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BackgroundWe examined the nicotine metabolite ratio's (NMR) relationship with smoking intensity, nicotine dependence, and a broad array of biomarkers of exposure and biological effect in commercial cigarette smokers.MethodsSecondary analysis was conducted on two cross-sectional samples of adult, daily smokers from Wave 1 (2013-2014) of the Population Assessment of Tobacco Use and Health (PATH) Study and baseline data from a 2014-2017 randomized clinical trial. Data were restricted to participants of non-Hispanic, white race. The lowest quartile of NMR (

Despite public health efforts, individuals with serious mental illness (SMI) still have very high rates of tobacco smoking. Innovative approaches to reach this population are needed. These series of case studies aimed to descriptively evaluate the usability, user experience (UX), and user engagement (UE) of Learn to Quit (LTQ), an acceptance and commitment therapy smoking cessation app designed for people with SMI, and to compare it with an app designed for the general population, NCI (National Cancer Institute) QuitGuide (QG). Both apps were combined with nicotine replacement therapy and technical coaching. Inspired by the ORBIT model, we implemented two case studies with crossover AB interventions, two B-phase training designs, and three bi-phasic AB single-case designs with Start-Point and Order randomization (A = QG, B = LTQ). Study outcomes were measured using the System Usability Scale, UX interviews, and background analytics. LTQ's usability levels were above the standard cutoff and on average higher than QG. UX outcomes suggested the relative benefits of LTQ's visual design, gamification and simple design structure. LTQ's overall UE was high; the app was opened for an average of 14 min per day (vs. QG: 7 min). However, users showed low levels of UE with each of the app's tracking feature. Measures of psychiatric functioning suggested the safety of LTQ in people with SMI. LTQ appears to be a usable and engaging smoking cessation app in people with SMI. An optimized version of LTQ should be tested in a Phase II study. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study is to understand how early cigarette use might predict subsequent illicit drug use, especially among individuals with attention-deficit hyperactivity disorder (ADHD) symptoms during childhood.Methods: Data were drawn from the National Longitudinal Study of Adolescent Health (Waves I-IV). The analysis sample involves participants who had not used illicit drugs at Wave I, with no missing responses for studied predictors (N = 7,332).Results: Smoking status at Wave I (ever regular vs. never regular) and childhood ADHD symptoms predicted subsequent illicit drug use at Waves II to IV. No interaction effect of smoking status at Wave I and childhood ADHD symptoms was found. However, an indirect effect from childhood ADHD symptoms on illicit drug use was identified, through smoking status at Wave I. Similar results were observed for predicting illicit drug dependence.Conclusions: The findings support the notion that smoking status during early adolescence may mediate the association between childhood ADHD symptoms and risk of later adult drug use. Interventions to prevent smoking among adolescents may be particularly effective at decreasing subsequent drug use, especially among children with ADHD symptoms. [ABSTRACT FROM AUTHOR]

Exposure to smoking cues increases craving for cigarettes and can precipitate relapse. Whereas brain imaging studies have identified a distinct network of brain regions subserving the processing of smoking cues, little is known about the influence of individual difference factors and withdrawal symptoms on brain cue reactivity. Multiple regression analysis was used to evaluate relations between individual difference factors and withdrawal symptoms and event-related blood oxygen level–dependent responses to visual smoking cues in a sample of 30 smokers. Predictors were self-report nicotine dependence (Fagerström test of nicotine dependence, FTND), prescan withdrawal symptoms (craving and negative affect), and sex. The unique variance of each predictor was examined after controlling for each of the others. Positive associations were observed between FTND and reactivity to cues in right anterior cingulate and orbitofrontal cortex (OFC) whereas negative associations were observed between prescan craving and reactivity in ventral striatum. Higher negative affect or being male was associated with greater reactivity in left hippocampus and left OFC. Women exhibited greater cue reactivity than men in regions including the cuneus and left superior temporal gyrus. Individual difference factors and withdrawal symptoms were uniquely associated with brain reactivity to smoking cues in regions subserving reward, affect, attention, motivation, and memory. These findings provide further evidence that reactivity to conditioned drug cues is multiply determined and suggest that smoking cessation treatments designed to reduce cue reactivity focus on each of these variables.Neuropsychopharmacology (2008) 33, 2148–2157; doi:10.1038/sj.npp.1301618; published online 7 November 2007 [ABSTRACT FROM AUTHOR]

Introduction: High rates of tobacco use among people with serious mental illness (SMI), along with their unique needs, suggest the importance of developing tailored smoking cessation interventions for this group. Previous early-phase work empirically validated the design and content of Learn to Quit, a theory-based app designed for this population., Methods: In a pilot randomized controlled trial, we compared the feasibility, acceptability, and preliminary efficacy of Learn to Quit versus QuitGuide, an app designed for the general population. All participants received nicotine replacement therapy and technical assistance. Daily smokers with SMI (N = 62) participated in the trial with outcomes assessed at weeks 4, 8, 12, and 16., Results: Compared to QuitGuide, Learn to Quit participants had similar number of days of app use (34 vs. 32, p = .754), but larger number of app interactions (335 vs. 205; p = .001), longer durations of app use (4.24 hrs. vs. 2.14 hrs; p = .044), and higher usability scores (85 vs. 79, p = .046). At week 16, Learn to Quit led to greater reductions in cigarettes per day (12.3 vs. 5.9 for QuitGuide; p = 0.10). Thirty-day point prevalence abstinence was verified in 12% of Learn to Quit participants versus 3% of QuitGuide participants (odds ratio = 3.86, confidence interval = 0.41 to 36, p = .239). Changes in psychiatric symptoms and adverse events were not clinically significant between conditions., Conclusions: This pilot trial provides strong evidence of Learn to Quit's usability, feasibility, and safety. Preliminary evidence suggests the app may be efficacious. A randomized controlled efficacy trial is needed to test the app in a larger sample of smokers with SMI., Implications: This study suggests that the Learn to Quit app is a feasible approach to deliver smoking cessation treatment in patients with co-occurring tobacco use disorder and SMI. This means that, if found efficacious, this technology could be used to deploy smoking cessation treatment to larger segments of this population, hence improving public health. Therefore, a randomized controlled trial should be conducted to examine the efficacy of this digital intervention., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved.For permissions, please e-mail: journals.permissions@oup.com.)

Objectives: The aim of this study is to understand how early cigarette use might predict subsequent illicit drug use, especially among individuals with attention-deficit hyperactivity disorder (ADHD) symptoms during childhood., Methods: Data were drawn from the National Longitudinal Study of Adolescent Health (Waves I-IV). The analysis sample involves participants who had not used illicit drugs at Wave I, with no missing responses for studied predictors (N = 7,332)., Results: Smoking status at Wave I (ever regular vs. never regular) and childhood ADHD symptoms predicted subsequent illicit drug use at Waves II to IV. No interaction effect of smoking status at Wave I and childhood ADHD symptoms was found. However, an indirect effect from childhood ADHD symptoms on illicit drug use was identified, through smoking status at Wave I. Similar results were observed for predicting illicit drug dependence., Conclusions: The findings support the notion that smoking status during early adolescence may mediate the association between childhood ADHD symptoms and risk of later adult drug use. Interventions to prevent smoking among adolescents may be particularly effective at decreasing subsequent drug use, especially among children with ADHD symptoms., (© The Author 2017. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com)