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OBJECTIVE Innovative strategies are needed to reduce young adult drinking. Real-time feedback via mobile health (mHealth) technology (e.g., smartphone devices/apps) may facilitate moderate drinking, yet requires evidence of feasibility, acceptability, and usability. METHOD Young adults reporting frequent heavy drinking (N = 99, Mage = 23, 51% male) participated in a manualized, brief, motivational interview on recent typical and peak blood alcohol concentration (BAC), then were randomized to use 1 of the 3 forms of technology: (a) smartphone breathalyzer device/app; (b) app that estimates BAC based on factors including sex, weight, number/types of drinks over time; or (c) self-text messaging after each drink. Technologies were tested initially in small-group laboratory alcohol self-administration sessions. Participants then completed a 2-week field test wherein they had free access to all three technologies. Participants reported on usability and acceptability. RESULTS Laboratory alcohol self-administration did not differ significantly by technology condition. The smartphone breathalyzer and BAC estimator app had favorable acceptability and usability. Participants used at least one form of technology on 67% of drinking days in the field period. In exploratory analyses, alcohol use during the field period was significantly lower than the baseline including a decrease of nearly one drink per drinking day. CONCLUSIONS These findings support the feasibility of research combining lab and field methods to test moderate drinking technologies in young adults. Findings further support the acceptability and usability of these technologies, along with young adults' openness to using them. Exploratory results suggest potential efficacy of combined mobile technology intervention to be tested in subsequent controlled studies. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

E-cigarette use has been increasing globally over the past decade. Many use e-cigarettes as an alternative or method to quit cigarette smoking, whereas others use these products recreationally. As technology has advanced, many individuals have reported symptoms of dependence on these products and continue to use them beyond achieving abstinence from smoking. Despite individuals reporting interest in quitting, little is known about e-cigarette cessation. This systematic review sought to identify and evaluate all human subjects literature published on the outcome of e-cigarette cessation through September 2021. Of the 79 articles identified, 56 were cross-sectional, 6 were qualitative, 5 were cohort studies, 3 were experimental, 2 were mixed methods, and 7 reported intervention or case studies of e-cigarette cessation. Results showed youth generally had high intent to quit e-cigarettes, whereas results were mixed with adult samples. Youth were motivated to quit e-cigarettes by health concerns, whereas adults were motivated to quit e-cigarettes by cost, lack of satisfaction, and psychologic factors. Adults were more likely to report past e-cigarette quit attempts, most commonly “cold turkey.” Few interventions tested strategies for e-cigarette cessation, with a majority targeted for youth. Given the lack of information on e-cigarette cessation, recommendations for future studies are outlined.

Introduction Contingency management (CM) interventions deliver monetary reinforcers contingent upon biochemically verified abstinence from smoking. CM has been found to be effective, however, individual participant, analyses are warranted to further elucidate how individual-level behavior patterns vary during the intervention period, both within and across treatment groups. Aims and Methods This is a secondary analysis of a randomized controlled pilot trial of presurgical cancer patients who smoke (RCT N = 40). All participants were current everyday smokers and were enrolled in cessation counseling, offered nicotine replacement therapy, and submitted breath CO testing 3 times per week for 2–5 weeks. Participants randomized to CM received monetary reinforcers for breath CO ≤6 ppm on an escalating schedule of reinforcement with a reset for positive samples. Sufficient breath CO data exist for 28 participants (CM = 14; monitoring only [MO] = 14). Effect size was calculated for differences in negative CO tests. Time to first negative test was tested using survival analysis. Fisher’s exact test was used to assess relapse. Results The CM group achieved abstinence more quickly (p < .05), had a lower percentage of positive tests (h = 0.80), and experienced fewer lapses following abstinence (p = .00). While 11 of 14 participants in the CM group achieved and sustained abstinence by their third breath test, this was only true for 2 of the 14 MO participants. Conclusions Those in CM achieved abstinence quicker and with fewer lapses than those engaged in MO speaking to the efficacy of the schedule of financial reinforcement. This is particularly important within presurgical populations given the potential benefits to postoperative cardiovascular and wound infection risk. Implications While the efficacy of CM as an intervention is well established, this secondary analysis provides insight into the individual behavior patterns underlying successful abstinence. Those assigned to CM were not only more likely to achieve abstinence, but did so more quickly and with fewer instances of relapse. This is of particular importance to those scheduled for surgery where achieving abstinence as early as possible impacts on the risk of postoperative complications. CM interventions may be particularly well suited for critical windows in which timely and sustained abstinence is advantageous.

Supplementary Table from Urgent Need for Novel Investigations of Treatments to Quit E-cigarettes: Findings from a Systematic Review

Supplementary Data from Urgent Need for Novel Investigations of Treatments to Quit E-cigarettes: Findings from a Systematic Review

The US Preventive Services Task Force recommends annual lung cancer screening for patients at high risk based on age and smoking history. Understanding the characteristics of patients attending lung cancer screening, including potential barriers to quitting smoking, may inform ways to engage these high-risk patients in tobacco treatment and address health disparities. Patients attending lung cancer screening who currently smoke cigarettes completed a survey at Smilow Cancer Hospital at Yale-New Haven (N = 74) and the Medical University of South Carolina (N = 73) at the time of their appointment. The survey assessed demographics, smoking history, and perceptions and concerns about quitting smoking. Patients were 55 to 76 years old (mean = 63.3, SD = 5.3), N = 64 (43.5%) female, and N = 31 (21.1%) non-Hispanic Black. Patients smoked 16.3 cigarettes per day on average (SD = 9.2) and rated interest in quitting smoking in the next month as moderate (mean = 5.6, SD = 3.1, measured from 0 = “very definitely no” to 10 = “very definitely yes”). The most frequently endorsed concerns about quitting smoking were missing smoking (70.7%), worry about having strong urges to smoke (63.9%), and concerns about withdrawal symptoms (59.9%). In comparison with other races/ethnicities, Black patients were less likely to report concerns about withdrawal symptoms and more likely to report smoking less now and perceiving no need to quit. Findings identified specific barriers for tobacco treatment and differences by race/ethnicity among patients attending lung cancer screening, including concerns about withdrawal symptoms and perceived need to quit. Identifying ways to promote tobacco treatment is important for reducing morbidity and mortality among this high-risk population. Prevention Relevance: The current study examines patient characteristics and tobacco treatment perceptions and barriers among patients attending lung cancer screening who continue to smoke cigarettes that may help inform ways to increase treatment engagement and address tobacco-related health disparities to reduce morbidity and mortality from smoking.

During the initial wave of the Coronavirus Disease 2019 (COVID-19) pandemic in the U.S., information was mixed about the relative COVID-19 risks and potential benefits associated with cigarette smoking. Therefore, we sought to understand individual differences in the impact of COVID-19 on cigarette smoking in a sample of adults who reported recent use, with a particular focus on chronic medical conditions likely associated with increased COVID-19 risk. Participants completed an online survey of smoking behavior, demographic variables, medical history, and COVID-19 risk perceptions between July and August 2020 (N = 286). We examined whether medical conditions, COVID-19 risk perceptions and/or demographic characteristics were related to smoking changes in response to the pandemic (i.e., no change, decrease, increase) using multinomial logistical regression. Younger age, higher COVID-19 risk perceptions and Black versus White race were associated with greater odds of decreased smoking compared to no smoking change. Moreover, having at least one chronic medical condition was associated with greater odds of increased smoking relative to no change. The results have important implications for tobacco cessation treatment and preventive healthcare during the ongoing COVID-19 pandemic and other public health threats.

BACKGROUND: There is a need for novel alcohol biosensors that are accurate, able to detect alcohol close in time to consumption, and feasible and acceptable for many clinical and research applications. We evaluated the field accuracy and tolerability of a novel (BACTrack Skyn) and established (Alcohol Monitoring Systems SCRAM CAM) alcohol biosensor. METHODS: The sensor and diary data were collected in a larger study of a biofeedback intervention but compared observationally in the present sub-study. Participants (high-risk drinkers, 40% female; median age 21) wore both Skyn and SCRAM CAM sensors for 1 to 6 days and were instructed to drink as usual. Data from the first cohort of participants (N=27; 101 person-days) were used to find threshold values of transdermal alcohol that classified each day as meeting or not meeting defined levels of drinking (heavy, above-moderate, any). These values were used to develop scoring metrics that were subsequently tested using the second cohort (N = 20; 57 person-days). Data from both biosensors were compared to mobile diary self-report to evaluate sensitivity and specificity in relation to a priori standards established in the literature. RESULTS: Skyn classification rules for Cohort #1 within 3 months of device shipment showed excellent sensitivity for heavy drinking (94%) and exceeded expectations for above-moderate and any drinking (78%/69%), while specificity met expectations (91%). However, classification worsened when Cohort #1 devices ≥3 months from shipment were tested (area under curve for receiver operator characteristic .87 vs .79) and the derived classification threshold when applied to Cohort #2 was inadequately specific (70%). Skyn tolerability metrics were excellent and exceeded the SCRAM CAM (p ≤.001). CONCLUSIONS: Skyn tolerability was favorable and accuracy rules were internally derivable but did not yield useful scoring metrics going forward across device lots and months of usage.

OBJECTIVE: Pharmacological treatments that can concomitantly address cigarette smoking and heavy drinking stand to improve healthcare delivery for these highly prevalent co-occurring conditions. This superiority trial tested the combination of varenicline plus naltrexone versus varenicline alone for smoking cessation and drinking reduction among heavy drinking smokers. METHODS: This was a phase 2, randomized, double-blind, clinical trial. Participants (n=165) were daily smokers who drank heavily and received either (a) varenicline tartrate 1 mg twice daily plus naltrexone 50 mg once daily, or (b) varenicline tartrate 1 mg twice daily plus matched placebo pills for 12-weeks. Primary outcomes were (a) 7-day point prevalence of nicotine abstinence bioverified by breath carbon monoxide (CO) reading of ≤ 5 ppm at the 26-week follow-up, and (b) drinks per drinking day during the 12-week treatment phase. RESULTS: Smoking abstinence at week 26 was significantly higher in the varenicline plus placebo condition than the varenicline plus naltrexone condition (n=37 [45.1%] versus n=22 [26.5%]; χ(2)[1] = 6.22, p=.015). For drinks per drinking day, there was a trend towards a main effect of medication [β=0.86, SE=0.44, t(1,250)=1.94, p=.054], favoring the combination of varenicline plus naltrexone over varenicline alone across the 12-week treatment phase. CONCLUSIONS: These findings suggest that smoking cessation and drinking reduction can be concomitantly targeted with pharmacotherapy and that while varenicline alone may be sufficient as a smoking cessation aid in heavy drinking smokers, the combination of varenicline plus naltrexone may confer benefits with regards to drinking outcomes, particularly during the 12-week period of active medication treatment. TRIAL REGISTRATION: ClinicalTrials.gov NCT02698215.

Introduction The purpose of this study was to evaluate a pilot preoperative contingency management (CM) intervention for smoking abstinence. Aims and Methods This multisite pilot study was conducted at two cancer center-based tobacco treatment programs. Participants who were smoking, diagnosed with or suspected to have any type of operable cancer, and had a surgical procedure scheduled in the next 10 days to 5 weeks (N = 40) were randomized to receive standard care plus monitoring only (MO) or CM prior to surgery. All patients received breath carbon monoxide (CO) tests 3 times per week, nicotine patches, and counseling. The CM group also earned payments for self-reported smoking abstinence confirmed by CO breath test ≤6 ppm on an escalating schedule of reinforcement (with a reset if they smoked). Seven-day point prevalence abstinence rates on the day of surgery and at 3-month follow-up were compared between groups using repeated measures log-linear regression models utilizing generalized estimating equations. Participants lost to follow-up are assumed to have returned to smoking. Results The sample was 50% female and 75% White. In covariate adjusted models, patients in the CM group had a greater probability of reported abstinence. On the day of surgery (end of treatment), 52% of CM patients were abstinent compared with 16% of patients in MO (risk ratio = 3.2 [1.1–9.3]; p = .03). At the 3-month follow-up, 43% of CM patients were abstinent compared with 5% in MO (risk ratio = 8.4 [1.5–48.3]; p = .02). Conclusions Providing monetary incentives contingent on abstinence prior to cancer surgery may produce significant improvements in smoking abstinence rates relative to breath CO MO. Implications In this pilot preoperative CM intervention for smoking abstinence, patients receiving a CM intervention prior to cancer surgery had a greater probability of smoking abstinence at the end of treatment compared with a breath MO group (52% vs. 16%, respectively). Thus, providing monetary incentives contingent on abstinence may produce significant improvements in smoking abstinence rates prior to cancer surgery relative to breath CO monitoring.

OBJECTIVE: Naltrexone is an effective treatment for heavy drinking among young adults, and laboratory-based studies have shown that naltrexone dampens the subjective response to alcohol and craving. However, few studies have tested naltrexone’s dynamic, within-person effects on subjective response and craving among young adults in natural drinking environments. METHODS: Using daily diary data from a randomized, placebo-controlled study of naltrexone efficacy in young adults, we examined the between-person effects of treatment condition (i.e., naltrexone vs. placebo) and medication dosage (daily, targeted, daily+targeted) on the subjective response to alcohol and craving on drinking days. Multilevel mediation models predicted subjective response and craving from treatment condition (between-person) and medication dosage (within-person), accounting for drinking levels. All effects were disaggregated within- and between-person. RESULTS: At the between-person level, naltrexone directly blunted intense subjective effects (i.e., “impaired”, “drunk”), and indirectly blunted subjective effects through reduced drinking. Naltrexone was not associated with craving. Between-person effects were not significant after alpha correction, but their effect sizes (bs=.14-.17) exceeded the smallest effect size of interest. At the within-person level, taking 2 (vs. 1) pills was associated with heavier drinking, and taking 1 (vs. 0) pills was associated with lighter drinking, and lighter drinking was associated with a lower subjective response and craving. Treatment condition did not moderate the within-person effects of dosing on outcomes. CONCLUSIONS: The findings suggest that the direct between-person effect of naltrexone was largest on intense subjective responses, blunting feeling “drunk” and “impaired”. Future research using momentary (rather than daily) assessments could confirm and extend these findings.

Introduction: Suboptimal use of nicotine replacement therapy (NRT) may pose a significant barrier to smokers attempting to quit. We examined NRT use as a predictor of smoking abstinence and heavy drinking in a randomised trial of hazardous drinkers who contacted the NY State Smokers’ quitline for smoking cessation assistance.Methods: Participants (N = 1,948) received either Tobacco Only Counselling or Alcohol + Tobacco Counselling (ATC), both in addition to a 2-week supply of NRT. NRT use, smoking status, and heavy drinking days were assessed by self-report at the 7-month follow-up.Results: Of those smokers who completed the 7-month follow-up (N = 843), 53.1% used all of the NRT and 40.6% used some. Those who used all of the NRT were more likely to be abstinent from smoking than those who used some, and more likely to report no heavy drinking days than those who used some or none.Conclusions: Approximately half of the heavy drinking smokers calling the quitline are willing to use the 2-week supply of free NRT, and most will at least try it. Those who reported using all of the NRT were more likely to report smoking abstinence and no heavy drinking days at the 7-month follow-up.

ObjectivesCombined smoking and heavy drinking is a significant health burden. Varenicline, an efficacious tobacco pharmacotherapy that also shows promise for drinking, has yielded mixed results among heavy-drinking smokers. This pilot study investigated integrated tobacco and alcohol counselling plus varenicline for this vulnerable group.DesignTwelve-week parallel, randomized controlled pilot trial of two behavioural interventions in combination with open-label varenicline. Participants were randomized using computer-generated tables, stratified by sex.SettingOutpatient academic medical centre research clinic.ParticipantsVolunteers who reported smoking and heavy drinking and sought tobacco or alcohol treatment (N = 26).Intervention(1) Integrated tobacco + alcohol counselling (INT; n = 13) or (2) counselling focused on their presenting concern (i.e., tobacco or alcohol) (SINGLE; n = 13), plus varenicline (2 mg) for 12 weeks.Main outcomesFeasibility/acceptability, smoking quit rates and heavy drinking.ResultsINT feasibility/acceptability was high among men but not women. More participants quit smoking in INT than SINGLE. This outcome was only in men, not significant, but had a medium effect size. Both conditions yielded significant drinking reductions.ConclusionIntegrated tobacco and alcohol behavioural counselling plus varenicline may be feasible and promote smoking cessation among men who smoke and drink heavily, but a larger sample is needed to replicate this finding.

Millions of consumer sport and fitness wearables (CSFWs) are used worldwide, and millions of datapoints are generated by each device. Moreover, these numbers are rapidly growing, and they contain a heterogeneity of devices, data types, and contexts for data collection. Companies and consumers would benefit from guiding standards on device quality and data formats. To address this growing need, we convened a virtual panel of industry and academic stakeholders, and this manuscript summarizes the outcomes of the discussion. Our objectives were to identify (1) key facilitators of and barriers to participation by CSFW manufacturers in guiding standards and (2) stakeholder priorities. The venues were the Yale Center for Biomedical Data Science Digital Health Monthly Seminar Series (62 participants) and the New England Chapter of the American College of Sports Medicine Annual Meeting (59 participants). In the discussion, stakeholders outlined both facilitators of (e.g., commercial return on investment in device quality, lucrative research partnerships, and transparent and multilevel evaluation of device quality) and barriers (e.g., competitive advantage conflict, lack of flexibility in previously developed devices) to participation in guiding standards. There was general agreement to adopt Keadle et al.'s standard pathway for testing devices (i.e., benchtop, laboratory, field-based, implementation) without consensus on the prioritization of these steps. Overall, there was enthusiasm not to add prescriptive or regulatory steps, but instead create a networking hub that connects companies to consumers and researchers for flexible guidance navigating the heterogeneity, multi-tiered development, dynamicity, and nebulousness of the CSFW field.

ObjectiveA pressing tobacco policy concern is how to help smokers who have little interest in quitting cigarettes, a group that often suffers severe health consequences. By switching from cigarettes to e-cigarettes, they could obtain nicotine, potentially with less harm. We examined if policy-relevant attributes of cigarettes/e-cigarettes might encourage these smokers to switch to e-cigarettes.MethodsAn online survey and discrete choice experiment on a nationally-representative sample of adult smokers in the US who reported low interest in quitting (n=2000). We modelled preference heterogeneity using a latent class, latent variable model. We simulated policies that could encourage switching to e-cigarettes.ResultsParticipants formed two latent classes: (1) those with very strong preferences for their own cigarettes; and (2) those whose choices were more responsive to policies. The latter group’s choices were only somewhat responsive to menthol cigarette bans and taxes; the former group’s choices were unresponsive.ConclusionsThe policies studied seem unlikely to encourage harm reduction for individuals with little interest in quitting smoking.

Background Our clinical trial of a mobile exercise intervention for adults 18 to 65 years old with type 1 diabetes (T1D) occurred during COVID-19 social distancing restrictions, prompting us to test web-based recruitment methods previously underexplored for this demographic. Objective Our objectives for this study were to (1) evaluate the effectiveness and cost of using social media news feed advertisements, a clinic-based approach method, and web-based snowball sampling to reach inadequately active adults with T1D and (2) compare characteristics of enrollees against normative data. Methods Participants were recruited between November 2019 and August 2020. In method #1, Facebook and Instagram news feed advertisements ran for five 1-to-8-day windows targeting adults (18 to 64 years old) in the greater New Haven and Hartford, Connecticut, areas with one or more diabetes-related profile interest. If interested, participants completed a webform so that the research team could contact them for eligibility screening. In method #2, patients 18 to 24 years old with T1D were approached in person at clinical visits in November and December 2019. Those who were interested immediately completed eligibility screening. Older patients could not be approached due to clinic restrictions. In method #3, snowball sampling was conducted by physically active individuals with T1D contacting their peers on Facebook and via email for 48 days, with details to contact the research staff to express interest and complete eligibility screening. Other methods referred participants to the study similarly to snowball sampling. Results In method #1, advertisements were displayed to 11,738 unique viewers and attracted 274 clickers (2.33%); 20 participants from this group (7.3%) volunteered, of whom 8 (40%) were eligible. Costs averaged US $1.20 per click and US $95.88 per eligible volunteer. Men had lower click rates than women (1.71% vs 3.17%; P Conclusions Web-based advertising and recruitment strategies are a promising means to attract adults with T1D to clinical trials and exercise interventions, with costs comparing favorably to prior trials despite targeting an uncommon condition (ie, T1D) and commitment to an intervention. These strategies should be tailored in future studies to increase access to higher-risk participants. Trial Registration ClinicalTrials.gov NCT04204733; https://clinicaltrials.gov/ct2/show/NCT04204733

Background Although smoking is prevalent among populations with opioid use disorder (OUD), few studies have examined electronic cigarette (EC) use in individuals seeking opioid agonist therapy (OAT). The aim of this study was to evaluate the prevalence and correlates of EC use among individuals seeking OAT. Methods 782 patients seeking OAT for OUD completed surveys assessing current and past EC use, reasons for use, current and past cigarette smoking, nicotine dependence, psychiatric distress, trauma, and pain. Bivariate and multivariate models evaluated correlates of daily EC use, past-30-day EC use, and current cigarette smoking. Results 6% of patients reported daily EC use, 18% reported past-30-day use, 62% reported EC use history, and 85% reported current cigarette smoking. 46% reported using ECs to quit or cut down smoking. In multivariate analyses, daily EC use was associated with higher odds of being a former smoker (OR 21; CI 1.7–273) and lower odds of ever smoking more than 100 cigarettes (OR 0.07; CI 0.01–0.32), while EC use in the past 30 days was associated with lower odds of being Caucasian (OR 0.55; CI 0.34–0.89), ever smoking more than 100 cigarettes (OR 0.13; CI 0.02–0.67), and history of chronic pain (OR 0.59; CI 0.38-0.90), and higher odds of reporting psychiatric distress (OR 1.5; CI 1.1–2.2). Conclusions EC use is common among people with OUD who smoke cigarettes. Those with daily use had higher odds of being former smokers than current smokers. Interventions using ECs may be effective to help reduce harms and mortality in OUD.

BACKGROUND: This study is the first to examine longitudinal post-treatment outcomes of a placebo-controlled trial of varenicline for alcohol use disorder with comorbid cigarette smoking. METHODS: Participants were 131 adults (n=39 female) seeking alcohol treatment in a randomized, double-blind, parallel group, placebo-controlled, 16-week multi-site trial of varenicline combined with medical management (O’Malley et al., 2018). Timeline follow-back assessments of alcohol and smoking behavior were conducted at the end of treatment (4 months), with follow-ups at 6, 9, and 12 months. Outcomes were percentage of heavy drinking days (PHDD), percent of participants with no heavy drinking days (NHDD), cotinine-confirmed prolonged smoking abstinence (PA), and good clinical outcome (GCO) on either NHDD or PA. RESULTS: Treatment improvements were maintained post-treatment. For the sample overall, PHDD or NHDD did not differ significantly by treatment condition (ps>.13), but varenicline produced higher rates of PA vs. placebo at 4, 9, and 12 months (p

AIMS Theory-driven, exploratory study to: (i) identify a reward drinking phenotype in young adults; (ii) evaluate this phenotype as a predictor of naltrexone response; and (iii) examine mechanisms of naltrexone in reward drinkers. DESIGN Secondary analysis of a randomized controlled trial. SETTING USA. PARTICIPANTS A total of 128 young adult (ages 18-25) heavy drinkers. INTERVENTIONS Naltrexone versus placebo. MEASUREMENTS Daily surveys assessed affect, urge, drinking, and context. The Drinking Motives Questionnaire was used to identify phenotypes based on reward (enhancement motives) and relief (coping motives) drinking. FINDINGS We identified three profiles: "Low reward/Low relief" (14.1%; low enhancement/low coping motives); "Reward drinkers" (62.2%; high enhancement/low coping motives); and "High reward/High relief" (22.7%; high enhancement/high coping motives). Among reward drinkers (versus low profile), naltrexone significantly reduced percent days drinking to intoxication (blood alcohol concentration [BAC] ≥0.08) (PDI) (d = 0.56; 95% CI [0.17, 0.96]) and percent high intensity drinking days (PHID) (8/10 drinks for women/men) (d = 0.32; 95% CI [0.01, 0.68]). Among the high reward/high relief profile drinkers (versus low profile), naltrexone reduced PHID (d = 0.69; 95% CI [0.02, 1.50]). Using profile-informed cutoffs and observed scores (for clinical applicability): (i) among cutoff-derived reward drinkers, we found a medium-to-large (d = 0.66; 95% CI [0.24, 1.16]) and small effect (d = 0.28; 95% CI [0.04, 0.72]) of naltrexone in reducing PDI and PHID, respectively; and (ii) among the cutoff-derived high reward/high relief subgroup, we found a medium-to-large effect (d = 0.63; 95% CI [0.05, 1.1]) of naltrexone in reducing PHID. Among reward drinkers (not other profiles), naltrexone reduced drinking on days a drinking event occurred by weakening the within-day association between positive affect and urges (P < 0.05). CONCLUSIONS Naltrexone has pronounced effects in reducing risky drinking among young adult reward drinkers (high reward/low relief) by reducing urges on days when individuals have higher positive affect and are exposed to a drinking event. Naltrexone also appears to reduce risky drinking among young adult high reward/high relief drinkers, but not via the same mechanism.

BACKGROUND Our clinical trial of a mobile exercise intervention for adults 18 to 65 years old with type 1 diabetes (T1D) occurred during COVID-19 social distancing restrictions, prompting us to test web-based recruitment methods previously underexplored for this demographic. OBJECTIVE Our objectives for this study were to (1) evaluate the effectiveness and cost of using social media news feed advertisements, a clinic-based approach method, and web-based snowball sampling to reach inadequately active adults with T1D and (2) compare characteristics of enrollees against normative data. METHODS Participants were recruited between November 2019 and August 2020. In method #1, Facebook and Instagram news feed advertisements ran for five 1-to-8-day windows targeting adults (18 to 64 years old) in the greater New Haven and Hartford, Connecticut, areas with one or more diabetes-related profile interest. If interested, participants completed a webform so that the research team could contact them for eligibility screening. In method #2, patients 18 to 24 years old with T1D were approached in person at clinical visits in November and December 2019. Those who were interested immediately completed eligibility screening. Older patients could not be approached due to clinic restrictions. In method #3, snowball sampling was conducted by physically active individuals with T1D contacting their peers on Facebook and via email for 48 days, with details to contact the research staff to express interest and complete eligibility screening. Other methods referred participants to the study similarly to snowball sampling. RESULTS In method #1, advertisements were displayed to 11,738 unique viewers and attracted 274 clickers (2.33%); 20 participants from this group (7.3%) volunteered, of whom 8 (40%) were eligible. Costs averaged US $1.20 per click and US $95.88 per eligible volunteer. Men had lower click rates than women (1.71% vs 3.17%; P CONCLUSIONS Web-based advertising and recruitment strategies are a promising means to attract adults with T1D to clinical trials and exercise interventions, with costs comparing favorably to prior trials despite targeting an uncommon condition (ie, T1D) and commitment to an intervention. These strategies should be tailored in future studies to increase access to higher-risk participants. CLINICALTRIAL ClinicalTrials.gov NCT04204733; https://clinicaltrials.gov/ct2/show/NCT04204733

BACKGROUND This paper describes the research protocol for a randomized controlled trial of a multimodal mobile sleep intervention for heavy-drinking young adults. Young adults report the highest rates of heavy, risky alcohol consumption and are a priority population for alcohol prevention and intervention efforts. Alcohol strategies that leverage other health concerns and use technology may offer an innovative solution. Poor sleep is common among young adults and is a risk factor for developing an alcohol use disorder. Moreover, young adults are interested in information to help them sleep better, and behavioral sleep interventions address alcohol use as a standard practice. OBJECTIVE The primary aim of this study is to assess the effectiveness of a 2-week multimodal mobile sleep intervention for reducing drinks consumed per week among heavy-drinking young adults. We will explore the effects on alcohol-related consequences, assessing quantitative and qualitative sleep characteristics as secondary aims. The study’s goals are to identify the optimal combination of sleep intervention components for improving drinking outcomes, the feasibility and acceptability of these components, and the potential mechanisms by which these components may promote alcohol behavior change. METHODS Young adults (aged 18-25 years) who report recent heavy drinking will be randomly assigned to one of three conditions: mobile sleep hygiene advice (n=30), mobile sleep hygiene advice and sleep and alcohol diary self-monitoring (n=30), or mobile sleep hygiene advice, sleep and alcohol diary self-monitoring, and sleep and alcohol data feedback (n=60). For the feedback component, participants will complete two web-based sessions with a health coach during which they will receive summaries of their sleep and alcohol data, and the potential association between them along with brief advice tailored to their data. All participants will wear sleep and alcohol biosensors daily for 2 weeks for objective assessments of these outcomes. RESULTS The study was funded by the National Institutes of Health in May 2018. Recruitment began in December 2018 and will be concluded in Spring 2021. As of February 4, 2021, we have enrolled 110 participants. CONCLUSIONS Ultimately, this research could result in an efficacious, low-cost intervention with broad population reach through the use of technology. In addition, this intervention may substantially impact public health by reducing alcohol use disorder risk at a crucial developmental stage. CLINICALTRIAL ClinicalTrials.gov NCT03658954; https://clinicaltrials.gov/ct2/show/NCT03658954 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/26557

Because tobacco use remains one of the leading causes of disease, disability, and mortality, tobacco treatment programs should be integrated into medical systems such as hospitals and outpatient centers. Medical providers have a unique, high-impact opportunity to initiate smoking cessation treatment with patients. However, there are several barriers that may hinder the development and implementation of these programs. The purpose of this review was to address such barriers by illustrating several examples of successful tobacco treatment programs in US health-care systems that were contributed by the authors. This includes describing treatment models, billing procedures, and implementation considerations. Using an illustrative review of vignettes from existing programs, various models are outlined, emphasizing commonalities and unique features, strengths and limitations, resources necessary, and other relevant considerations. In addition, clinical research and dissemination trials from each program are described to provide evidence of feasibility and efficacy from these programs. This overview of example treatment models designed for hospitals and outpatient centers provides guidelines for any emerging tobacco cessation services within these contexts. For existing treatment programs, this review provides additional insight and ideas about improving these programs within their respective medical systems.

INTRODUCTION. Varenicline is an FDA–approved medication for smoking cessation and has demonstrated promise in reducing alcohol use. This study sought to compare the efficacy of varenicline in reducing smoking and drinking among Black and White people seeking alcohol treatment. METHODS. Linear mixed modeling was conducted using data from two multi-site placebo-controlled randomized clinical trials examining the effects of varenicline for treatment of Alcohol Use Disorder (AUD; O’Malley et al., 2018 and Litten et al., 2013) among Black and White adults with AUD and co-occurring cigarette smoking. The primary analyses were conducted in a sample of 117 adults (O’Malley trial: 29.1% female, 55.2% Black), and replicated in an independent sample of 73 adults (Litten trial: 23.3% female, 45.2% Black). RESULTS. Black participants smoked fewer cigarettes per day compared to White participants (O’Malley trial: F(1,116) = 8.95, p = .003; Litten trial: F(1,68.9) = 4.74 p = .03). Linear mixed models revealed a marginal effect of varenicline on reducing cigarettes smoked per day regardless of race in the O’Malley trial (F(1,109) = 3.34, p = .07), which was replicated in the Litten trial (F(1,67.1) = 20.77 p < .0001). Participants reduced the number of drinks consumed regardless of treatment condition or race in both trials (O’Malley trial: F(1,98) = 131.69, p

The development of mobile-health technology has the potential to revolutionize personalized medicine. Biomedical sensors (e.g., wearables) can assist with determining treatment plans for individuals, provide quantitative information to healthcare providers, and give objective measurements of health, leading to the goal of precise phenotypic correlates for genotypes. Even though treatments and interventions are becoming more specific and datasets more abundant, measuring the causal impact of health interventions requires careful considerations of complex covariate structures, as well as knowledge of the temporal and spatial properties of the data. Thus, interpreting biomedical sensor data needs to make use of specialized statistical models. Here, we show how the Bayesian structural time series framework, widely used in economics, can be applied to these data. This framework corrects for covariates to provide accurate assessments of the significance of interventions. Furthermore, it allows for a time-dependent confidence interval of impact, which is useful for considering individualized assessments of intervention efficacy. We provide a customized biomedical adaptor tool, MhealthCI, around a specific implementation of the Bayesian structural time series framework that uniformly processes, prepares, and registers diverse biomedical data. We apply the software implementation of MhealthCI to a structured set of examples in biomedicine to showcase the ability of the framework to evaluate interventions with varying levels of data richness and covariate complexity and also compare the performance to other models. Specifically, we show how the framework is able to evaluate an exercise intervention’s effect on stabilizing blood glucose in a diabetes dataset. We also provide a future-anticipating illustration from a behavioral dataset showcasing how the framework integrates complex spatial covariates. Overall, we show the robustness of the Bayesian structural time series framework when applied to biomedical sensor data, highlighting its increasing value for current and future datasets., Author summary In this paper, we propose and describe a robust and flexible modeling framework called MhealthCI based on the Bayesian structural time series, for which we have found to excel at analyzing diverse biosensor data. While Bayesian modeling is often employed in various fields such as finance, marketing, and weather forecasting, it is rarely used in biomedicine, specifically for biosensor and wearable data relating to human health and behavior. We use and apply this framework with the goal of interpreting and quantifying the causal impact of an intervention, a widespread goal of biomedicine. We describe the diversity of data types to which it could apply, provide intuition to its mechanics, collect relevant data in various fields, provide a wrapper tool around well-known R packages that prepares and registers diverse biosensor data to be analyzed, and finally apply the method to showcase its strength in quantifying the impact of interventions.

Background Novel alcohol prevention strategies are needed for heavy-drinking young adults. Sleep problems are common among young adults who drink heavily and are a risk factor for developing an alcohol use disorder (AUD). Young adults, interested in the connection between sleep and alcohol, are open to getting help with their sleep. Therefore, sleep interventions may offer an innovative solution. This study evaluates social media advertising for reaching young adults and recruiting them for a new alcohol prevention program focused on sleep. Objective This study aims to evaluate the effectiveness and cost of using Facebook, Instagram, and Snapchat advertising to reach young adults who drink heavily for a sleep intervention; characterize responders’ sleep, alcohol use, and related concerns and interests; and identify the most appealing advertising content. Methods In study 1, advertisements targeting young adults with sleep concerns, heavy alcohol use, or interest in participating in a sleep program ran over 3 months. Advertisements directed volunteers to a brief web-based survey to determine initial sleep program eligibility and characterize the concerns or interests that attracted them to click the advertisement. In study 2, three advertisements ran simultaneously for 2 days to enable us to compare the effectiveness of specific advertising themes. Results In study 1, advertisements generated 13,638 clicks, 909 surveys, and 27 enrolled volunteers in 3 months across the social media platforms. Fees averaged US $0.27 per click, US $3.99 per completed survey, US $11.43 per volunteer meeting initial screening eligibility, and US $106.59 per study enrollee. On average, those who completed the web-based survey were 21.1 (SD 2.3) years of age, and 69.4% (631/909) were female. Most reported sleep concerns (725/909, 79.8%) and an interest in the connection between sleep and alcohol use (547/909, 60.2%), but few had drinking concerns (49/909, 5.4%). About one-third (317/909, 34.9%) were identified as being at risk for developing an AUD based on a validated alcohol screener. Among this subsample, 8.5% (27/317) met the final criteria and were enrolled in the trial. Some volunteers also referred additional volunteers by word of mouth. In study 2, advertisements targeting sleep yielded a higher response rate than advertisements targeting alcohol use (0.91% vs 0.56% click rate, respectively; P Conclusions Social media advertisements designed to target young adults with sleep concerns reached those who also drank alcohol heavily, despite few being concerned about their drinking. Moreover, advertisements focused on sleep were more effective than those focused on drinking. Compared with previous studies, cost-effectiveness was moderate for engagement (impressions to clicks), excellent for conversion (clicks to survey completion), and reasonable for enrollment. These data demonstrate the utility of social media advertising focused on sleep to reach young adults who drink heavily and recruit them for intervention.

History has shown that we must adapt and learn from crises so that we can improve how we deliver care and conduct research to improve clinical outcomes. The coronavirus disease 2019 (COVID‐19) pandemic has expedited work regarding virtual research methods and serves as an opportunity to evaluate how to initiate, implement, and sustain cancer prevention, early detection, and treatment research going forward.

BACKGROUND Novel alcohol prevention strategies are needed for heavy-drinking young adults. Sleep problems are common among young adults who drink heavily and are a risk factor for developing an alcohol use disorder (AUD). Young adults, interested in the connection between sleep and alcohol, are open to getting help with their sleep. Therefore, sleep interventions may offer an innovative solution. This study evaluates social media advertising for reaching young adults and recruiting them for a new alcohol prevention program focused on sleep. OBJECTIVE This study aims to evaluate the effectiveness and cost of using Facebook, Instagram, and Snapchat advertising to reach young adults who drink heavily for a sleep intervention; characterize responders’ sleep, alcohol use, and related concerns and interests; and identify the most appealing advertising content. METHODS In study 1, advertisements targeting young adults with sleep concerns, heavy alcohol use, or interest in participating in a sleep program ran over 3 months. Advertisements directed volunteers to a brief web-based survey to determine initial sleep program eligibility and characterize the concerns or interests that attracted them to click the advertisement. In study 2, three advertisements ran simultaneously for 2 days to enable us to compare the effectiveness of specific advertising themes. RESULTS In study 1, advertisements generated 13,638 clicks, 909 surveys, and 27 enrolled volunteers in 3 months across the social media platforms. Fees averaged US $0.27 per click, US $3.99 per completed survey, US $11.43 per volunteer meeting initial screening eligibility, and US $106.59 per study enrollee. On average, those who completed the web-based survey were 21.1 (SD 2.3) years of age, and 69.4% (631/909) were female. Most reported sleep concerns (725/909, 79.8%) and an interest in the connection between sleep and alcohol use (547/909, 60.2%), but few had drinking concerns (49/909, 5.4%). About one-third (317/909, 34.9%) were identified as being at risk for developing an AUD based on a validated alcohol screener. Among this subsample, 8.5% (27/317) met the final criteria and were enrolled in the trial. Some volunteers also referred additional volunteers by word of mouth. In study 2, advertisements targeting sleep yielded a higher response rate than advertisements targeting alcohol use (0.91% vs 0.56% click rate, respectively; P CONCLUSIONS Social media advertisements designed to target young adults with sleep concerns reached those who also drank alcohol heavily, despite few being concerned about their drinking. Moreover, advertisements focused on sleep were more effective than those focused on drinking. Compared with previous studies, cost-effectiveness was moderate for engagement (impressions to clicks), excellent for conversion (clicks to survey completion), and reasonable for enrollment. These data demonstrate the utility of social media advertising focused on sleep to reach young adults who drink heavily and recruit them for intervention.

Purpose: Evaluate the feasibility and preliminary efficacy of implementing evidence-based tobacco treatment at the workplace for service industry employees. Design: Randomized trial using 6 paired worksites (3 test and 3 delayed intervention control sites). Setting: US Northeast city. Participants: Employees were recruited from university food service settings. Intervention: Comprehensive smoking treatment was provided at the workplace including individual counseling, free pharmacotherapy (dual nicotine replacement therapy or varenicline), and 5 weeks of contingency management that reinforced abstinence or reductions in smoking to encourage progress toward quitting. Measures: Primary measures included a smoking status survey administered at the end of treatment at the test sites and before treatment began at the delayed intervention control sites. Analysis: Analyses compared rates of quit attempts and successful abstinence for at least 24 hours between the test and delayed intervention control sites. Results: Twenty-five employees were enrolled in treatment. The majority were single (12/25), black (16/25), and reported their educational attainment as high school or less (18/25). Employees in the test (vs delayed intervention control) sites reported higher rates of quit attempts (66.7% vs 12.5%, P = .02) and success quitting for at least 24 hours (53.3% vs 12.5%, P = .08). Participants rated the treatment as very helpful overall. Conclusion: Findings support the feasibility and efficacy of providing workplace-based smoking cessation services and may inform strategies to increase access to treatment.

Tobacco cessation after cancer diagnosis leads to better patient outcomes. However, tobacco treatment services are frequently unavailable in cancer care settings, and multilevel implementation challenges can impede uptake of new programs. The National Cancer Institute (NCI) dedicated Cancer Moonshot funding through the Cancer Center Cessation Initiative (C3I) for NCI-Designated Cancer Centers to implement or enhance the implementation of tobacco treatment services. We examined a pragmatic application of the RE-AIM framework (reach, effectiveness, adoption, implementation, and maintenance) to evaluate tobacco treatment programs implemented within Cancer Centers funded through C3I. Using three C3I-funded Centers as examples, we describe how each RE-AIM construct was operationalized to evaluate the implementation of a wide range of cessation services (e.g., tobacco use screening, counseling, Quitline referral, pharmacotherapy) in this heterogeneous group of cancer care settings. We discuss the practical challenges encountered in assessing RE-AIM constructs in real world situations, including using the electronic health record (EHR) to aid in assessment. Reach and effectiveness evaluation required that Centers define the setting(s) where cessation services were implemented (to determine the "denominator"), enumerate the patient population, report current patient tobacco use, patient engagement in tobacco treatment, and 6-month cessation outcomes. To reduce site heterogeneity, increase data accuracy, and reduce burden, reach was frequently captured via standardized EHR enhancements that improved the identification of current smokers and tobacco treatment referrals. Effectiveness was determined by cessation outcomes (30-day point prevalence abstinence at 6-months post-engagement) assessed through a variety of data collection approaches. Adoption was measured by the characteristics and proportion of targeted cancer care settings and clinicians engaged in cessation service delivery. Implementation was assessed by examining the delivery of tobacco screening assessments and intervention components across sites, and provider-level implementation consistency. Maintenance assessments identified whether tobacco treatment services continued in the setting after implementation and documented the sustainability plan and organizational commitment to continued delivery. In sum, this paper demonstrates a pragmatic approach to using RE-AIM as an evaluation framework that yields relevant outcomes on common implementation metrics across widely differing tobacco treatment approaches and settings.

Prior studies have established an association between sleep problems during early adolescence and heavy alcohol use/alcohol use disorder (AUD) risk in late adolescence. Less research has explored the association between sleep problems and heavy alcohol use during young adulthood, the period when AUD onset peaks. Moreover, research to date has primarily utilized cross-sectional, between-subjects' methods to examine this relationship, with limited focus on the potential intraindividual variation in these behaviors. Multilevel modeling techniques are well-suited to examine the variability in sleep problems and risky alcohol use over time and the dynamic bidirectional relations among these behaviors. This article reports on 42 heavy-drinking college students at-risk for an AUD based on their responses to a validated alcohol screener who completed daily diaries of sleep and alcohol use and wore a sleep-wake activity monitor (i.e., Philips Respironics Actiwatch 2™) daily for 7 days yielding a total of 294 reports. Hierarchical linear models demonstrated that days of heavy drinking predicted delayed bed and wake times within individuals and those individuals who tended to drink more heavily on average had shorter sleep durations. Conversely, days of shorter sleep duration, earlier wake times, and greater perceived sleep quality upon waking predicted greater alcohol use within individuals, and those who tended to feel more alert upon waking drank more on average. These results highlight important within- and between-person variability in the associations among objective and subjective sleep-related problems and at-risk drinking among young adults. Further, the results have implications for alcohol prevention/intervention strategies for young adults at risk for AUDs. (PsycINFO Database Record

Background:Lung cancer screening and tobacco treatment for patients at high-risk for lung cancer may greatly reduce mortality from smoking, and there is an urgent need to improve smoking cessation therapies for this population.Aims:The purpose of this study is to test the efficacy of two separate, sequential interventions to promote tobacco cessation/reduction compared to standard care in smokers considered high-risk for lung cancer.Methods:The study will recruit 276 current smokers attending a lung cancer screening clinic or considered high-risk for lung cancer based on age and smoking history across two sites. Patients first will be randomized to either standard tobacco treatment (8 weeks of nicotine patch and five individual counselling sessions) or standard tobacco treatment plus personalized gain-framed messaging. At the 8-week visit, all patients will be re-randomized to receive biomarker feedback or no biomarker feedback. Repeated assessments during treatment will be used to evaluate changes in novel biomarkers: skin carotenoids, lung function, and plasma bilirubin that will be used for biomarker feedback. We hypothesize that personalized gain-framed messages and receiving biomarker feedback related to tobacco cessation/reduction will improve quit rates and prevent relapse compared to standard care. Primary outcomes include 7-day point-prevalence abstinence verified with expired carbon monoxide at 8 weeks and mean cigarettes per day in the past week at 6 months.Conclusions:Study findings will inform the development of novel interventions for patients at risk for lung cancer to improve smoking cessation rates.

Background Young adults with higher trait urgency (i.e., a tendency to act rashly in response to heightened affect) may be especially vulnerable to heavy drinking. The current study examined 1) the influence of urgency on daily relations between affect and drinking to intoxication, and 2) whether urgency influenced the effectiveness of naltrexone (vs. placebo) for reducing alcohol use. Methods This study is a secondary analysis of data from 126 (n = 40 female) heavy drinking young adults, ages 18–25, enrolled in a double-blind, 8-week clinical trial comparing brief motivational intervention and either naltrexone or placebo. Multilevel models examined whether trait urgency moderated daily relations between positive and negative affect and drinking to intoxication, measured by an estimated blood-alcohol concentration (eBAC) at or above the legal limit (≥0.08 g%). Person-level interactions examined whether naltrexone was more effective than placebo at reducing the odds of eBAC ≥ 0.08 g% for individuals with higher vs. lower trait urgency. Results On days of greater within-person positive or negative affect, young adults with higher urgency were more likely to drink to intoxication than those with lower urgency. Naltrexone reduced the odds of drinking to intoxication significantly more than placebo, independent of positive or negative urgency. Conclusions Although naltrexone treatment reduced drinking overall, young adults with higher trait urgency were still at increased risk for hazardous drinking following times of strong positive or negative mood. Targeted interventions are needed to reduce the risk of heavy drinking among young adults with high trait urgency.

IntroductionMenthol cigarette use remains a serious public health problem, prompting the consideration of tobacco regulatory efforts to ban menthol cigarettes. The current study uses a novel empirical design to model the potential effects of a ban of menthol cigarettes on smoking behaviour among current menthol smokers.Methods29 non-treatment-seeking adults who smoked menthol cigarettes were recruited in Connecticut in 2017–2018 (n=15 female; n=17 Black, n=10 White, n=5 Hispanic). Repeated-measures analyses examined within-person changes in smoking behaviour when participants were switched from smoking their usual brand menthol cigarettes to a matched-brand non-menthol cigarette for 2 weeks to model a potential ban of menthol cigarettes.ResultsParticipants smoked significantly fewer non-menthol (vs menthol) cigarettes per day (mean decrease=2.2 cigarettes, SD=3.2, p18%, pConclusionsBanning menthol as a characterising flavour in cigarettes may decrease smoking and reduce the addictive potential of cigarettes among current smokers. Results provide additional support for tobacco regulatory policies banning menthol flavour in an effort to improve public health.Trial registrationNCT03075839.

Smoking cessation is crucial for reducing cancer risk and premature mortality. The US Preventive Services Task Force (USPSTF) has recommended annual lung cancer screening with low-dose computed tomography (LDCT), and the Center for Medicare and Medicaid Services recently approved lung screening as a benefit for patients ages 55 to 77 years who have a 30 pack-year history. The Society for Research on Nicotine and Tobacco (SRNT) and the Association for the Treatment of Tobacco Use and Dependence (ATTUD) developed the guideline described in this commentary based on an illustrative literature review to present the evidence for smoking-cessation health benefits in this high-risk group and to provide clinical recommendations for integrating evidence-based smoking-cessation treatment with lung cancer screening. Unfortunately, extant data on lung cancer screening participants were scarce at the time this guideline was written. However, in this review, the authors summarize the sufficient evidence on the benefits of smoking cessation and the efficacy of smoking-cessation interventions for smokers ages 55 to 77 years to provide smoking-cessation interventions for smokers who seek lung cancer screening. It is concluded that smokers who present for lung cancer screening should be encouraged to quit smoking at each visit. Access to evidence-based smoking-cessation interventions should be provided to all smokers regardless of scan results, and motivation to quit should not be a necessary precondition for treatment. Follow-up contacts to support smoking-cessation efforts should be arranged for smokers. Evidence-based behavioral strategies should be used at each visit to motivate smokers who are unwilling to try quitting/reducing smoking or to try evidence-based treatments that may lead to eventual cessation.

Although the primary focus of clinical trials is on between-group comparisons during treatment, these studies can also yield insights into which patient characteristics predict longer term outcomes. Our goal was to identify predictors of good outcome during the 1-year follow-up in the Combined Pharmacotherapies and Behavioral Interventions for Alcohol Dependence (COMBINE) Study.We constructed classification trees and a deterministic forest to predict no heavy drinking days during the last 8 weeks of the 1-year follow-up in COMBINE, based on more than 100 baseline predictors and drinking outcomes during the treatment phase of the study. The COMBINE sample was randomly split into a training and a validation data set. Logistic regression models were fit to compare the predictive performance of tree-based methods and classical methods.A small tree with only two splits and four nodes based on abstinence and good clinical outcome during treatment had fair classification accuracy in the training and the validation samples: area under the curve (AUC) of 71% and 70%, respectively. Drinking outcomes during treatment were the strongest predictors in the deterministic forest. Logistic regression analyses based on four main effects (good clinical outcome, level of drinking during treatment, age at onset of alcohol dependence, and feeling more energetic) had slightly better classification accuracy (AUC = 74%).End-of-treatment outcomes were the strongest predictors of long-term outcome in all analyses. The results emphasize the importance of optimizing outcomes during treatment and identify potential subgroups of individuals who require additional or alternative interventions to achieve good long-term outcome.

OBJECTIVE Drinking goals set at treatment onset predict treatment outcome in patients with alcohol use disorders. Yet the cognitive constructs of goal setting and goal attainment are understudied in young adult drinkers. This study sought to examine how the interplay of goal setting and goal attainment during treatment impacts treatment outcome in a sample of young adult heavy drinkers. METHOD Participants were 128 young adult heavy drinkers (Mage = 21.5 years) who participated in a double-blind, placebo-controlled, 8-week efficacy trial of naltrexone plus brief counseling. Participants were not required to be interested in changing their drinking for inclusion. Drinking goals were assessed at baseline, midtreatment, and end of treatment. Outcomes were peak drinking, typical drinking, and drinking frequency. RESULTS Results from PROCESS serial, multiple mediator models showed that midtreatment goal setting and goal attainment collectively predicted peak drinking (b = 0.87, 95% CI [0.40, 1.37]) and drinking frequency (b = 0.66, 95% CI [0.37, 1.06]). Only midtreatment goal setting mediated the relationship between baseline goal setting and typical drinking (b = 0.35, 95% CI [0.10, 0.85]). Participants who set more ambitious drinking goals at baseline were more likely to set subsequent, ambitious goals; more ambitious goals at midtreatment were associated with better treatment outcomes. CONCLUSION Setting initial, ambitious goals led to further ambitious goals, which ultimately contributed to lower levels of drinking. Thus, cognitive processes during treatment may be an important target of intervention efforts. For example, the inclusion of goal-setting exercises during treatment could serve to improve intervention effects. (PsycINFO Database Record

Introduction Electronic cigarettes (ECs) have emerged as a potential harm-reducing alternative for tobacco smokers. However, the role ECs might play in treatment settings is unclear. We conducted an exploratory study of treatment-seeking smokers enrolling in a standard tobacco treatment program who were provided with either a nicotine or non-nicotine EC to use as needed to cease tobacco smoking. Methods Treatment-seeking smokers received standard tobacco treatment for 8 weeks and were given nicotine transdermal patch therapy, behavioral counseling, and either a nicotine or non-nicotine EC to use as needed. Smoking and EC use patterns were tracked longitudinally to week 24. Results 40 subjects were enrolled into the study. At week 24, 6 subjects (15%) were abstinent, and the mean reduction in reported cigarettes smoked per day was 6.8 ± 12. There were no significant differences in smoking outcomes between those who received a nicotine or non-nicotine EC (proportion abstinent at 24 weeks: nicotine EC = 4/20 (20%); non-nicotine EC = 2/20 (10%); p = 0.66). Among subjects assessed at follow-up, 62.5% were EC non-users. Conclusions The addition of a 2nd generation EC to outpatient tobacco treatment among tobacco smokers is feasible. Among those who quit smoking, half were still using the EC at 6-month follow-up. Appeal of the EC among smokers was variable, and those who had quit smoking tended to switch to lower strength nicotine solutions. Further research is needed to determine whether ECs can reduce harm and be an effective adjunct to existing tobacco treatment interventions.

Objective This study evaluated whether tobacco quitline telephone coaches can be trained to counsel hazardous-drinking smokers to improve smoking cessation success and to limit or abstain from alcohol use. Method Smokers (N = 1,948) who called the New York State Smokers' Quitline and reported hazardous drinking (exceeding sex-specific weekly limits [14 drinks for men, 7 drinks for women] or meeting/exceeding daily drinking limits [5 drinks for men, 4 drinks for women] at least once in the past year) were randomized to receive either brief motivational counseling to limit or abstain from alcohol plus an alcohol reduction booklet added to standard care (Alcohol + Tobacco Counseling; ATC), or only smoking cessation counseling plus a smoking cessation booklet added to standard care (Tobacco-Only Counseling; TOC). Results Acceptable coach adherence was achieved. The intention-to-treat (ITT) analysis showed that ATC was associated with a significantly higher rate of smoking abstinence at 7-month follow-up (13.5%) compared with TOC (10.3%; p = .03). The respondent analysis (ATC= 26.2%; TOC = 20.4%) paralleled the ITT findings. When controlling for treatment condition, participants who did not report any heavy drinking were significantly more likely to quit smoking than those who reported any heavy drinking (OR = 1.87, 95% CI [1.29, 2.71]; p = .001). Conclusions A brief alcohol intervention plus standard care via a telephone quitline resulted in significantly higher smoking cessation rates for hazardous-drinking callers. Given that quitline coaches were trained to provide the intervention with acceptable adherence, the potential to extend this intervention for wide-scale implementation and impact is promising.

BACKGROUND: The goal of the current study was to use tree-based methods (Zhang and Singer, 2010, Recursive Partitioning and Applications, 2nd ed. Springer, New York) to identify predictors of abstinence from heavy drinking in COMBINE (Anton et al. JAMA 2006; 295:2003), the largest study of pharmacotherapy for alcoholism in the United States to date, and to validate these results in PREDICT (Mann et al. Addict Biol 2012; 18:937), a parallel study conducted in Germany. METHODS: We compared a classification tree constructed according to purely statistical criteria to a tree constructed according to a combination of statistical criteria and clinical considerations for prediction of no heavy drinking during treatment in COMBINE. We considered over 100 baseline predictors. The tree approach was compared to logistic regression. The trees and a deterministic forest identified the most important predictors of no heavy drinking for direct testing in PREDICT. RESULTS: The tree built using both clinical and statistical considerations consisted of 4 splits based on consecutive days of abstinence (CDA) prior to randomization, age, family history of alcoholism, and confidence to resist drinking in response to withdrawal and urges. The tree based on statistical considerations with 4 splits also split on CDA and age but also on gamma-glutamyl transferase level and drinking goal. Deterministic forest identified CDA, age, and drinking goal as the most important predictors. Backward elimination logistic regression among the top 18 predictors identified in the deterministic forest analyses identified only age and CDA as significant main effects. Longer CDA and goal of complete abstinence were associated with better outcomes in both data sets. CONCLUSIONS: The most reliable predictors of abstinence from heavy drinking were CDA and drinking goal. Trees provide binary decision rules and straightforward graphical representations for identification of subgroups based on response and may be easier to implement in clinical settings. Language: en

Sleep disturbance and heavy drinking increase risk of negative consequences in college students. Limited research exists on how they act synergistically, and the overall nature of sleep and sleep-related impairment in college student drinkers is poorly understood. A latent profile analysis was conducted on the sleep characteristics and daytime sleep-related consequences of college student drinkers who were at-risk based on Alcohol Use Disorders Identification Test-Consumption scores.Participants (N = 312, mean age = 18.90 (0.97) years) consumed a mean (SD) of 20.93 (13.04) drinks per week. Scores on the 10 items of the Sleep/Wake Behavior Problems Scale (SWPS) were the class indicators.Four classes best described the sleep and sleep-related consequences of at-risk college drinkers. Classes represented different gradients and types of sleep patterns and sleep-related impairment; nearly half the sample reported late bedtimes and daytime consequences of insufficient sleep. Subsequent validation analyses indicated that these classes were directly correspondent with severity of alcohol consumption, alcohol-related consequences illicit substance use, and perceived health.These findings indicate the presence of significant heterogeneity in college drinkers' sleep patterns and experiences of sleep-related impairment. Class differences significantly impact the level of alcohol and drug use and the consequences members experience. Greater alcohol use and sleep/wake problems are associated with increased risk for negative consequences for certain classes. These results suggest that college drinking interventions could benefit from the incorporation of sleep-related content and the value in adding brief alcohol assessments and interventions to other college health treatments.