people quit smoking has been demonstrated. As the majority of people who smoke ultimately relapse, it is important to enhance the reach of available interventions and to continue to develop novel interventions. These efforts associated with innovative policy regulations (aimed at reducing nicotine content or eliminating tobacco products) have the potential to reduce the prevalence of tobacco and nicotine use and their enormous adverse impact on population health.

AIMS To identify when smoking cessation treatments affect craving, negative affect and anhedonia, and how these symptoms relate to abstinence, to help evaluate the effects of particular intervention components in multi-component treatments and accelerate treatment refinement. DESIGN Secondary analysis of data from a two-arm randomized controlled trial. SETTING Seven primary care clinics in Wisconsin, United States. PARTICIPANTS Adult primary care patients who smoked daily (n = 574). INTERVENTION AND COMPARATOR Intervention was abstinence-optimized treatment (A-OT, n = 276) comprising 3 weeks of nicotine mini-lozenges pre-target quit day (TQD), 26 weeks of combination nicotine patch and mini-lozenges post-TQD and extensive psychosocial support. The comparator was recommended usual care (RUC, n = 298), comprising brief counseling and 8 weeks of nicotine patch post-TQD. MEASUREMENTS Time-varying effect models examined dynamic effects of A-OT (versus RUC) on the primary outcomes of nightly cigarette craving, negative affect and anhedonia from 1 week pre- to 2 weeks post-TQD. Exploratory models examined within-person relations between nicotine medication use and same-day symptom ratings. Secondary logistic regression analyses examined associations between post-TQD craving, negative affect and anhedonia and 1-month post-TQD abstinence. FINDINGS A-OT significantly suppressed pre- and post-TQD craving (β = -0.27 to -0.46 across days) and post-TQD anhedonia (β = -0.24 to -0.38 across days), relative to RUC. Within individuals, using patches was associated with lower negative affect in RUC (β = -0.42 to -0.52), but not in A-OT. Using more mini-lozenges was associated with greater craving (β = 0.04-0.07) and negative affect (β = 0.03-0.05) early, and with lower anhedonia (β = -0.06 to -0.12) later. Greater post-TQD craving (OR = 0.68) and anhedonia (OR = 0.85) predicted lower odds of abstinence 1 month post-TQD. CONCLUSION Time-varying effect models showed that a multi-component treatment intervention for smoking cessation suppressed significant withdrawal symptoms more effectively than recommended usual care among daily adult smokers motivated to quit. The intervention reduced craving pre- and post-target quit day (TQD) and anhedonia post-TQD.

BACKGROUND AND AIMS The phase-based model of smoking cessation treatment suggests that treatment needs may vary across phases (e.g. pre-cessation, cessation). This study tested the comparative effects of varenicline and combination nicotine replacement therapy (C-NRT) relative to nicotine patch monotherapy on pre-cessation and cessation phase candidate withdrawal, expectancy and motivation mediators; relations between mediators and abstinence; and indirect effects of enhanced treatments on abstinence via candidate mediators. DESIGN Secondary mediation analysis of data from the open-label, randomized Wisconsin Smokers' Health Study 2, a comparative effectiveness trial of varenicline or C-NRT, versus patch monotherapy, in adults who smoked, recruited via media and community outreach. SETTING Research clinics in Madison and Milwaukee, Wisconsin, USA. PARTICIPANTS A total of 1051 daily smokers motivated to quit smoking (52.5% female; mean age = 48.1, standard deviation = 11.6). INTERVENTIONS Twelve weeks of varenicline (n = 407) or 12 weeks of combination nicotine patch and nicotine lozenge therapy (n = 421), both compared with 12 weeks of patch control condition (n = 230), with individual smoking cessation counseling. MEASUREMENTS The primary abstinence outcome was biochemically verified 7-day point-prevalence abstinence 4 weeks post-target quit day (TQD). Candidate mediators (craving, positive smoking expectancies, withdrawal symptoms, and quitting motivation) were assessed via ecological momentary assessment from 1 week prior (pre-cessation phase) to 4 weeks after (cessation phase) the TQD. FINDINGS Pre-cessation and cessation mean levels and slopes of craving [adjusted odds ratio (aOR) = 0.34-0.79], smoking expectancies (aOR = 0.46-0.79) and quitting motivation (aOR = 1.35-7.21) significantly predicted 4-week post-TQD abstinence (P

Introduction Greater use of nicotine replacement therapy (NRT) is related to smoking cessation success, but the causal direction is unclear. This study characterized the relationship between NRT use and smoking lapse and relapse. Methods Participants (N = 416 smokers; 57% female, 85% White) were recruited from primary care for a smoking cessation factorial experiment and analyzed if abstaining ≥1 day in the first 2 weeks post-target quit day (TQD). Participants were randomized to counseling and 8 versus 26 weeks of nicotine patch plus nicotine gum post-TQD. Participants carried electronic dispensers that timestamped each gum use. Participants who lapsed (smoked after abstaining) within 6 weeks post-TQD were matched with nonlapsers (n = 146 pairs) on multiple variables. We compared lapsers’ versus matched nonlapsers’ gum use in the 5 days before and after the lapsers’ first lapse. Results By week 6 post-TQD, 63% of participants lapsed. Compared with nonlapsers, lapsers used less gum 1 and 2 days pre-“lapse” and on the 5 days post-lapse. Lapsers used less gum during the 5 days post-lapse than the 5 days pre-lapse. Univariate survival analyses with lapsers showed greater gum use during both pre- and post-lapse periods predicted longer latency to relapse in the first 6 weeks. Conclusions In a smoking cessation attempt using nicotine patch plus gum, lapsers versus matched nonlapsers used less gum immediately preceding and following their first lapse. Lower mean gum use before and after lapses predicted a more rapid escalation to relapse. Decreased nicotine gum use both precedes and follows returns to smoking during cessation attempts. Implications This research examined electronically monitored nicotine gum use collected in real time and found that among smokers engaged in a quit attempt, lapsers (vs. matched nonlapsers) tended to decrease their gum use 1–2 days prior to lapsing and to further decrease their gum use from pre- to post-lapse. Decreased gum use pre-lapse may signal heightened lapse risk in 1–2 days, with lower level of gum use predicting a more precipitous course of relapse. These results encourage further exploration of objective measures of smoking medication use patterns to examine their signaling properties and to inform understanding of cessation failure. Clinical Trial Registration ClinicalTrials.gov NCT01120704.

Introduction Most people who smoke cigarettes are not willing (ie, not ready) to make a quit attempt (QA) at any given time. Unfortunately, interventions intended to increase QAs and the success of QAs are only modestly effective. Identifying processes leading to QAs and quitting success could guide intervention development. Aims and Methods This is a secondary analysis of a randomized factorial trial of 6 weeks of motivation-phase interventions among primary care patients (N = 517) who were initially unwilling to quit but were willing to reduce their smoking. Using logistic regression, we controlled for treatment condition and tested whether baseline or change in smoking-related constructs after 6 weeks of treatment predicted (1) making an at least 24 h QA between weeks 6 and 26 and (2) quitting success at week 26 (7-day point-prevalence abstinence among those who made a QA). Predictors included cigarettes/day, time to first cigarette, motivation to quit, quitting self-efficacy, anticipated urges to smoke if quit, positive affect, negative affect, and time spent around others who smoke. Results In multivariable models that included all smoking-related constructs, changes in the following variables predicted initiating a QA above and beyond other variables: greater baseline time to first cigarette (odds ratio [OR] = 1.60), increases in time to first cigarette (OR = 1.27), and increases in quitting self-efficacy (OR = 1.14). Increased motivation to quit predicted conversion of a QA into quitting success at 26 weeks (OR = 1.36). Conclusion Predictors of making a QA differed from predictors of quitting success. Predictors of QAs and success could each serve as important treatment targets of motivation-phase interventions. Implications Motivation-phase interventions for people initially unwilling to quit smoking cigarettes may be improved by striving to increase their (1) time to first cigarette and quitting self-efficacy to promote QAs and (2) motivation to quit to promote quit success. Future experimental tests of such interventions are needed to identify causal determinants of QAs and quitting success.

Understanding the co-use of e-cigarettes and alcohol, including the situational contexts and subjective effects associated with co-use in real-time is necessary for validating this behavior and informing intervention. Yet, the sparse literature has built upon retrospective data.This study recruited 686 college students who were currently using e-cigarettes from three campuses in the Midwest and South of U.S in Fall 2019-Fall 2021. An on-line survey was conducted to measure e-cigarette use patterns, GPA, e-cigarette and alcohol dependence symptoms, and respiratory symptoms. A 7-day ecological momentary assessment was used to collect real-time data on e-cigarette and alcohol use, situational contexts and subjective effects.Frequent drinking e-cigarette users reported more high-risk use behavior including consuming 6 + drinks/occasion and simultaneous use, and reported more e-cigarettes and alcohol related dependence symptoms and respiratory symptoms, compared to infrequent/non-drinker e-cigarette users. Alcohol quantity was positively associated with e-cigarette quantity among the high frequency drinking group. This study identified important use contexts that were associated with higher e-cigarette consumption including use of menthol or fruit flavored e-cigarettes, being in a car, and the presence of others. E-cigarette use and alcohol use both increased the levels of positive affect, physiological sensation, and craving for e-cigarettes, whereas only alcohol use significantly decreased negative affect. No interaction effects between e-cigarette use and alcohol use were found.The findings highlight the addiction and health risks associated with frequent co-use of e-cigarettes and alcohol, and also call for regulations on nontobacco flavorings in e-cigarette products.

Aims To investigate how strongly smoking dependence and smoking dependence motives are associated with depressive symptoms among daily smokers and if these associations are independent of measured confounders and shared familial factors. Design Cross-sectional individual-based and within-pair analyses. Setting Fourth wave of the population-based Finnish Twin Cohort conducted in 2011. Participants 918 daily smokers born 1945-1957 (48% men), mean age 59.5 years including 38 twin pairs discordant for depression. Measurements Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression scale with a cut off value >= 20 for depression. Smoking dependence was assessed using the Fagerstrom Test for Cigarette Dependence (FTCD) and smoking dependence motives with three subscales from the multi-dimensional Brief Wisconsin Inventory of Smoking Dependence Motives (WISDM): primary dependence motives (PDM), affective enhancement (AE), and Taste. Logistic regressions, using standardized scores of independent variables and adjusted for multiple confounders with correction for sampling as twin pairs, were used in the individual-based analyses. Conditional logistic regression was used to control for shared familial factors in discordant twin pairs. Findings Prevalence of depression was 18% (n = 163: 61 [14%] in men, n = 102 [22%] in women). Higher smoking dependence measured by the FTCD (OR 1.45; 95% CI 1.20, 1.75), and dependence motives measured by the PDM (1.56; 1.30, 1.87) and the AE (1.54; 1.28, 1.85) were associated with higher odds of depression. The associations remained after adjusting for individual confounders, except for neuroticism, which attenuated all associations. FTCD, PDM, and AE showed associations with depression within depression-discordant monozygotic pairs, suggesting an association independent of familial factors. Conclusions Depression appears to be associated with smoking dependence and smoking dependence motives related to heavy, automatic use and use to regulate affective states. The associations appear to be confounded or mediated by neuroticism but are independent of shared familial influences.

Background Traditional mediation analysis typically examines the relations among an intervention, a time-invariant mediator, and a time-invariant outcome variable. Although there may be a total effect of the intervention on the outcome, there is a need to understand the process by which the intervention affects the outcome (i.e., the indirect effect through the mediator). This indirect effect is frequently assumed to be time-invariant. With improvements in data collection technology, it is possible to obtain repeated assessments over time resulting in intensive longitudinal data. This calls for an extension of traditional mediation analysis to incorporate time-varying variables as well as time-varying effects. Methods We focus on estimation and inference for the time-varying mediation model, which allows mediation effects to vary as a function of time. We propose a two-step approach to estimate the time-varying mediation effect. Moreover, we use a simulation-based approach to derive the corresponding point-wise confidence band for the time-varying mediation effect. Results Simulation studies show that the proposed procedures perform well when comparing the confidence band and the true underlying model. We further apply the proposed model and the statistical inference procedure to data collected from a smoking cessation study. Conclusions We present a model for estimating time-varying mediation effects that allows both time-varying outcomes and mediators. Simulation-based inference is also proposed and implemented in a user-friendly R package.

Introduction The addictive nature of nicotine makes smoking cessation an extremely challenging process. With prolonged exposure, tobacco smoking transforms from being a positive reinforcer to a negative one, as smoking is used to mitigate aversive withdrawal symptoms. Studying the variations in withdrawal symptoms, especially during their peak in the first week of a quit attempt, could help improve cessation treatment for the future. The time-varying mediation model effectively studies whether altering withdrawal symptoms act as mediators in the pathway between treatment and cessation. Aims and Methods This secondary data analysis of a randomized clinical smoking cessation trial of three pharmacotherapy regimens (nicotine patch, varenicline, and nicotine patch + mini-lozenge) analyzes ecological momentary assessment (EMA) data from the first 4 weeks post-target quit day (TQD). We assess whether withdrawal symptoms (eg, negative mood, cessation fatigue, and craving) mediate the pathway between pharmacotherapy and daily smoking status and whether this effect varies over time. Results We found a statistically significant time-varying mediation effect of varenicline on smoking status through craving, which shows decreasing risk of lapse via reduction in craving. We did not find significant time-varying mediation effects through negative mood and cessation fatigue. Conclusions This study supports the importance of craving suppression in the smoking cessation process. It also helped identify specific timepoints when withdrawal symptoms increased that would likely benefit from targeted cessation intervention strategies. Implications This study aimed to understand the underlying dynamic mechanisms of the smoking cessation process using a new analytical approach that capitalizes on the intensive longitudinal data collected via EMAs. The findings from this study further elucidate the smoking cessation process and provide insight into behavioral intervention targets and the timing of such interventions through the estimation of time-varying mediation effects.

This commentary addresses critical questions regarding the impact of the reduction of nicotine on changes in smoking behavior. There appears to be moderate evidence that use of reduced nicotine cigarettes (RNC) increases the likelihood of making a quit attempt among smokers unmotivated to quit and among smokers motivated to quit who also used nicotine replacement therapy (NRT). There was limited evidence that RNC combined with NRT increased smoking abstinence, regardless of motivation to quit. Several plausible mechanisms via which RNC may influence smoking behavior, including reducing dependence, are reviewed. The moderate evidence that abrupt reduction in nicotine reduces self-reported dependence as well as smoking behavior and likelihood of relapse is also reviewed. The data reviewed here suggest that abrupt switching to, and extended use of, RNC can reduce cigarette dependence and several related constructs, including the ability to quit smoking. The data reviewed in this commentary suggest that abrupt reduction in the level of nicotine in combustible cigarettes could reduce smoking behavior, nicotine dependence, and other related constructs and increase quit attempts and eventual smoking cessation.

Carotid artery grayscale ultrasound echogenicity and texture features predict cardiovascular disease events. We evaluated the longitudinal effects of smoking cessation on four grayscale ultrasound measures. This was a secondary analysis of data from 188 age, sex, and body mass index (BMI)-matched smokers (94 eventual abstainers [EA], 94 continued smokers [CS]) from a smoking cessation trial that had carotid ultrasound examinations at baseline and after 3 years. General linear models that included time, smoking group (EA or CS), and a time*smoking interaction term were used to examine the impact of smoking abstinence on carotid artery grayscale marker values at year 3. Participants were mean (SD) 50.3 (11.4) years old (57% female, 86% white). The baseline grayscale median value (GSM) was inversely correlated with age, BMI, insulin resistance, and smoking pack-years ( r = −0.20 to –0.30, p < 0.007 for all). There was a significant time*smoking status interaction for predicting GSM at year 3: GSM decreased significantly in the EA group compared to the CS group (–3.63 [13.00] vs CS 0.39 [12.06] units; p = 0.029). BMI increased more in the EA than the CS group (2.42 [3.00] vs CS 0.35 [2.57] kg/m2; p < 0.001). After adjusting for changes in BMI, the time*smoking status interaction no longer was significant ( p = 0.138). From baseline to year 3, contrast increased similarly in both groups. Entropy and angular second moment did not change significantly in either group. Changes in carotid ultrasound echogenicity and grayscale texture features during a smoking cessation attempt are modest and mostly related to weight gain. Clinicaltrials.gov Identifier: NCT01553084

BACKGROUND: Smoking reduction treatment is a promising approach to increase abstinence amongst smokers initially unwilling to quit. However, little is known about which reduction treatment elements increase quit attempts and the uptake of cessation treatment amongst such smokers. METHODS: This study is a secondary analysis of a 4-factor randomized factorial experiment conducted amongst primary care patients (N=517) presenting for regular healthcare visits in Southern Wisconsin who were unwilling to quit smoking but willing to cut down. We evaluated the main and interactive effects of Motivation-phase intervention components on whether participants: 1) made a quit attempt (intentional abstinence ≥ 24 hours) by 6- and 26- weeks post-study enrollment and, 2) used cessation treatment. We also evaluated the relations of quit attempts with abstinence. The four intervention components evaluated were: 1) Nicotine Patch vs. None; 2) Nicotine Gum vs. None; 3) Motivational Interviewing (MI) vs. None; and 4) Behavioral Reduction Counseling (BR) vs. None. Intervention components were administered over 6 weeks, with an option to repeat treatment; participants could request cessation treatment at any point. RESULTS: Nicotine gum significantly increased the likelihood of making a quit attempt by 6 weeks (23% vs. 15% without gum; p

Introduction Reducing adverse events from pharmacologic treatment is an important goal of precision medicine and identifying genetic predictors of adverse events is a step toward this goal. In 2012, King et al. reported associations between genetic variants and adverse events in a placebo-controlled smoking cessation trial of varenicline and bupropion. Strong associations were found between gastrointestinal adverse events and 11 variants in the CHRNA5–CHRNA3–CHRNB4 region of chromosome 15, a region repeatedly associated with smoking-related phenotypes. Our goal was to replicate, in an independent sample, the impact of variants in the CHRNA5–CHRNA3–CHRNB4 region on gastrointestinal adverse events and to extend the analyses to adherence and smoking cessation. Methods The University of Wisconsin Transdisciplinary Tobacco Use Research Center (TTURC) conducted a multiarmed, placebo-controlled smoking cessation trial of bupropion and nicotine replacement therapy that included 985 genotyped European-ancestry participants. We evaluated relationships between our key variables using logistic regression. Results Gastrointestinal adverse events were experienced by 31.6% TTURC participants. Each of the CHRNA5–CHRNA3–CHRNB4 associations from the King et al. study was found in TTURC, with the same direction of effect. Neither these variants nor the gastrointestinal adverse events themselves were associated with adherence to medication or successful smoking cessation. Conclusions Variants in the CHRNA5–CHRNA3–CHRNB4 region of chromosome 15 are associated with gastrointestinal adverse events in smoking cessation. Additional independent variants in this region strengthen the association. The consistency between the results of these two independent studies supports the conclusion that these findings reflect biological response to the use of smoking cessation medication. Implications The fact that our findings from the TTURC smoking cessation trial support the independent findings of King et al. suggest that associations of variants in the CHRNA5–CHRNA3–CHRNB4 region of chromosome 15 with gastrointestinal adverse events while taking medications for smoking cessation reflect biology. However, although adherence to medication was a strong predictor of successful smoking cessation in TTURC, neither adverse events nor the genetic variants associated with them predicted either adherence or successful cessation in this study. Thus, although we should strive to minimize adverse events during treatment, we should not expect that to increase successful smoking cessation substantially.

Background Electronic cigarettes (e-cigarettes) have drastically changed the nicotine and tobacco product landscape. However, their potential public health impact is still unclear. A reliable and valid measure of e-cigarette dependence would likely advance assessment and prognostication of the public health impact of e-cigarettes. The aim of this research was to examine the internal consistency, structure, and validity of three e-cigarette dependence scales. Methods Adult dual users (smokers who also vape, N = 256) enrolled in an observational cohort study (45.1% women, 70.7% white). At baseline, participants completed the e-cigarette Fagerström Test of Cigarette Dependence (e-FTCD), the e-cigarette Wisconsin Inventory of Smoking Dependence Motives (e-WISDM), and the Penn State Electronic Cigarette Dependence Index (PS-ECDI). All participants provided a urine sample for cotinine analysis and reported e-cigarette use at 1 year. Results The e-WISDM subscales had the highest internal consistency (α = .81–.96), then the PS-ECDI (α = .74) and e-FTCD (α = .51). A single-factor structure for the e-FTCD and an 11-factor structure for the e-WISDM were supported, but the PS-ECDI did not have a single-factor structure. All three e-cigarette dependence scales were highly correlated with validation criteria including continued e-cigarette use at 1 year, but not with e-liquid nicotine concentration or cotinine. Conclusions The e-WISDM and PS-ECDI had stronger internal consistency than did the e-FTCD, despite the e-FTCD’s single-factor structure, but all 3 measures appear to be valid measures of e-cigarette dependence as suggested by their significant relations with self-perceived addiction, heavy use, early use after overnight deprivation, and continued use over time. Implications This research provides empirical support for three e-cigarette dependence measures: the e-FTCD, the PS-ECDI, and the e-WISDM among dual users of e-cigarettes and combustible cigarettes. The PS-ECDI and e-WISDM are more reliable, but all three measures were strongly correlated with key dependence constructs such as heavy use and continued use over time.

OBJECTIVE: To determine the cost-effectiveness of an incentive-based stop-smoking intervention that paid Medicaid recipients who smoke to take calls from a tobacco quit line. STUDY DESIGN: Cost-effectiveness analysis alongside a randomized controlled trial. The analysis was conducted from a health care systems perspective based on costs and effectiveness over 6-month follow-up. METHODS: Participants (n=1900) were recruited from May 2013 to June 2015 through either quit line (n=980), clinic-based (n=444), or community-based referral (n=476). Incentive group participants (n=948) received $30/call for taking up to 5 tobacco quit line calls and $40 for biochemically-verified tobacco abstinence at 6 months. Control group participants (n=952) did not receive financial incentives for taking quit line calls. Intervention resource costs included incentive payments to participants, counselor and administrative staff time, and smoking cessation medications. Baseline and 6-month smoking status were determined for all study participants via carbon monoxide (CO) breath tests (abstinence = CO

Smoking increases cardiopulmonary and rheumatic disease risk, yet tobacco cessation intervention is rare in rheumatology clinics. This study aimed to implement a rheumatology staff-driven protocol, Quit Connect, to increase the rate of electronic referrals (e-referrals) to free, state-run tobacco quit lines.We conducted a quasi-experimental cohort study of Quit Connect at 3 rheumatology clinics comparing tobacco quit line referrals from 4 baseline years to referrals during a 6-month intervention period. Nurses and medical assistants were trained to use 2 standardized electronic health record (EHR) prompts to check readiness to quit smoking within 30 days, advise cessation, and connect patients using tobacco quit line e-referral orders. Our objective was to use EHR data to examine the primary outcome of tobacco quit line referrals using pre/post design.Across 54,090 pre- and post-protocol rheumatology clinic visits, 4,601 were with current smokers. We compared outcomes between 4,078 eligible pre-implementation visits and 523 intervention period visits. Post-implementation, the odds of tobacco quit line referral were 26-fold higher compared to our pre-implementation rate (unadjusted odds ratio [OR] 26 [95% confidence interval (95% CI) 6-106]). Adjusted odds of checking readiness to quit in the next 30 days increased over 100-fold compared to pre-implementation (adjusted OR 132 [95% CI 99-177]). Intervention led to e-referrals for 71% of quit-ready patients in90 seconds; 24% of referred patients reported a quit attempt.Implementing Quit Connect in rheumatology clinics was feasible and improved referrals to a state-run tobacco quit line. Given the importance of smoking cessation to reduce cardiopulmonary and rheumatic disease risk, future studies should investigate disseminating cessation protocols like Quit Connect that leverage tobacco quit lines.

BACKGROUND AND AIMS: We quantified the effects of smoking and smoking cessation on carotid artery atherosclerosis and wall thickness in two unique cohorts of smokers making a quit attempt. METHODS: Our primary analysis included 726 smokers making a quit attempt in a randomized clinical trial with long-term follow-up. Our secondary analysis included 889 smokers making a quit attempt in a subsequent trial. Participants underwent carotid artery ultrasonography at baseline and up to 3 subsequent visits. Primary outcomes were changes in carotid plaque score and intima media-thickness (IMT). We calculated a smoking burden score (SBS) that reflected the number of visits in which participants reported smoking after the quit attempt. Multivariable regression examined relations between SBS and carotid artery outcomes with adjustments for cardiovascular disease risk factors. RESULTS: In the primary analysis, participants were mean (standard deviation) 46.1 (10.3) years old (57.9% female) and smoked 21.1 (8.9) cigarettes per day (CPD). After a median of 7 years, lower SBS predicted less increase in carotid plaque score (Χ(2)=13.0, p=0.012). SBS independently predicted change in carotid plaque score (p=0.007; SBS 0 vs 4) as did baseline CPD (p=0.024) and age (p

AIMS To assess the effectiveness of intervention components designed to increase quit attempts and promote abstinence in patients initially unwilling to quit smoking. DESIGN A four-factor, randomized factorial experiment. SETTING Sixteen primary care clinics in southern Wisconsin. PARTICIPANTS A total of 577 adults who smoke (60% women, 80% White) recruited during primary care visits who were currently willing to reduce their smoking but unwilling to try to quit. Interventions Four factors contrasted intervention components administered over a 1-year period: (i) nicotine mini-lozenge versus none; (ii) reduction counseling versus none; (iii) behavioral activation (BA) counseling versus none; and (iv) motivational 5Rs counseling versus none. Participants could request cessation treatment at any time. MEASUREMENTS The primary outcome was 7-day point-prevalence abstinence at 52 weeks post enrollment; secondary outcomes were point-prevalence abstinence at 26 weeks and making a quit attempt by weeks 26 and 52. FINDINGS No abstinence main effects were found but a mini-lozenge × reduction counseling × BA interaction was found at 52 weeks; P = 0.03. Unpacking this interaction showed that the mini-lozenge alone produced the highest abstinence rate (16.7%); combining it with reduction counseling produced an especially low abstinence rate (4.1%). Reduction counseling decreased the likelihood of making a quit attempt by 52 weeks relative to no reduction counseling (P = 0.01). CONCLUSIONS Nicotine mini-lozenges may increase smoking abstinence in people initially unwilling to quit smoking, but their effectiveness declines when used with smoking reduction counseling or other behavioral interventions. Reduction counseling decreases the likelihood of making a quit attempt in people initially unwilling to quit smoking.

OBJECTIVE: Heavy drinking is common among smokers and is associated with especially poor health outcomes. Varenicline may affect mechanisms and clinical outcomes that are relevant for both smoking cessation and alcohol use. The current study examines whether varenicline, relative to nicotine replacement therapy, yields better smoking cessation outcomes among binge drinking smokers. METHOD: Secondary data analyses of a comparative effectiveness randomized controlled trial of three smoking cessation pharmacotherapies (12 weeks of varenicline, nicotine patch, or nicotine patch and lozenge) paired with six counseling sessions were conducted. Adult daily cigarette smokers (N = 1,078, 52% female) reported patterns of alcohol use, cigarette craving, and alcohol-related cigarette craving at baseline and over 4 weeks after quitting. Smoking cessation outcome was 7-day biochemically confirmed point-prevalence abstinence. RESULTS: Binge drinkers had higher relapse rates than moderate drinkers at 4-week post-target quit day but not at the end of treatment or long-term follow up (12 and 26 weeks). Varenicline did not yield superior smoking cessation outcomes among binge drinkers, nor did it affect alcohol use early in the quit attempt. Varenicline did produce relatively large reductions in alcohol-related cigarette craving and overall cigarette craving during the first 4 weeks after quitting. CONCLUSIONS: Varenicline did not yield higher smoking abstinence rates or reduce alcohol use among binge drinkers. Varenicline did reduce alcohol-related cigarette craving but this did not translate to meaningful differences in smoking abstinence. Varenicline’s effects on smoking abstinence do not appear to vary significantly as a function of drinking status.

OBJECTIVE: Approaches for effectively treating smoking in those with posttraumatic stress disorder (PTSD) and with major depressive disorder (MDD) could be improved be identifying motivational processes underlying their tobacco dependence. The goal of this study was to identify the motivational processes influencing smoking dependence among smokers with PTSD and with MDD relative to non-diagnosed controls. METHODS: Participants were United States (US) veterans who smoked daily (N = 162) and met DSM-IV criteria for either PTSD (n = 52), MDD (n = 52), or no current psychiatric disorder (controls; n = 58). Smoking dependence motives were assessed via the Brief Wisconsin Inventory for Smoking Dependence Motives (Brief WISDM). The 11 Brief WISDM subscales are categorized into two major factors: Primary Dependence Motives and Secondary Dependence Motives. RESULTS: Smokers with PTSD scored higher than non-diagnosed controls on the following Primary Dependence Motives subscales: Automaticity, Craving, and Tolerance (all p-values

A working group (WG) of experts from diverse fields related to nicotine and tobacco addiction was convened to identify elements and measures from the Host: Social/Cognitive domain to include in the Tobacco Regulatory Research Collection in the PhenX Toolkit, a catalogue of measures for biomedical research. This paper describes the methods used to identify, select, approve and include measures in the toolkit with potential relevance to users of both conventional and newer tobacco products, such as electronic cigarettes (e-cigarettes). In addition to 25 complementary measures primarily focused on cigarette use already present in the PhenX Toolkit, the WG recommended 11 additional social/cognitive measures focused on children and adult users or potential users of tobacco products. Of these, 10 were self-administered measures: frequency of communication with parents about smoking, quality of communication with parents about smoking, susceptibility to tobacco use, behaviour economics/purchase behaviour, motivation to quit (both single and multi-item measures), hedonic tone or response to pleasurable situations, multigroup ethnic identity, peer and family influence on smoking, attentional control and house rules about tobacco use. The remaining selected measure was computer based (distress tolerance). Although validated tools for use in the Host: Social/Cognitive realm are available, much remains to be done to develop, standardise and validate the tools for application to users of e-cigarettes and other non-combusted tobacco products, non-English language speakers and adolescents.

Introduction The availability of electronic cigarettes (e-cigarettes) has profoundly changed the tobacco product landscape. In the United States, almost 6 million adults use both combustible and e-cigarettes (ie, dual users). The goal of this study was to understand how smokers and dual users differ in terms of demographics, cigarette dependence, and exposure to carcinogens. Methods An observational cohort (smokers, n = 166, ≥5 cigarettes/day for 6 months and no e-cigarette use in 3 months; dual users, n = 256, smoked daily for 3 months and used e-cigarettes at least once/week for the past 3 months) completed baseline assessments of demographics, tobacco use, and dependence. They also provided breath samples for carbon monoxide (CO) assay and urine samples for cotinine, 3-hydroxycotinine, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) assays. Results Compared to smokers, dual users (mean e-cigarette use = 5.5 days/week [SD = 1.9]) were significantly younger and more likely to be white, have more education, report a history of psychiatric co-morbidity, and smoke fewer cigarettes per day. There were no differences in CO, cotinine, or 3-hydroxycotinine levels; however, dual users had significantly lower levels of NNAL than did smokers. Most smokers and dual users had no plans to quit smoking within the next year; 91% of dual users planned to continue using e-cigarettes for at least the next year. Conclusions In this community sample, dual users are supplementing their smoking with e-cigarette use. Dual users, versus smokers, smoked fewer cigarettes per day and delayed their first cigarette of the day, but did not differ in quitting intentions. Implications This comparison of a community sample of established dual users and exclusive smokers addresses key questions of dependence and health risks of dual use in real-world settings. Dual users were more likely to be white, younger, have more than a high school education and have a psychiatric history. Dual users also smoked significantly fewer cigarettes and had lower levels of NNAL (a carcinogen), but they did not differ from exclusive smokers in CO or cotinine levels, suggesting that they supplemented their nicotine intake via e-cigarettes.

Objective: E-cigarette use among college students has increased drastically in recent years. This study aims to inform development of a comprehensive measure of e-cigarette consumption for this population. Participants and Methods: This mixed-method study collected both quantitative and qualitative data from a sample of 43 experienced e-cigarette users from two college campuses, using a self-reported questionnaire and a semi-structured interview, in March-September of 2017. Results: College student users found some of the consumption questions in national surveys difficult to answer. Switching nicotine levels, mixing flavors, co-using with alcohol and marijuana, using with others who were vaping or drinking, and vaping in a car or indoor space were all common. The participants defined "regular user" based on ownership of a device rather than on quantity/frequency. Conclusions: A comprehensive e-cigarette consumption measure should cover the complex characteristics that are potentially associated with negative health consequences such as flavorings, co-use and social contexts.

Background We evaluated the effects of smoking and smoking cessation on aortic wave reflections (augmentation index), aortic pulse wave velocity, and carotid artery distensibility and stiffness (distensibility coefficient, Young's elastic modulus). Methods and Results Current smokers underwent carotid, radial, and femoral artery tonometry and carotid ultrasound at baseline and 3 years after a quit attempt. Baseline associations of smoking heaviness markers (exhaled carbon monoxide and cigarettes smoked/d) and effects of smoking cessation at year 3 on changes in arterial measures were assessed using multivariable linear regression models. The 1417 smokers (54% female) were mean (SD) 49.3 (11.6) years old and smoked 17.2 (8.3) cigarettes/d (exhaled carbon monoxide 14.7 [8.2] parts per million). Arterial measures were associated more strongly with age, blood pressure (BP), and waist circumference than with smoking heaviness markers. Augmentation index was associated independently with carbon monoxide ( P =0.004). Pulse wave velocity, distensibility coefficient, and Young's elastic modulus had small, inconsistent associations with smoking heaviness markers. At year 3, augmentation index improved with smoking cessation ( P =0.006) despite more weight gain (2.54 vs 0.36 kg, P P =0.001) among abstainers, but distensibility coefficient decreased ( P =0.004). Changes in arterial measures were related more strongly to changes in BP than smoking cessation. Conclusions Arterial wave reflection and stiffness measures were associated more strongly with age, BP, and waist circumference than smoking heaviness. Smoking cessation was associated with weight gain and increased insulin resistance. Changes in arterial measures were predicted by changes in BP, highlighting the need to address weight gain and BP changes during a quit attempt.

The Comorbidity Workgroup of the Tobacco Treatment Research Network, within the Society for Research on Nicotine and Tobacco, previously highlighted the need to provide tobacco treatment to patients diagnosed with comorbid physical and mental health conditions. Yet, systemic barriers in the United States health care system prevent many patients who present for medical treatment from getting the evidence-based tobacco treatment that they need. The identified barriers include insufficient training in the epidemiologic impact of tobacco use, related disorders, and pharmacological and behavioral treatment approaches; misunderstanding among clinicians about the effectiveness of tobacco treatment; lack of therapeutic support from clinical staff; insufficient use of health information technology to improve tobacco use identification and treatment; and limited time and reimbursement for clinicians to provide treatment. We highlight three vignettes demonstrating the complexities of practical barriers at the health care system level. We consider each of the barriers in turn and discuss evidence-based strategies that could be implemented in the clinical care of patients with comorbid conditions. In addition, in the absence of compelling data to guide implementation approaches, we offer suggestions for potential strategies and avenues for future research. Implications: Three vignettes highlighted in this article illustrate some systemic barriers to providing tobacco treatment for patients being treated for comorbid conditions. We explore the barriers to tobacco treatment and offer suggestions for changes in training, health care systems, clinical workflow, and payment systems that could enhance the reach and the quality of tobacco treatment within the US health care system.