Baseline Tobacco Use Research Articles

Identifying Patterns of Smoking Cessation App Feature Use That Predict Successful Quitting: Secondary Analysis of Experimental Data Leveraging Machine Learning.

Leveraging free smartphone apps can help expand the availability and use of evidence-based smoking cessation interventions. However, there is a need for additional research investigating how the use of different features within such apps impacts their effectiveness. We used observational data collected from an experiment of a publicly available smoking cessation app to develop supervised machine learning (SML) algorithms intended to distinguish the app features that promote successful smoking cessation. We then assessed the extent to which patterns of app feature use accounted for variance in cessation that could not be explained by other known predictors of cessation (eg, tobacco use behaviors). Data came from an experiment (ClinicalTrials.gov NCT04623736) testing the impacts of incentivizing ecological momentary assessments within the National Cancer Institute's quitSTART app. Participants' (N=133) app activity, including every action they took within the app and its corresponding time stamp, was recorded. Demographic and baseline tobacco use characteristics were measured at the start of the experiment, and short-term smoking cessation (7-day point prevalence abstinence) was measured at 4 weeks after baseline. Logistic regression SML modeling was used to estimate participants' probability of cessation from 28 variables reflecting participants' use of different app features, assigned experimental conditions, and phone type (iPhone [Apple Inc] or Android [Google]). The SML model was first fit in a training set (n=100) and then its accuracy was assessed in a held-aside test set (n=33). Within the test set, a likelihood ratio test (n=30) assessed whether adding individuals' SML-predicted probabilities of cessation to a logistic regression model that included demographic and tobacco use (eg, polyuse) variables explained additional variance in 4-week cessation. The SML model's sensitivity (0.67) and specificity (0.67) in the held-aside test set indicated that individuals' patterns of using different app features predicted cessation with reasonable accuracy. The likelihood ratio test showed that the logistic regression, which included the SML model-predicted probabilities, was statistically equivalent to the model that only included the demographic and tobacco use variables (P=.16). Harnessing user data through SML could help determine the features of smoking cessation apps that are most useful. This methodological approach could be applied in future research focusing on smoking cessation app features to inform the development and improvement of smoking cessation apps. ClinicalTrials.gov NCT04623736; https://clinicaltrials.gov/study/NCT04623736.

Even worse for Black girls: the longitudinal association of racial bullying with the initiation of alcohol and tobacco use.

We used Poisson's linear regression to examine the association between racial bullying (RB) and the initiation of alcohol and tobacco uses after 9 months. Two cluster-randomized controlled trials were conducted in 2019 with children in grades five (girls: 50.0%; 10 years old: 82.0%; White: 36.8%; Black: 58.7%; others: 4.5%) and seven (girls: 49.5%; 12 years old: 78.1%; White: 33.2%; Black: 60.4%; others: 6.4%) from 30 public schools in the municipality of São Paulo, Brazil. We restricted our analyses to 2 subsets of students in each grade: those who reported no lifetime alcohol use at baseline and those who reported no lifetime baseline tobacco use. At baseline, 16.2% of fifth and 10.7% of seventh graders reported suffering from RB in the 30 days before data collection. After 9 months, 14.9% of fifth graders started using alcohol and 2.5%, tobacco. Among seventh graders, the figures were 31.2% and 7.7%, respectively. RB predicted the initiation of use of alcohol (risk ratio [RR]= 1.36; 95% CI, 1.07-1.70) and tobacco (RR= 1.81; 95% CI, 1.14-2.76) among seventh graders, with race-gender differences, particularly in Black girls (alcohol: RR= 1.45; 95% CI, 1.07-1.93; tobacco: RR= 2.34; 95% CI, 1.31-3.99). School-based programs and policies must explicitly address issues related to racism and gender in alcohol and tobacco prevention strategies.

Effect of nicotine corrective messaging on nicotine-related beliefs in US adults: a randomised controlled trial

IntroductionWidespread misperceptions of the health risks of nicotine could undermine the public health benefits of the Food and Drug Administration’s actions, including modified risk tobacco product authorisations and a reduced...

Health risk behaviour and persistent and incident depression among middle-aged and older adults in South Africa.

The aim of this study was to assess the association between five health risk behaviours and persistent and incident depressive symptoms in a longitudinal study in South Africa. The sample included 5059 men and women (≥40 years) in 2014/2015, and 4176 in 2018/2019 of the 'Health and Ageing in Africa: A Longitudinal Study of an INDEPTH Community in South Africa'. Depressive symptoms were assessed with the Centre for Epidemiologic Studies Depression scale. Multivariable logistic regression analysis was conducted to assess the associations between five health risk behaviours and persistent and incident depressive symptoms. Results indicate that 5.0% of participants had depressive symptoms at both wave 1 and 2 (persistent depressive symptoms), and 27.9% had incident depressive symptoms in wave 2. Higher education and moderate baseline physical activity were negatively associated and those with cardiovascular disease were positively associated with persistent depressive symptoms. Middle wealth index was negative, and being HIV positive and baseline tobacco use were positively associated with incident depressive symptoms. In conclusion, of five health risk behaviours assessed (inadequate fruit/vegetable intake, alcohol dependence, tobacco use, physical activity, and sedentary behaviour), only moderate physical activity was protective against persistent depressive symptoms, and tobacco use was associated with incident depressive symptoms.

Testing if attitudes mediate the association between advertising exposure and adolescent tobacco use

IntroductionA growing body of evidence indicates that exposure to tobacco advertising among adolescents increases the likelihood of subsequent tobacco use. It is important to understand the process by which this occurs, in order to appropriately target factors for intervention. The objective of this study was to test whether attitudes towards tobacco advertising mediates the impact of advertising exposure on tobacco use. MethodsFrom an ongoing prospective cohort study of male adolescents (aged 11–16 at baseline), we recruited a subset of tobacco users and non-users to participate in an additional ecological momentary assessment (EMA) project (N = 164). Adolescents completed smartphone-based surveys 2–3 times/day over a 10-day period with items assessing their exposures and attitudes towards tobacco-related advertising. If participants reported exposure to tobacco advertising, they were asked about their attitudes toward it (how much they enjoyed it, liked it, and found it appealing). ResultsAdolescents who reported a greater amount of advertising exposure during the EMA period were more likely to report past-30-day tobacco use at their next cohort follow-up (6–12 months later). Moreover, the impact of advertising exposure on subsequent use was mediated by attitudes toward the tobacco advertisements, as reported during the EMA. This effect remained after controlling for baseline tobacco use. ConclusionsBy pairing EMA with long-term follow-up, we identified attitudes as a mediator between adolescent advertising exposure and subsequent tobacco use. Interventions to lessen adolescents’ positive attitudes toward tobacco advertisements may help disrupt this impact.

Local Tobacco 21 Policies are Associated With Lower Odds of Tobacco Use Among Adolescents.

Tobacco 21 (T21) policies have shown promise in reducing cigarette use among adolescents. This study examined whether local T21 policies affected adolescent use of a variety of tobacco products and whether results differed by grade level. We used repeated cross-sectional data from eighth, ninth, and eleventh-grade respondents to the 2016 (n = 107 981) and 2019 (n = 102 196) Minnesota Student Surveys. Generalized estimating equations modeled eight adolescent tobacco use outcomes in 2019 (past 30-day use of any tobacco, cigarettes, cigars, e-cigarettes, hookah, chewing tobacco, flavored tobacco, and multiple products) by T21 exposure, defined as respondents' attendance at a school within a jurisdiction with T21 policy implementation between the two surveys. Models controlled for demographic characteristics and product-specific baseline tobacco use at the school level in 2016 and were stratified by grade. After adjusting for baseline tobacco use and other demographics, T21-exposed eighth and ninth-grade students had significantly lower odds of tobacco use than unexposed peers in five of eight models, i.e. any tobacco (aOR = 0.80, 95% CI: 0.74, 0.87), cigarettes (aOR = 0.81, 95% CI: 0.67, 0.99), e-cigarettes (aOR = 0.78, 95% CI: 0.71, 0.85), flavored tobacco (aOR = 0.79, CI: 0.70, 0.89), and dual/poly tobacco (aOR = 0.77, 95% CI: 0.65, 0.92). T21-exposed eleventh-grade students did not differ significantly in their odds of any tobacco use outcomes relative to their unexposed peers. T21 exposure is associated with lower odds of multiple forms of tobacco use, particularly among younger adolescent populations, supporting the implementation of T21 policies to reduce tobacco use in this population.

Objective and perceived measures of tobacco marketing are uniquely associated with cigar use

BackgroundFew studies have examined associations between perceived and objective exposure to tobacco marketing and cigar use, which is the second most commonly used tobacco product by youth.MethodsWe used Geographic Ecological...

Reporting of tobacco use and impact on outcomes in cancer cooperative group clinical trials: A systematic scoping review.

40 Background: Continued smoking after a diagnosis of cancer negatively impacts cancer outcomes but the impact of tobacco on many innovative treatments has not yet been well established. Collecting and evaluating tobacco use in cancer clinical trials may advance understanding of the consequences of tobacco use on specific treatment modalities. We performed a systematic scoping review of the frequency of reporting and analysis of tobacco use in clinical trials run by cancer cooperative clinical trial groups. Methods: A comprehensive literature search was conducted to identify cancer cooperative group clinical trials published from January 2017 to October 2019 using Medline, Epub Ahead of Print and In-Process & Other Non-Indexed Citations, Embase, Cochrane Central Register of Controlled Trials using OvidSP. Eligible studies evaluated either systemic and/or radiation therapies, involved at least one cancer cooperative group, included > 100 adult patients and reported on at least one primary or secondary endpoint, which included overall survival (OS), disease/progression-free survival (DFS/PFS), response rates, toxicities/adverse events, or quality of life (QoL). Secondary analyses of previously published trials were excluded. Results: Among 14843 identified studies, 91 studies representing 90 trials met inclusion criteria. 24% were phase II trials, 2% phase II/III and 74% phase III. Trial start dates ranged from 1995-2015 with most (29%) between 2007-2008; median trial sample size was 406 (range: 100-4994); 86% involved systematic therapy, 35% involved radiation; 14% were lung and 5% were head and neck trials. 51% of trials had a curative intent, 33% were palliative and 16% involved hematologic cancers. 74 studies reported on OS, 73 DFS/PFS, and 88 toxicity/QoL. 19 studies reported baseline tobacco use information, while two reported collecting follow-up tobacco use. Of those collecting baseline tobacco use, only 7 reported any analysis of the impact of tobacco on clinical outcomes. There was significant heterogeneity in the reporting of baseline tobacco use: 5 reported never/ever status, 10 reported never/ex-smoker/current smoker status; 4 reported some measure of smoking intensity; none reported on verifying smoking status or second hand smoke exposure. Trials of tobacco related (lung and head and neck) cancers were more likely to report baseline tobacco use compared to non-tobacco related cancers (83% vs 6% p < 0.001). Conclusions: Few cancer cooperative group clinical trials report and analyze trial participants’ baseline tobacco use, and even fewer collect follow up information. Significant heterogeneity exists in reporting tobacco use. Routine standardized collection and reporting of tobacco use, both at baseline and follow up in clinical trials, should be implemented to enable investigators to evaluate the clinical impact of tobacco use on new cancer therapies.

Crossover associations of alcohol and smoking, craving and biochemically verified alcohol and nicotine use in heavy drinking smokers.

This study examined associations between drinking and smoking prior to treatment (biochemically measured at baseline), alcohol and tobacco craving, and biochemical alcohol and tobacco use during the analog trial period. We conducted a secondary data analysis of a randomized clinical analog trial where participants with a Diagnostic and Statistical Manual, Fourth Edition Text Revision (DSM-IV-TR) diagnosis of alcohol dependence, abuse or reported heavy drinking, with a co-occurring DSM-IV-TR diagnosis of nicotine dependence, abuse or reported heavy use, who were not seeking treatment were recruited. A generalized estimation equation model for longitudinal binary outcomes was created (N = 34) to determine the predictive effects of baseline tobacco use, alcohol craving, and tobacco craving on alcohol use over the 4 weeks of the trial. Baseline smoking was significantly (*p < 0.05) associated with drinking over time [odds ratio (OR) = 3.09*], while baseline drinking was associated with smoking (OR = 4.17*). Baseline alcohol and tobacco craving were positively associated with smoking over time (OR = 3.21* and OR = 1.92*, respectively) but were negatively associated with alcohol use over time (OR = 0.79* and OR = 0.57*, respectively). Heavier use of either tobacco or alcohol preceding treatment may require more intensive interventions in order to reduce tobacco and alcohol use. Future trials designed to address mechanisms of behavior change in the context of novel treatments could promote a better understanding of the cross-rewarding effects related to the co-use of these substances and lead to the development of more integrated and appropriately intense treatments for individuals with concomitant tobacco and alcohol use disorders.

When, How, & Where Tobacco Initiation and Relapse Occur During U.S. Air Force Technical Training.

Military personnel are at high risk for tobacco use, particularly during the first year of military service. Technical Training follows an 8½week tobacco ban during basic military training and is a vulnerable time for personnel to both reinitiate and initiate tobacco use. Thus, this can be a crucial time to promote tobacco policies and interventions. However, there is limited research examining when, how, and where personnel access tobacco during the first year of service, particularly among users of newer products (eg, electronic cigarettes[e-cigarettes]). Thus, the purpose of the current study is to explore the timing, source, and location of tobacco use during Technical Training across all types of products. Furthermore, this study will examine differences in demographic characteristics and prior tobacco history in relationship to these tobacco behaviors. Participants were U.S. Air Force recruits completing Technical Training (2017-2018). Protocol was approved by the Institutional Review Board at the 59th Medical Wing of the U.S. Air Force. During the first week of Technical Training, Airmen were consented to participate in the study and completed a questionnaire about demographics and tobacco use history. Next, Airmen were randomized to receive one of three tobacco prevention interventions as part of military training. At a 3-month follow-up, during the last week of Technical Training, consented participants completed a questionnaire about current tobacco use. Airmen reported when (ie, first month vs. after), how (ie, "bummed" from another airman, bought on or off base, received from the internet or event), and where (ie, designated smoking areas on base, off base, bar or club, friend's house, cigar lounge, hookah bar, or vape shop) they used tobacco during Technical Training. Descriptive statistics were used to examine these behaviors across all tobacco products. Additionally, Wilcoxon-Mann-Whitney and Kruskal-Wallis tests compared differences in demographic characteristics and baseline tobacco use in relationship to these tobacco behaviors. No significant differences were found when comparing prior users and first-time users in relationship to tobacco behaviors during Technical Training; however, significant differences in educational background and age were found in regard to the source and location of tobacco use. Additionally, how and where Airmen first used tobacco during Technical Training differed across products. Cigarettes and smokeless tobacco were equally likely to be bought on or off base and most commonly first used at a designated smoking area on base. However, e-cigarettes, cigarillos/little cigars, and hookah were more likely to be bought off base, and first used at a specialty store (ie, vape shop, hookah bar, or cigar lounge). Tobacco use behaviors during Technical Training differed depending on the type of product. Specifically, new and emerging products were more likely to be bought off base and first used at a specialty store. Thus, military polices regulating on base tobacco pricing might not reduce the growing prevalence of e-cigarettes. Future policies might consider addressing the density of off-base tobacco retailers to reduce the high rates of tobacco use in this population.

Effect of Participatory Health Promotion Initiative on Tobacco Use among Adolescents: A School-Based Quasi-Experimental Pilot Study from Central India

Introduction: Prevalence of noncommunicable diseases (NCDs) is increasing rapidly in developing countries like India. The commonly attributable modifiable risk factors of NCDs include raised blood pressure (13%), tobacco use (9%), physical inactivity (6%), and obesity (5%). This quasi-experimental study with a pre-post design was conducted with an objective to assess the effect of Participatory Health Promotion initiative (PHPI) on tobacco use among adolescents. PHPI included distribution of personalized health card, tobacco-tar experiment demonstration, use of body mapping technique to emphasize hazards of tobacco on different body organs, and sensitization in small groups. Methods: Baseline tobacco use and health risk assessment were conducted by adapting WHO ASSIST tool among 200 students who were randomly selected from a secondary high school. All students in the school were then exposed to the PHPI. The postmeasurement was done among another 200 randomly selected students after 3 months. Results: The number of current tobacco users reduced from 29 (14.5%) in the baseline to 9 (4.5%) in the postmeasurement with a P

Understanding the Opioid Epidemic: Factors Predictive of Inpatient and Postdischarge Prescription Opioid Use After Orthopaedic Trauma.

The purpose of this study was to determine which factors influence inpatient and postdischarge opioid use after orthopaedic trauma. Retrospective cohort study. Single Level 1 trauma center. The study included 235 adult trauma patients treated operatively for fracture with minimum 1 overnight hospital stay. Operative fracture management. Total opioid pain medication use, in oral morphine equivalents, in inpatient and postdischarge settings. Controlling for length of stay, inpatient opioid use was negatively correlated with age and positively correlated with Injury Severity Score, intensive care unit (ICU) admission, and baseline tobacco use (P < 0.0001, adjusted R = 0.274). Discharge opioid prescription amount was negatively correlated with age, the presence of a complication, and ICU admission and positively correlated with inpatient opioid use (P < 0.0001, adjusted R = 0.201). Postdischarge opioid use was associated with larger amounts of opioids prescribed at discharge, a patient history of alcohol use at baseline, and ICU admission (P < 0.0001, R = 0.123). Nonmodifiable factors accounted for the level of inpatient opioid use in a trauma population. Higher inpatient use predicts larger opioid prescriptions at discharge, whereas larger discharge prescription predicts greater postdischarge opioid use. Strategies to reduce postdischarge opioid use should begin with reductions in inpatient opioid use. Multimodal pain strategies may be needed to achieve this goal. Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Tobacco use does not influence the response to non-pharmacologic depression treatment: A secondary analysis of the Regassa randomized controlled trial

Behavioural interventions show promising results among patients with mild- to moderate depression. However, whether tobacco use moderates the effects of these interventions is not known. In the present study, we examined whether patients suffering from mild-to-moderate depression differed in their response to prescribed physical exercise or internet-based cognitive behavioural therapy (ICBT) according to their current tobacco use. We conducted a secondary analysis of data from 740 participants in a multicentre randomised controlled trial comparing physical exercise, internet-based cognitive behavioural therapy and treatment as usual (Regassa study). Information on current daily tobacco use was self-reported at baseline. Linear and logistic regression were used to examine the treatments’ effect (reduction in depression score) in the subgroups of tobacco users (n=154) and non-users (n=586). We found that baseline tobacco use did not significantly moderate the association between treatment type and post-treatment depression severity. Both interventions (exercise and ICBT) resulted in a reduction of depression scores that was similar among non-users and users of tobacco, albeit formally statistically significant only among non-users. Physical exercise on prescription and ICBT can be used in the clinical management of depressed patients, with similar prognostic advantage among tobacco users and non-users.

Implications of Attrition in a Longitudinal Web-Based Survey: An Examination of College Students Participating in a Tobacco Use Study.

BackgroundWeb-based survey research has several benefits, including low cost and burden, as well as high use of the Internet, particularly among young adults. In the context of longitudinal studies, attrition raises concerns regarding the validity of data, given the potential associations with individual and institutional characteristics, or the focal area of study (eg, cigarette use).ObjectivesThe objective of this study was to compare baseline characteristics of nonresponders versus responders in a sample of young adult college students in a Web-based longitudinal study regarding tobacco use.MethodsWe conducted a secondary data analysis of 3189 college students from seven Georgia colleges and universities in a 2-year longitudinal study. We examined baseline tobacco use, as well as individual- and institutional-level factors, as predictors of attrition between wave 1 (October and November 2014) and wave 2 (February and March 2015) using multilevel modeling. Results: A total 13.14% (419/3189) participants were lost to follow-up at wave 2. Predictors of nonresponse were similar in the models examining individual-level factors and institutional-level factors only and included being black versus white (odds ratio [OR] 1.74, CI 1.23-2.46); being male versus female (OR 1.41, CI 1.10-1.79); seeking a bachelor’s degree versus advanced degree (OR 1.41, CI 1.09-1.83); not residing on campus (OR 0.62, CI 0.46-0.84); past 30-day tobacco use (OR 1.41, CI 1.10-1.78); attending a nonprivate college (OR 0.48, CI 0.33-0.71); and attending a college with ≤10,000 students (OR 0.56, CI 0.43-0.73).ConclusionsFuture longitudinal studies should assess predictors of attrition to examine how survey topic and other individual and institutional factors might influence the response to allow for correction of selection bias.

Utilization of a Web-based vs integrated phone/Web cessation program among 140,000 tobacco users: an evaluation across 10 free state quitlines.

BackgroundPhone-based tobacco cessation program effectiveness has been established and randomized controlled trials have provided some support for Web-based services. Relatively little is known about who selects different treatment modalities and how they engage with treatments in a real-world setting.ObjectiveThis paper describes the characteristics, Web utilization patterns, and return rates of tobacco users who self-selected into a Web-based (Web-Only) versus integrated phone/Web (Phone/Web) cessation program.MethodsWe examined the demographics, baseline tobacco use, Web utilization patterns, and return rates of 141,429 adult tobacco users who self-selected into a Web-Only or integrated Phone/Web cessation program through 1 of 10 state quitlines from August 2012 through July 2013. For each state, registrants were only included from the timeframe in which both programs were offered to all enrollees. Utilization data were limited to site interactions occurring within 6 months after registration.ResultsMost participants selected the Phone/Web program (113,019/141,429, 79.91%). After enrollment in Web services, Web-Only were more likely to log in compared to Phone/Web (21,832/28,410, 76.85% vs 23,920/56,892, 42.04%; P<.001), but less likely to return after their initial log-in (8766/21,832, 40.15% vs 13,966/23,920, 58.39%; P<.001). In bivariate and multivariable analyses, those who chose Web-Only were younger, healthier, more highly educated, more likely to be uninsured or commercially insured, more likely to be white non-Hispanic and less likely to be black non-Hispanic, less likely to be highly nicotine-addicted, and more likely to have started their program enrollment online (all P<.001). Among both program populations, participants were more likely to return to Web services if they were women, older, more highly educated, or were sent nicotine replacement therapy (NRT) through their quitline (all P<.001). Phone/Web were also more likely to return if they had completed a coaching call, identified as white non-Hispanic or “other” race, or were commercially insured (all P<.001). Web-Only were less likely to return if they started their enrollment online versus via phone. The interactive Tobacco Tracker, Cost Savings Calculator, and Quitting Plan were the most widely used features overall. Web-Only were more likely than Phone/Web to use most key features (all P<.001), most notably the 5 Quitting Plan behaviors. Among quitlines that offered NRT to both Phone/Web and Web-Only, Web-Only were less likely to have received quitline NRT.ConclusionsThis paper adds to our understanding of who selects different cessation treatment modalities and how they engage with the program in a real-world setting. Web-Only were younger, healthier smokers of higher socioeconomic status who interacted more intensely with services in a single session, but were less likely to re-engage or access NRT benefits. Further research should examine the efficacy of different engagement techniques and services with different subpopulations of tobacco users.

Marijuana use and risk of lung cancer: a 40-year cohort study

Cannabis (marijuana) smoke and tobacco smoke contain many of the same potent carcinogens, but a critical-yet unresolved-medical and public-health issue is whether cannabis smoking might facilitate the development of lung cancer. The current study aimed to assess the risk of lung cancer among young marijuana users. A population-based cohort study examined men (n = 49,321) aged 18-20 years old assessed for cannabis use and other relevant variables during military conscription in Sweden in 1969-1970. Participants were tracked until 2009 for incident lung cancer outcomes in nationwide linked medical registries. Cox regression modeling assessed relationships between cannabis smoking, measured at conscription, and the hazard of subsequently receiving a lung cancer diagnosis. At the baseline conscription assessment, 10.5 % (n = 5,156) reported lifetime use of marijuana and 1.7 % (n = 831) indicated lifetime use of more than 50 times, designated as "heavy" use. Cox regression analyses (n = 44,284) found that such "heavy" cannabis smoking was significantly associated with more than a twofold risk (hazard ratio 2.12, 95 % CI 1.08-4.14) of developing lung cancer over the 40-year follow-up period, even after statistical adjustment for baseline tobacco use, alcohol use, respiratory conditions, and socioeconomic status. Our primary finding provides initial longitudinal evidence that cannabis use might elevate the risk of lung cancer. In light of the widespread use of marijuana, especially among adolescents and young adults, our study provides important data for informing the risk-benefit calculus of marijuana smoking in medical, public-health, and drug-policy settings.

A randomized controlled trial of a smoking cessation intervention conducted among prisoners.

AimTo evaluate the efficacy of nortriptyline (NOR) added to a multi-component smoking cessation intervention, which included cognitive–behavioural therapy (CBT) and provision of nicotine replacement therapy (NRT).DesignRandomized controlled trial (RCT) comparing two study groups with blinded follow-up at 3, 6 and 12 months. Both groups received a multi-component smoking cessation intervention comprising two half-hour individual sessions of CBT and NRT with either active NOR or placebo.SettingPrisons in New South Wales (17) and Queensland (one), Australia.ParticipantsA total of 425 male prisoners met inclusion criteria and were allocated to either treatment (n = 206) or control group (n = 219).MeasurementsPrimary end-points at 3, 6 and 12 months were continuous abstinence, point prevalence abstinence and reporting a 50% reduction in smoking. Smoking status was confirmed by expired carbon monoxide, using a cut-point of ≤10 parts per million.FindingsParticipants' demographics and baseline tobacco use were similar in treatment and control groups. Based on an intention-to-treat analysis, continuous abstinence between the treatment and control groups was not significantly different at 3 months (23.8 versus 16.4%), 6 months (17.5 versus 12.3%) and 12 months (11.7 versus 11.9%).ConclusionAdding nortriptyline to a smoking cessation treatment package consisting of behavioural support and nicotine replacement therapy does not appear to improve long-term abstinence rates in male prisoners.

How adolescents with substance use disorder spend research payments

There is concern that research reimbursements to adolescents may increase substance use. However, these concerns have not been examined empirically. Participants were 70 adolescents (13–19 years) with at least one non-nicotine substance use disorder (SUD) enrolled in a 12-week clinical trial of atomoxetine/placebo for attention/deficit-hyperactivity disorder (ADHD). Adolescent participants received cash reimbursement after each study visit (maximum possible=$425 over 12 weeks). Participants reported each week how they spent the previous reimbursement. Results were tallied, and correlates of spending a payment on substances were examined. Results showed that 26 of 70 subjects reported spending at least one research payment on alcohol or drugs, and 25 of 70 subjects reported spending at least one payment on tobacco. Comparing those who did and did not spend a research payment on alcohol/drugs, those who did had more frequent baseline alcohol/drug use but did not differ in demographics (age, gender) or other clinical characteristics (ADHD severity, diagnosis of conduct disorder, number of SUD diagnoses, number of treatment sessions attended, or pre/post-change in number of days used substances in the past 28 days). Comparing those who did and did not spend a payment on tobacco, those who did were slightly older and had more frequent baseline tobacco use. In conclusion, a significant proportion of subjects used at least a portion of one research payment to buy alcohol, drugs or tobacco. However, there was little indication that research payments increased substance use.

Tobacco use and other risk behaviors: cross-sectional and predictive relationships for adolescent orthodontic patients.

The purpose of these analyses was to examine the prevalence of selected substance abuse, general and dental health risk, and scholastic risk behaviors and their cross-sectional and predictive relationships with tobacco use among 15, 179 adolescent orthodontic patients in Southern California. Subjects were recruited through 154 orthodontists' offices and interviewed by telephone at baseline and two-year posttest. Results show a pattern of increasing prevalence of risk behaviors with age. In most cases, gender differences were small. There were statistically significant positive relationships between each risk behavior and tobacco use status for both boys and girls. Prevalence rates of risk behaviors other than tobacco use were highest for current smokers, intermediate for experimenters, and lowest for respondents reporting that they had never used tobacco. Baseline tobacco use predicted each posttest risk behavior in logistic regression analyses. Principle components analysis (with varimax rotation) of posttest risk practices other than tobacco use yielded three theoretically meaningful factors, all which were predicted by baseline tobacco use in multiple regressions. These findings show that tobacco use among adolescents can predict subsequent risk practices other than tobacco use as long as two years, and that unhealthy behaviors among teens are interrelated. Orthodontists, who have a high frequency of adolescent patient contact, may be in a unique position to deliver health promotion interventions to their patients; possibly targeting multiple risk behaviors.