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BACKGROUND Family history of alcohol use disorder; AUD (FH +) and impulsivity-related traits are known risk factors for problem drinking that have been investigated in predominately White samples. This cross-sectional study examined whether these risk factors vary by sex in the overall, majority White sample and in a Black subsample. METHOD A model building regression procedure was used to investigate the combined effect of FH + and impulsivity-related traits on alcohol quantity, frequency, and problems by sex (overall sample: N = 757, 50% female, 73% White, agemean = 33.74, SD = 11.60; Black subsample: n = 138, 47% female, agemean = 33.60, SD = 9.87). RESULTS Overall Sample. No sex differences were found in the compounding effects of FH + and impulsivity-related traits on alcohol outcomes. Males reported more physical, social, and overall alcohol-related problems than females. FH + was positively associated with all alcohol-related consequences. Poor self-regulation was the only trait associated with all alcohol outcomes. Black Subsample: A three-way interaction suggested a negative association between inhibition and frequency of alcohol use among FH + males only. A two-way interaction also suggested impulse control was associated with more interpersonal alcohol-related problems among males only. Main effects were also found in the expected direction such that higher impulsivity and FH + were associated with poorer alcohol outcomes. CONCLUSION These findings suggest no sex differences in the overall sample in the interactive effects of established risk factors for AUD on alcohol outcomes, and that poor self-regulation may be key for personality-targeted alcohol prevention and intervention programs. Preliminary findings of sex differences in the Black subsample should be replicated. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Prior research suggests that cannabis expectancies are related to cannabis misuse and problems. Although there are established measures of cannabis expectancies, existing measures have psychometric limitations and/or are lengthy. Existing measures typically have a two-factor structure of positive and negative expectancies, but recent conceptualizations of alcohol expectancies support a valence- (positive vs. negative) and arousal-based (high vs. low arousal) structure. Thus, the present study sought to test a similar structure for cannabis. Cannabis expectancy items underwent 2 preliminary studies, assessing item valance/arousal (n = 233) and relevance to cannabis (n = 124). A final pool of 76 items underwent exploratory factor analysis (n = 303), and remaining items underwent confirmatory factor analysis in a separate sample (n = 469). Lastly, an additional sample (n = 435) examined validity. Results suggested a 3-factor structure (general positive, high arousal negative, low arousal negative) for the 17-item Anticipated Effects of Cannabis Scale (AECS), which was invariant across cannabis use frequency, sex, and race/ethnicity. Positive expectancies were strongly associated with cannabis use, whereas low arousal negative expectancies were protective against cannabis frequency; high arousal negative expectancies were strongly associated with more negative consequences and dependence symptoms. In addition, the proposed interpretation of AECS test scores showed evidence of incremental validity relative to another abbreviated measure. The current study provides initial support for the AECS, a brief, psychometrically sound cannabis expectancies measure. The AECS captures the full range of cannabis effects and may be suited to test discrepancies between cannabis expectancies and subjective response. Additional research is needed to validate its structure and predictive utility. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Introduction E-cigarette dependence measures largely focus on e-cigarette use (“vaping”) that is linked to nicotine use, and measures assessing sensory aspects of vaping that may influence use (e.g., taste) are limited in scope. Thus, we developed the novel Sensory E-cigarette Expectancies Scale (SEES). Methods In Summer 2017, 610 adult e-cigarette users (48.7% male, 84.9% White, 37.41[±12.15] years old) completed an online survey that included 23 SEES items. Psychometric analyses included evaluating latent structure, internal consistency, measurement invariance, mean differences, and test-criterion relationships. Results Factor analyses supported a 9-item, 3-subscale structure (taste/smell, pleasure/satisfaction, vapor cloud production). Subscales evidenced internal consistency and scalar invariance by sex, race, smoking status (current/not), vaping status (daily/not), e-liquid nicotine content (yes/no), and device type (cig-a-likes/vape-pens/Advanced Personal Vaporizers [APVs]/Mods). Women and daily e-cigarette users reported stronger SEEs for taste/smell and pleasure than their counterparts. Non-white participants reported stronger SEEs for cloud production than White participants. Cig-a-like users reported the weakest SEEs for taste/smell and weaker SEEs linked to cloud production than APV/mod users. SEES scores evidenced convergence with nicotine dependence (mean r = .36). Finally, SEES scores predicted vaping frequency and habitual vaping concurrently and incrementally beyond nicotine dependence. Conclusions The SEES evidenced good psychometric properties, suggesting that the measure can be used to assess sensory vaping expectancies in adults. Importantly, SEES scores indicated that sensory expectancies are related, yet distinct, from nicotine dependence. Future research should evaluate how SEEs relate to product characteristic preferences and patterns of vaping including the development and maintenance of addiction.

Rates of e-cigarette use are high among youth, and there is little known about the long-term health effects of e-cigarettes. Since peer influence is a powerful determinant of tobacco use, we aimed to identify message themes about e-cigarettes that youth would use to encourage or discourage peers from using e-cigarettes. We conducted 10 focus groups (N = 69) with non-smokers and smokers from one middle school, high school and college in Connecticut. Participants engaged in a discussion about e-cigarettes, and each participant created one written message to encourage e-cigarette use and one to discourage use among peers. We content-analyzed the messages and identified three main themes and 12 encouraging and discouraging sub-themes. Encouraging themes included health benefits of e-cigarettes relative to cigarettes, attractive product characteristics (e.g. flavors) and social advantages (e.g. positive social image) of using e-cigarettes. Discouraging messages included health risks of e-cigarettes relative to cigarettes, unattractive product characteristics (e.g. cost) and social disadvantages (e.g. negative social image of using an e-cigarette). Overall, there were no differences by sex, age group or smoking status in generation of encouraging and discouraging message themes. This study identified youth-generated themes that may aid in e-cigarette prevention among youth.

Introduction E-liquid flavor is typically presented by flavor category (e.g. menthol, mint, fruit, dessert). Cooling sensations produced by flavor additives such as menthol enhance appeal of e-cigarettes among youth, but not all e-liquids that produce cooling sensations are labeled as menthol. Sensory experiences produced by flavors may allow for a new way to capture e-cigarette flavor use. This study aims to examine use of flavors that produce cooling sensations among youth and its association with e-cigarette use behaviors. Methods A 2019 survey of high school students (n = 4875) examined use of e-cigarette flavors that produced cooling sensations (cooling flavors) among past 30-day e-cigarette users. E-cigarette use behaviors (flavor use, nicotine use, frequency of use) were examined between those who did and did not use cooling flavors. A binary logistic regression was used to examine associations between vaping frequency, nicotine (vs. non-nicotine) use, and vaping cooling flavors while controlling for demographics, number of flavors vaped in the past month, and vaping age of onset. Results 51.6% (n = 473/916) of the analytic sample endorsed vaping cooling flavors. There were no demographic differences by vaping cooling flavors. Vaping cooling flavors was associated with vaping more frequently (AOR:1.04,95% CI:1.03,1.05) and vaping nicotine (AOR:2.37,95% CI:1.53,3.67). Conclusion Vaping cooling flavors was associated with greater nicotine vaping and frequency of e-cigarette use. Assessing sensory experience, such as cooling, in addition to flavor category may more fully capture e-cigarette flavor use and its impacts on youth e-cigarette use behaviors.

Introduction JUUL, a closed system e-cigarette with disposable pods, is popular among youth, with positive attributes of this product linked to current use by youth. However, many youth try JUUL and do not continue using; understanding differences in the appeal of this device between current users and those who chose not to continue use can inform regulation and prevention efforts. The aim of the current study is to compare JUUL appeal in youth among past users (ie, used, but not in past month) and current users (ie, used in past month). Methods A cross-sectional survey was conducted in four Connecticut high schools in Spring 2018. This survey assessed JUUL use and reasons for liking/disliking JUUL, including its' pharmacological effects (eg, nicotine “buzz”), product characteristics (eg, flavors), peer influence, appeal compared to other e-cigarettes, and concealability. Logistic regressions were conducted to examine differences in liking/disliking JUUL by use status (past vs. current). Results Among JUUL users (N = 1374; 43% of total sample), 30.4% were past users and 69.6% were current users. Compared to current users, past users were less likely to like JUUL for positive pharmacological effects (eg, nicotine “buzz”), product characteristics (eg, flavors), and peer use and more likely to dislike JUUL for the adverse pharmacological effects (eg, headache), product characteristics (eg, flavors), and for “other” reasons (open-ended response; eg, perceived harm). Conclusions Findings suggest that altering JUUL appeal through regulating nicotine content and flavors may be key in policy aimed at shifting youth to become past JUUL users. Implications This study investigates how current and past youth JUUL users differ in their report of the appeal of JUUL. Past users are less likely to report experiencing positive pharmacological effects and product characteristics of JUUL and are less likely to report appeal due to peer use. Understanding how appeal of JUUL may differ among past and current users can aid in our understanding of how to regulate these products so that they are less appealing to current youth users.

Objectives We evaluated the appeal and use of e-cigarette product features in a sample of high school students in Connecticut. Methods In 2015, we conducted school-wide surveys in 8 high schools and analyzed data from 1765 students (877 susceptible tobacco-naive never-e-cigarette users, 315 susceptible tobacco-exposed never-e-cigarette users, and 656 current e-cigarette users). Students were asked: "What is cool about e-cigarettes?" Response options included e-liquid ingredients (eg, flavors, nicotine content, propylene glycol/vegetable glycerin ratio [ie, PG/VG), the heating source (eg, battery), and physical design (eg, color, shape, appearance). Students were asked: "How do you customize your e-cigarette?" (Change flavors, voltage, PG/VG levels, temperature, skin/tank color, other) and use of nicotine in the e-liquid (yes/no). Multivariable regression assessed associations between current e-cigarette users' customization and e-cigarette use frequency (#days/month). Results Flavors were the most appealing product feature among all groups. Among current users, using nicotine e-liquid was more prevalent than changing flavors (44.2% vs 29.6%). Using nicotine e-liquids and changing PG/vG ratios were associated with more frequent e-cigarette use among current users. Conclusions These findings can inform tobacco regulatory actions that put forth evidence-based recommendations to manufacture e-liquid flavors, nicotine concentrations and PG/VG ratios that prevent e-cigarette initiation and escalation of use.

In recent years, the tobacco use landscape among youth has changed greatly, underscoring a need to understand current tobacco product initiation patterns. This study aimed to examine if adolescents’ first tobacco product tried differs by race/ethnicity and socioeconomic status (SES). Cross-sectional survey data were collected from 6 Connecticut high schools in Spring 2019 (N = 4875). The analytic sample comprised ever users of tobacco products who reported on the first tobacco product they tried (N = 2530; 53.6% female). Of ever tobacco product users, 64.6% reported that their first tobacco product tried was an e-cigarette, 24.4% reported blunts, 6.5% reported another tobacco product, and 4.5% reported cigarettes. A multinomial logistic regression model examined race/ethnicity and SES as predictors of the first tobacco product tried with cigarettes as the reference group. Compared to Non-Hispanic (NH) White students, NH Black students (OR = 0.38, 95%CI = 0.17–0.82), Hispanic students (OR = 0.44, 95%CI = 0.27–0.71), and students of other NH races (OR = 0.30, 95%CI = 0.18–0.52) were less likely to report initiating tobacco product use with e-cigarettes. Additionally, compared to NH White students, NH Black students were more likely to report using blunts as their first tobacco product (OR = 3.01, 95%CI = 1.38–6.56). Compared to low SES, middle SES (OR = 1.62, 95%CI = 1.04–2.52) was associated with greater odds of reporting e-cigarettes as the first tobacco product. These findings suggest that youth of different backgrounds initiate tobacco use with different tobacco products and tailored prevention strategies are needed.

Objectives In November 2018, JUUL, Inc. restricted sales of mango, fruit medley, crème brûlée, and cucumber pods to its website. Physical/online sales of tobacco, menthol, and mint pods continued. We examined rates of adolescent JUUL device and flavored pod use before and after restrictions were implemented to examine their potential impact. Methods Students from 4 Connecticut high schools completed cross-sectional surveys in 2018 (N = 3170) and 2019 (N = 3074). Results Compared to 2018, current (past-month) JUUL use decreased in 2019 (30.2–25.6%). Among current JUUL users, restricted flavor use (mango [62.8–36.9%]; cucumber [27.7–11.9%]; fruit [23.5–11.4%]; crème brûlée [12.3–5.0%]) and the total number of flavors used (2.09[SD = 1.71]-1.51[SD = 1.33]) decreased (p-values < .001), while mint pod use increased (62.0–68.6%, p < .01). Tobacco and menthol pod use remained stable. Conclusions Following voluntary sales restrictions implemented by JUUL, Inc., restricted flavor use and the total number of flavors used decreased among JUUL users while mint use increased. Results suggest flavor restrictions may impact adolescents’ e-cigarette use. While 2020 Food and Drug Administration restrictions on mint pods may further limit youth JUUL use, research is needed to determine where youth acquire restricted flavors and if restrictions prompt increased popularity of unrestricted devices/e-liquids.

Introduction E-cigarettes appeal to adolescents because of alternative uses, such as dripping (i.e., applying e-liquid directly on the atomizer) and conducting vape tricks (i.e., creating shapes from exhaled aerosol). However, little is known about these behaviors and adolescents who engage in these behaviors. Methods Using cross-sectional surveys from 4 high schools in Connecticut in 2017 (N = 2945), we assessed the frequency of dripping and conducting vape tricks, product characteristics (e.g., nicotine, flavor) used for these behaviors, and where adolescents learn about these behaviors. We also conducted multinomial logistic regression analysis to assess whether demographics, age of e-cigarette use onset, past-month-use of e-cigarettes, and lifetime use of other tobacco products were associated with dripping and/or vape tricks. Results Among ever e-cigarette users (N = 1047), 20.5% ever dripped and 54.9% ever conducted vape tricks. The most frequently endorsed 1) flavors used for both behaviors were fruit, candy, and mint, 2) nicotine concentrations used for dripping was 3 mg and for vape tricks was 0 mg, and 3) the top source for learning these behaviors were friends. The multinomial model showed that earlier age of e-cigarette use onset, past-month-use of e-cigarettes, and lifetime use of other tobacco products were associated with dripping and vape tricks. Discussion Engaging in dripping and vape tricks was associated with risky tobacco use behaviors (e.g., earlier age of onset, other tobacco use), and involved exposure to nicotine and flavors. Reducing appeal of dripping and vape tricks and preventing product characteristics that facilitate these behaviors may reduce harm to adolescents.

Background Identifying risk factors for youth e-cigarette use is critical, given high rates of e-cigarette use and unknown health effects of long-term use. The current study examined whether an early age of onset of e-cigarette use mediates the association between impulsivity and e-cigarette frequency. Methods Cross-sectional survey data of e-cigarette users (n = 927) were collected from 8 high schools in southeastern Connecticut. The sample was 44.7% female (mean age 16.2 [SD = 1.2], mean age of e-cigarette onset 14.7 [SD = 1.6]). Two domains of self-reported, trait impulsivity were assessed using the abbreviated Barratt Impulsiveness Scale: impaired self-regulation (e.g., problems with concentration or self-control) and behavioral impulsivity (e.g., doing things without thinking). Mediation was tested with Mplus, and the model included school as a cluster variable and controlled for covariates related to e-cigarette use (i.e., sex, age, race, peer use, and other tobacco products ever tried). Results The hypothesized mediation was supported for both domains of impulsivity (impaired self-regulation a 1 b = 0.09, SE = 0.02, 95%CI [0.03–0.14], p = .002; behavioral impulsivity a 2 b = 0.07, SE = 0.03, 95%CI [.01–.14], p = 0.03). Specifically, impaired self-regulation ( B = −0.33, SE = 0.06, p 0.001) and behavioral impulsivity ( B = −0.26, SE = 0.11, p = 0.02) predicted trying e-cigarettes at an earlier age, and earlier initiation was associated with more days of e-cigarette use in the past month ( B = −0.28, SE = 0.08, p 0.001). Conclusions Adolescents who endorse aspects of impulsivity, such as acting without thinking, are at greater risk for more frequent e-cigarette use through an early age of e-cigarette initiation. Further research is needed to evaluate these relationships longitudinally and to develop targeted e-cigarette interventions for impulsive youth.

Objective We examined the associations between socioeconomic status (SES) and adolescent polytobacco use profiles (including e-cigarettes and blunts). Methods Adolescents (N = 1932) completed surveys conducted in 2014 in 3 Connecticut high schools. Within a Latent Class Analysis (LCA) framework, logistic regressions examined associations between SES and polytobacco use profiles comprising never, ever, and current e-cigarette, blunt, cigarette, cigar, cigarillo, hookah, and smokeless tobacco use. Results We identified 5 classes: (1) current polytobacco users; (2) ever polytobacco users; (3) current e-cigarette, blunt, and cigarette users; (4) ever e-cigarette and blunt users; and (5) never users. Low SES, relative to high SES, was associated with greater likelihood of being: (1) an ever polytobacco user; (2) a current e-cigarette, blunt, and cigarette user; and (3) an ever e-cigarette and blunt user, relative to a never user. Conclusions Low SES is associated with membership in distinct polytobacco use latent classes. Regulatory initiatives that focus exclusively on cigarette use may miss the opportunity to influence adolescent use of other products, which may be especially relevant to low-income individuals. Future research should examine whether targeting a broader range of products reduces SES-related tobacco use disparities.

Objectives We examined sources of e-cigarette acquisition among youth, and changes in these sources, between 2014 and 2015. We also assessed whether youth were ever refused the sale of e-cigarettes. Methods Anonymous, cross-sectional surveys conducted in five high schools in 2014 and 2015 in Connecticut assessed demographics, e-cigarette and cigarette use, and e-cigarette acquisition sources (friends/boyfriends/girlfriends, tobacco shops, siblings, online, parents/adult family members, other). We restricted analyses to adolescents younger than 18 years old who had used e-cigarettes in the past month (2014: N = 400, 2015: N = 390). Results Top sources of e-cigarette acquisition were friends (2014: 50.2%, 2015: 45.4%), tobacco shops (2014: 17.5%, 2015: 12.6%), and online shops (2014: 9.8%, 2015: 10.5%). A multilevel model, controlling for sex, age, and cigarette smoking status, while clustering by schools showed a decrease in the proportion of youth obtaining e-cigarettes from friends (AOR = .84) between 2014 and 2015. In 2015, 69.8% and 85.8% purchased e-cigarettes from a physical store and an online store, respectively. Conclusions Peers were the most popular source of e-cigarette acquisition. Many adolescents were able to purchase e-cigarettes from commercial sources. Future studies should continue to conduct surveillance of where adolescents obtain e-cigarettes to inform prevention strategies.

Introduction Most tobacco use is initiated during adolescence and susceptibility is an important predictor of initiation. Research is needed to understand susceptibility across tobacco products among youth to inform prevention efforts. Aims and Methods We surveyed 2945 students from four Southeastern Connecticut high schools in 2017. We assessed susceptibility to future use of seven different tobacco products (ie, cigarettes, e-cigarettes, hookah, cigars, cigarillos, blunts, and smokeless tobacco) among youth who had never used a tobacco product. Susceptibility was coded as any response other than “definitely not” to three items assessing (1) curiosity, (2) willingness to experiment with the product in the future, and (3) willingness to try if offered by a friend. Latent class analysis was used to identify patterns of susceptibility across multiple tobacco products and sociodemographic predictors of these classes. Results Among n = 1246 youth who had never tried a tobacco product, 51.2% (n = 638) were susceptible to at least one product and 29.1% (n = 363) were susceptible to two or more products (average among susceptible youth: M = 2.4 products, SD = 1.7, range 1–7). Latent class analysis identified three classes: youth who were: (1) susceptible to all products (5.6%), (2) susceptible to e-cigarettes, hookah, and blunts (23.6%), and (3) mostly non-susceptible to all products (70.8%). In a multivariable model, demographic variables and peer tobacco use predicted class membership. Conclusions We observed high rates of susceptibility to non-traditional tobacco products among youth, and many youth were susceptible to more than one product. Targeting susceptibility across multiple tobacco products may be important for reducing youth tobacco use. Implications Patterns of polytobacco use susceptibility were identified among youth who had never previously used tobacco products. Many youth were susceptible to more than one product and we observed three distinct classes of susceptibility among youth: those who were mostly non-susceptible, those who were susceptible to alternative or non-traditional tobacco products (e-cigarettes, hookah, and blunts), and those who were susceptible to all tobacco products. These findings suggest the importance of addressing susceptibility across multiple tobacco products.

Introduction JUUL is a closed-system e-cigarette that uses disposable pods with high concentrations of nicotine. JUUL use among youth arose exponentially since 2015, thus, it is essential to understand youths’ reasons for liking/disliking JUUL to inform the regulation of the product. Methods A cross-sectional survey was conducted in 4 high schools in Connecticut in 2018 (N = 3170). The survey assessed JUUL use in the past month and reasons for liking/disliking JUUL, which included pharmacological effects (e.g., subjective nicotine and/or flavor effects), product characteristics (e.g., flavors, nicotine, shape), peer influence (e.g., friends’ use), comparisons to other e-cigarettes (e.g., lower harm), and concealability (e.g., hide from authority). Results 30.2% (N = 956) were past-month users who used a JUUL on an average of 13.6 days (SD = 11.7; 25% reported daily use). The top reasons for liking JUUL were: “it gives me a buzz” (52%), “I like the flavors” (43%), and “my friends use it” (36%). The top reasons for disliking JUUL were: “the pods are expensive” (57%), “nicotine is too high” (20%), and “it gives me a headache” (18%). Regression models indicated that liking JUUL because of the buzz, ability to help concentrate, nicotine level, and ease of hiding it from teachers were associated with more days of use in the past month, while peer influence was negatively associated. Furthermore, disliking the high cost of pods was associated with more frequent use. Conclusions Comprehensive policies that regulate device characteristics that appeal to youth (e.g., nicotine level, flavors) are needed to prevent JUUL use among youth.

Background Extensive research indicates that having a positive family history of alcohol use disorder (FHP) and impulsivity are 2 risk factors for problem drinking. To our knowledge, no study has investigated which facets of impulsivity interact with family history to increase risk for problem drinking. The goal of this study was to: (i) examine whether FHP individuals with higher levels of impulsivity are more likely to engage in problematic drinking, and (ii) identify which facets of impulsivity interact with FHP to increase risk for problems. Methods The data consisted of a combined sample of 757 participants (50% female, 73% White, mean age = 32.85, SD = 11.31) drawn from the Transdisciplinary Tobacco Use Research Center and the Center for the Translational Neuroscience of Alcohol. Analyses of covariance and cumulative logistic regression models investigated the association of family history and impulsivity-related traits with drinking quantity, frequency, and alcohol-related problems. Models were adjusted for age, sex, race, ethnic group, education level, and data source. Results Significant interactions between impulsivity and family history were found for measures of alcohol-related problems. Specifically, there was a stronger positive association of Barratt Impulsiveness Scale (BIS) poor self-regulation with interpersonal, F(1, 504) = 6.27, p = 0.01, and impulse control alcohol-related problems, F(1, 504) = 6.00, p = 0.01, among FHP compared to FHN individuals. Main effects of family history and impulsivity on alcohol quantity and frequency of use and problems were also found. Conclusions These findings suggest that having both a family history of AUD and high BIS poor self-regulation is more strongly associated with alcohol-related consequences in the interpersonal and impulse control domains. Given the heterogeneity of impulsivity, these findings highlight the need for additional research to examine which facets of impulsivity are associated with which alcohol outcomes to narrow phenotypic risk for alcohol misuse.

Background Effective electronic cigarette (e-cigarette) prevention messages are needed to combat the rising popularity/uptake of e-cigarettes among youth. We examined preferences for e-cigarette prevention messages that either emphasized gains (e.g., You save money by not using e-cigarettes) or losses (e.g., You spend money by using e-cigarettes) among adolescents and young adults. Methods Using surveys in two middle schools, four high schools, and one college in CT ( N = 5405), we assessed students' preferences for gain- or loss-framed e-cigarette prevention messages related to four themes: financial cost, health risks, addiction potential, and social labeling as a smoker. We also assessed whether preferences for each message framing theme differed by sex, school level, cigarette-use status, and e-cigarette use-status. We also examined whether preference for message framing differed by cigarette and e-cigarette susceptibility status among never e-cigarette users. Results Overall, loss-framing was preferred for message themes related to health risks, addiction potential, and social labeling as a smoker, whereas gain-framing was preferred for message themes related to financial cost. Logistic regression analyses showed that 1) females preferred loss-framed messages for all themes relative to males, 2) lifetime e-cigarette users preferred loss-framed health risks and social labeling messages relative to never users, and 3) high school students preferred gain-framed social labeling messages relative to college students. The preference for message framing did not differ by cigarette or e-cigarette susceptibility. Conclusions Preference for message framing differed by themes and individual characteristics. This formative research could inform the construction of persuasive e-cigarette prevention messages.

Introduction Although limited in empirical support, Alcohol Expectancy (AE) theory posits that AEs may overestimate subjective response (SR) to the positive effects of alcohol, which, in turn, confers alcohol-related risk (e.g., Darkes & Goldman, 1993). The recent development of the Anticipated Effects of Alcohol Scale (AEAS; Morean, Corbin, & Treat, 2012) and the Subjective Effects of Alcohol Scale (SEAS; Morean, Corbin, & Treat, 2013) now permits direct AE–SR comparisons using psychometrically sound assessments designed for this purpose. Methods We ran secondary data analyses (Morean et al., 2012, 2013) evaluating measurement invariance of AEs and SR; AE–SR relationships; the accuracy of AEs; and relations between AE–SR discrepancies and binge drinking, driving after drinking, and alcohol-related problems in a sample of 102 young adults (mean age 22.81 [2.25]; 74.5% male; 76.5% Caucasian) who consumed alcohol in a simulated bar setting (target blood alcohol level = .08 g/dL). Results The AEAS and SEAS were scalar measurement invariant and that AEs generally overestimated SR (mean Cohen's d = .48). Relative to SR, inflated high arousal negative AEs (e.g., aggressive) were associated with frequent binge drinking and alcohol-related problems, whereas exaggerated low arousal negative AEs (e.g., woozy) served protective functions. As blood alcohol levels rose, inflated low arousal positive AEs (e.g., relaxed) and low arousal negative AEs (e.g., wobbly) were associated with less frequent driving after drinking. Conclusions Challenging AE–SR discrepancies for high arousal effects may have utility in treatment and prevention efforts, whereas maintaining overestimates of low arousal effects may serve protective functions.

Introduction Preliminary evidence suggests adolescents use e-cigarettes in school. However, little is known about the types of devices that are used in schools, where they are used, and who uses them. Knowledge about these issues is critical to inform school regulations. Methods Cross-sectional surveys were conducted in 6 Connecticut high schools in 2019. Adolescents reported on current use (past 30-day use) of the following e-cigarette devices inschool: JUUL, any pod system other than JUUL, vape pens, disposables, mods, and on deviceuse in different locations: class, bathroom, hallways, outside on school grounds, and other school locations. Separate binary logistic regressions investigated predictors of use (demographics and past month use frequency of each device) in school for each device. Results Overall, 45.0% of current users (N = 1447) used e-cigarettes at school. Among users of each device, prevalence of current use at school varied by device with 45.7% reporting JUUL use, 41.3% other pod use, 34.6% vape pen use, 38.3% disposables use and 27.3% mod use. Current users used devices in bathrooms (75.1%), followed by outside on school grounds (52.2%), classrooms (45.7%), hallways (38.8%) and other school locations (11.7%). Greater e-cigarette past month use frequency for each device was associated with device use in school. Conclusions This study is the first to examine use of specific e-cigarette devices in schools and demonstrates that e-cigarette use frequency predicts school use. Despite rules against vaping, e-cigarette use remains prevalent in many school locations, suggesting alternative strategies such as prevention and e-cigarette education are needed.

Sexual misconduct occurs with disproportionate frequency on college campuses, and alcohol is involved in most sexual assaults. Importantly, collegiate athletes are at risk for both heavy drinking and sexual misconduct. Thus, the current study evaluated the efficacy of a novel, 2.5-hr, peer-facilitated, interactive, group-based bystander intervention program for student athletes that integrated information on sexual misconduct and risky drinking (Preventing and Responding to Sexual Misconduct [PRSM]). In all, 205 athletes completed 25-min surveys immediately before and after the training, and 76 (of 94 invited) completed a 3-month follow-up. Participating in the workshop was associated with significant increases in acknowledgment that sexual misconduct is a problem on campus, knowledge of where to get help if sexual misconduct occurs, knowledge about the college’s procedures for addressing sexual misconduct, confidence that the college’s procedures for addressing sexual misconduct are fair, bystander confidence, and engagement in a range of bystander activities. A significant decrease in rape myths also was observed. Participating in the workshop also produced changes in alcohol-related beliefs and behaviors. After participating in PRSM, athletes reported increased expectations that drinking alcohol can produce negative effects including aggression and acute intoxication. Participating in the workshop also was associated with significant reductions in drinking frequency, the total number of drinks consumed per month, the maximum drinks consumed in 24 hours, the frequency of binge-drinking episodes, and the experience of alcohol-related problems. In sum, the PRSM program evidenced preliminary efficacy as a program designed to increase prosocial bystander behavior and decrease high-risk drinking among collegiate athletes; changes in beliefs and behaviors consistent with reducing risk for sexual misconduct and problem drinking were observed after workshop participation. Future research should evaluate whether the PRSM program is effective for use with other high-risk populations like fraternity members or more diverse institutions of higher education including large universities.

Introduction Psychometrically sound measures of e-cigarette dependence are lacking. Methods We modified the PROMIS Item Bank v1.0—Smoking: Nicotine Dependence for All Smokers for use with e-cigarettes and evaluated the psychometrics of the 22-, 8-, and 4-item adapted versions, referred to as The E-cigarette dependence scale (EDS). Adults (1009) who reported using e-cigarettes at least weekly completed an anonymous survey in summer 2016 (50.2% male, 77.1% White, mean age 35.81 [10.71], 66.4% daily e-cigarette users, 72.6% current cigarette smokers). Psychometric analyses included confirmatory factor analysis, internal consistency, measurement invariance, examination of mean-level differences, convergent validity, and test-criterion relationships with e-cigarette use outcomes. Results All EDS versions had confirmable, internally consistent latent structures that were scalar invariant by sex, race, e-cigarette use (nondaily/daily), e-liquid nicotine content (no/yes), and current cigarette smoking status (no/yes). Daily e-cigarette users, nicotine e-liquid users, and cigarette smokers reported being more dependent on e-cigarettes than their counterparts. All EDS versions correlated strongly with one another, evidenced convergent validity with the Penn State E-cigarette Dependence Index and time to first e-cigarette use in the morning, and evidenced test-criterion relationships with vaping frequency, e-liquid nicotine concentration, and e-cigarette quit attempts. Similar results were observed when analyses were conducted within subsamples of exclusive e-cigarette users and duals-users of cigarettes and e-cigarettes. Conclusions Each EDS version evidenced strong psychometric properties for assessing e-cigarette dependence in adults who either use e-cigarette exclusively or who are dual-users of cigarettes and e-cigarettes. However, results indicated little benefit of the longer versions over the 4-item EDS, which provides an efficient assessment of e-cigarette dependence. Implications The availability of the novel, psychometrically sound EDS can further research on a wide range of questions related to e-cigarette use and dependence. In addition, the overlap between the EDS and the original PROMIS that was developed for assessing nicotine dependence to cigarettes provides consistency within the field.

IntroductionMany e-cigarette users find the variety of e-cigarette flavors appealing. We examined whether preferences for e-liquid flavors and the total number of flavors preferred differed between samples of adolescent and adult e-cigarette users. We also examined whether these preferences were associated with e-cigarette use frequency for adolescents or adults, respectively.Materials and methodsThe analytic samples comprised 1) 396 adolescent, past-month e-cigarette users from 5 Connecticut high schools who completed an anonymous, school-based survey in Fall 2014 (56.1% male; 16.18 [1.18] years; 42.2% past-month smokers), and 2) 590 adult, past-month e-cigarette users who completed an anonymous, MTurk survey in Fall 2014 (53.7% male; 34.25 [9.89] years; 51.2% past-month smokers).ResultsCompared to adults, a larger proportion of adolescents preferred fruit, alcohol, and "other"-flavored e-liquids, whereas adults disproportionately preferred tobacco, menthol, mint, coffee, and spice-flavored e-liquids (p-values < .05). Adults also preferred a greater total number of flavors compared to adolescents and used e-cigarettes more frequently (p-values < .001). Flavor preferences uniquely were associated with frequency of e-cigarette use within the adolescent sample; the total number of flavors preferred was associated with more days of e-cigarette use (ηp2 = 0.04), as were preferences for fruit (ηp2 = 0.02), dessert (ηp2 = 0.02), and alcohol-flavored (ηp2 = 0.02) e-liquids.ConclusionsFlavor preferences differed between adolescent and adult samples. While youth reported less frequent e-cigarette use overall, their preferences for specific flavors and the total number of flavors preferred were associated with more days of e-cigarette use, indicating that flavor preferences may play an important role in adolescent e-cigarette use.

Military service is associated with increased rates of heavy drinking. Widely used clinical practices (e.g., motivational interviewing) indicate that addressing both negative and positive drinking consequences is essential to effective treatment. However, research on effectively assessing positive drinking consequences in a clinical population is absent.The current study (1) evaluated the utility of the Positive Drinking Consequences Questionnaire (PDCQ), a measure previously validated in an undergraduate sample, for use with treatment-seeking veterans, and (2) evaluated relationships between positive drinking consequences and alcohol expectancies, pre-treatment alcohol use, and alcohol-related problems.Ninety-seven veterans seeking treatment for alcohol problems completed an anonymous survey (97.9% male; mean age = 49.76[11.40], 67.0% Caucasian).The PDCQ evidenced a single factor latent structure and internal consistency (Cronbach's alpha = .90). Positive drinking consequences and expectancies were related yet distinct constructs. After controlling for demographic factors, experiencing more positive drinking consequences at program intake was associated with heavier pretreatment drinking (ηp(2) = .10, p = .003) and alcohol-related problems (ηp(2) = .18, p.001). Further, PDCQ scores evidenced incremental validity in accounting for pretreatment alcohol use (ηp(2) = .12, p = .002) and alcohol-related problems (ηp(2) = .11, p = .003) when expectancies also were included in the model.Positive drinking consequences are assessed reliably by the PDCQ in a clinical sample and appear to play an important role in the drinking behavior of veterans seeking alcohol treatment.

Introduction Research has shown that adults perceive that electronic cigarettes (e-cigarettes) are effective for smoking cessation, yet little is known about adolescents and young adults' perceptions of e-cigarettes for quitting cigarette smoking. This study describes middle, high school, and college students' beliefs about, and experiences with, e-cigarettes for cigarette smoking cessation. Methods We conducted 18 focus groups (n = 127) with male and female cigarette smokers and nonsmokers in 2 public colleges, 2 high schools, and 1 middle school in Connecticut between November 2012 and April 2013. Participants discussed cigarette smoking cessation in relation to e-cigarettes. Verbatim transcripts were analyzed using thematic analysis. Results All participants, regardless of age and smoking status, were aware that e-cigarettes could be used for smoking cessation. College and high school participants described different methods of how e-cigarettes could be used for smoking cessation: (a) nicotine reduction followed by cessation; (b) cigarette reduction/dual use; and (c) long-term exclusive e-cigarette use. However, overall, participants did not perceive that e-cigarette use led to successful quitting experiences. Participants described positive attributes (maintenance of smoking actions, "healthier" alternative to cigarettes, and parental approval) and negative attributes (persistence of craving, maintenance of addiction) of e-cigarettes for cessation. Some college students expressed distrust of marketing of e-cigarettes for smoking cessation. Conclusions Adolescent and young adult smokers and nonsmokers perceive that there are several methods of using e-cigarettes for quitting and are aware of both positive and negative aspects of the product. Future research is needed to determine the role of e-cigarettes for smoking cessation in this population.

Background Substance use is partially driven by habitual processes that occur automatically in response to environmental cues and may be central to users’ identities. This study was designed to validate the Self-Report Habit Index (SRHI) for assessing habitual marijuana, alcohol, cigarette, and e-cigarette use. Methods We examined the SRHI’s psychometrics in separate samples of adult marijuana ( N s = 189;170), alcohol ( Ns = 100;133), cigarette ( Ns = 58;371), and e-cigarette ( N = 239) users. Results A 6-item, single-factor solution evidenced good fit across substances (CFI marijuana/alcohol/cigarettes/e-cigarettes = 0.996/0.997/0.996/0.994, RMSEA = 0.046/0.047/0.067/0.068, SRMR = 0.017/0.017/0.010/0.015) and internal consistency (α = 0.88/0.94/0.95/0.91). The SRHI was scalar invariant for sex and race. However, independent-samples t -tests indicated only that women endorsed stronger habitual e-cigarette use and that men endorsed stronger habitual marijuana use. The SRHI also was scalar invariant by product type in dual-users (cigarettes/e-cigarettes[ N = 371]; alcohol/cigarettes [n = 58]), although differences in habit strength only were observed for cigarettes versus e-cigarettes, with dual-users reporting stronger habitual cigarette use. Finally, the SRHI predicted frequency of marijuana, alcohol, cigarette, and e-cigarette use (n p 2 [marijuana/alcohol/cigarettes/e-cigarettes] = 0.37/0.48/0.31/0.17) and quantity of alcohol and cigarette use (n p 2 = 0.43/0.33). Conclusions The SRHI is a psychometrically sound measure of adults’ habitual substance use. The SRHI detected mean differences by sex and substance type and predicted the frequency of using each substance. Future research should determine if the SRHI is appropriate for use with other substances or age groups (e.g., adolescents), how it relates to task-based, behavioral measures of habit strength, and the degree to which habit predicts the development or maintenance of addiction.

Quickly progressing from initiating alcohol use to drinking to intoxication recently was identified as a novel risk factor for hazardous drinking in college students (ME Morean et al. [2012] Alcohol Clin Exp Res, 36, 1991-1999). The current study evaluated the risk associated with age of onset (AO) and delay to first intoxication (Delay) in a high school sample.Adolescent drinkers (N = 295, age 16.29 [1.14], 55.3% female, 80.3% Caucasian, AO = 13.51 [2.29] years, Delay = 0.80 [1.43] years) completed an anonymous survey about their substance use in February of 2010. Self-report questions assessed AO and age of first intoxication (AI) (i.e., "How old were you the first time you tried alcohol/got drunk?") and past-month alcohol use/binge drinking (i.e., How often did you drink alcohol/drink ≥5 drinks?).Bivariate correlations indicated that AO was positively correlated with AI and inversely correlated with Delay, the frequency of any drinking, and the frequency of binge drinking. When considered alone, Delay was not significantly correlated with either alcohol use outcome. In contrast, hierarchical regression analyses indicated that when considered in concert, an earlier AO and a shorter Delay were each associated with heavier drinking (any drinking adjusted R(2) = 0.08; binge drinking R(2) = 0.06, p-values0.001) beyond demographic characteristics. Two-way interactions among study variables were nonsignificant, suggesting that AO and Delay conferred risk similarly by racial/ethnic status, gender, and grade in high school.When considered simultaneously, both an early AO and a quick progression to drinking to intoxication appear to be important determinants of high school student drinking. In addition to continuing efforts to postpone AO, efforts designed to delay intoxication may modulate alcohol-related risk associated with early drinking.

Self-reported impulsivity confers risk factor for substance abuse. However, the psychometric properties of many self-report impulsivity measures have been questioned, thereby undermining the interpretability of study findings using these measures. To better understand these measurement limitations and to suggest a path to assessing self-reported impulsivity with greater psychometric stability, we conducted a comprehensive psychometric evaluation of the Barratt Impulsiveness Scale-11 (BIS-11), the Behavioral Inhibition and Activation Scales (BIS/BAS), and the Brief Self-Control Scale (BSCS) using data from 1,449 individuals who participated in substance use research. For each measure, we evaluated (a) latent factor structure, (b) measurement invariance, (c) test-criterion relationships between the measures, and (d) test-criterion relations with drinking and smoking outcomes. Notably, we could not replicate the originally published latent structure for the BIS, BIS/BAS, or BSCS or any previously published alternative factor structure (English language). Using exploratory and confirmatory factor analysis, we identified psychometrically improved, abbreviated versions of each measure: 8-item, 2-factor BIS-11 (root-mean-square error of approximation [RMSEA] = .06, comparative fit index [CFI] = .95); 13-item, 4-factor BIS/BAS (RMSEA = .04, CFI = .96); and 7-item, 2-factor BSCS (RMSEA = .05, CFI = .96). These versions evidenced (a) stable, replicable factor structures, (b) scalar measurement invariance, ensuring our ability to make statistically interpretable comparisons across subgroups of interest (e.g., sex, race, drinking/smoking status), and (c) test-criterion relationships with each other and with drinking/smoking. This study provides strong support for using these psychometrically improved impulsivity measures, which improve data quality directly through better scale properties and indirectly through reducing response burden.

Alcohol expectancy (AEs) research has enhanced our understanding of how anticipated alcohol effects confer risk for heavy drinking and alcohol-related problems. However, extant AE measures have limitations within 1 or more of the following areas: assessing a comprehensive range of effects, specifying the hypothetical number of drinks consumed, assessing AEs by limb of the blood alcohol curve (BAC), and/or not having undergone psychometric evaluation. Building upon the strengths of existing measures, we employed conceptual and statistical advances in measurement development to create the novel, psychometrically sound Anticipated Effects of Alcohol Scale (AEAS). Unique to this study, pilot data ensured that the AEAS comprised a comprehensive sampling of effects that varied in valence (positive/negative) and arousal (low/high) and were identified as plausible outcomes of drinking. The AEAS specified the number of drinks individuals imagined consuming (adjusted for sex) and the hypothetical drinking episode length (2 hr). AEs were also assessed separately by BAC limb. For validation purposes, the AEAS was included in several survey studies of young adults (ages 18-30). The validity argument for the proposed interpretation of AEAS test scores was based upon the following: (a) exploratory and confirmatory factor analyses (N = 546) identified a 22-item, 4-factor internal structure, categorizing alcohol effects into quadrants (high/low arousal crossed with positive/negative valence); (b) scalar measurement invariance was established for BAC limb, sex, and binge drinking status; (c) convergence/divergence was observed with alternative AEs measures and mood; and (d) test-criterion relationships were observed with several alcohol-related outcomes. The reliability argument was based on test-retest and internal consistency coefficients.

Introduction Some traditional cigarette smokers are motivated to smoke to lose weight or control their weight. The current study evaluated whether a subset of adult e-cigarette users reported vaping to lose or control their weight and examined potential predictors of vaping for weight management. Methods Adult e-cigarette users (n = 459) who reported wanting to lose weight or maintain their weight completed an anonymous online survey. Participants reported on demographics, vaping frequency, e-cigarette nicotine content, cigarette smoking status, preferred e-cigarette/e-liquid flavors, current weight status (i.e., overweight, underweight), use of dieting strategies associated with anorexia and bulimia, lifetime history of binge eating, self-discipline, and impulse control. Binary logistic regression was used to examine whether vaping for weight loss/control was associated with the aforementioned variables. Results Participants who reported vaping for weight loss/control (13.5%) were more likely to vape frequently (adjOR = 1.15; 95% CI [1.00, 1.31]); be overweight (adjOR = 2.80; [1.33, 5.90]); restrict calories (adjOR = 2.23; [1.13, 4.42]); have poor impulse control (adjOR = 0.59; [0.41, 0.86]); and prefer coffee- (adjOR = 2.92; [1.47, 5.80]) or vanilla-flavored e-liquid (adjOR = 7.44; [1.56, 36.08]). Conclusions A subset of adult e-cigarette users reported vaping for weight loss/control, raising concerns about expanded, scientifically unsubstantiated uses of e-cigarettes. Identifying where individuals obtain information about vaping for weight loss (e.g., e-cigarette ads, Internet) and whether weight-related motives promote e-cigarette initiation among e-cigarette naive individuals is important to informing regulatory efforts. Further research also is needed to better understand the link between e-liquid flavors and weight loss motivations.

Introduction E-cigarettes are popular in the United States, but psychometrically sound measures of vaping beliefs and behaviors are lacking. Methods We evaluated the psychometrics of the Short Form Vaping Consequences Questionnaire (S-VCQ), a modified version of the Short Form Smoking Consequences Questionnaire that assesses expectancies for negative consequences, positive reinforcement, negative reinforcement, and appetite/weight control associated with vaping. Adult, past-month e-cigarette users completed an anonymous survey in Fall 2015 (N = 522, 50.4% female; 71.5% white; 34.10 [SD = 9.66] years). Psychometric analyses included confirmatory factor analysis, internal consistency, measurement invariance, t tests, correlations, and test-criterion relationships with vaping outcomes. Results The S-VCQ evidenced a four-factor latent structure (Bentler's Comparative Fit Index = .95, Root Mean Square Error of Approximation = .05, Standardized Root Mean Square Residual = .06), and subscales evidenced internal consistency (mean α = 0.89). S-VCQ scores were scalar invariant for sex and smoking status; women reported stronger appetite/weight control than men and dual cigarette/e-cigarette users (n = 309) reported stronger negative vaping consequences and negative reinforcement than nonsmokers. Among dual users, vaping and smoking expectancies also were scalar invariant; dual users reported stronger positive reinforcement associated with vaping than smoking but stronger negative consequences, negative reinforcement, and appetite/weight control associated with smoking than vaping. Correlations indicated that vaping and smoking expectancies were related, yet distinct constructs. Univariate general linear models indicated that vaping frequency and dependence were associated with positive reinforcement (ηp2 = .02/.02), negative reinforcement (ηp2 = .02/.08), and appetite/weight control (ηp2 = .02/.02) from vaping. Conclusions The S-VCQ evidences solid psychometrics as a measure of adult e-cigarette users' vaping expectancies. Implications The current study provides evidence for the reliability and validity of the S-VCQ, the first measure of vaping expectancies that has been validated for use with adult e-cigarette users. Results indicated that the S-VCQ comprises four subscales that evidence internal consistency, scalar measurement invariance for important groups of interest, and test-criterion relationships with vaping outcomes. Researchers are encouraged to consider using this measure for assessing vaping expectancies in adult e-cigarette users.

The Anticipated Effects of Alcohol Scale (AEAS), the Subjective Effects of Alcohol Scale, and the Positive Drinking Consequences Questionnaire (PDCQ) are psychometrically sound measures of alcohol expectancies (expectancies), subjective response to alcohol, and positive drinking consequences, respectively, for use with adults. Prior research using these measures suggests that expectancies, subjective response, and positive drinking consequences are related yet distinct determinants of drinking. The current study presents psychometric evaluations of these measures for use with adolescents including confirmatory factor analyses (CFA) of the previously identified latent structures, internal consistency, and test-criterion relationships. Legally, alcohol cannot be administered to adolescents, so we assessed retrospective subjective response (during the first drinking episode ever [SEAS First] and the most recent drinking episode [SEAS Recent]). The sample comprised 248 Connecticut high school students (53.6% male; mean age 16.50 [1.19] years; 71.4% White) who completed an anonymous survey. CFA confirmed the latent factor structures for each measure. The AEAS, SEAS First, SEAS Recent and the PDCQ were internally consistent (mean α AEAS = .83; SEAS First = .88; SEAS Recent = .89, PDCQ = .87). AEAS subscales evidenced moderate overlap with corresponding SEAS First subscales (mean = .36) and SEAS Recent subscales (mean = .46) and modest overlap with the PDCQ (mean = .17). Expectancies, subjective response, and positive drinking consequences also accounted for significant variance in monthly drinking, lifetime maximum number of drinks consumed, and alcohol-related problems. In sum, the AEAS, the retrospective SEAS, and the PDCQ are psychometrically sound measures for use with adolescents.

Objective There is limited research on adolescents’ use of e-cigarettes and other substances. Materials and methods 2241 Connecticut high school students completed anonymous, cross-sectional surveys assessing e-cigarette and other substance use. We used latent class analysis (LCA) to: (1) classify students based on their past-month use of e-cigarettes, cigarettes, cigars, smokeless tobacco, hookah, blunts, marijuana, and alcohol, and (2) determine if age, sex, or race predicted class membership. Results Past-month e-cigarette use was 11.6%, and use rates for the remaining substances ranged from 2.8% (smokeless tobacco) to 20.7% (alcohol). The optimal latent class solution comprised four classes: (1) primarily abstainers (81.6%; abstainers), (2) primarily e-cigarette and alcohol users (4.6%; E-cigarette–Alcohol), (3) primarily marijuana and alcohol users (6.9%; Marijuana–Alcohol), and (4) primarily users of all products (6.9%; All Products). Compared to abstainers, (1) all substance-using classes comprised older students, (2) the All Products and E-cigarette–Alcohol classes were more likely to comprise males and less likely to comprise Blacks, and (3) the Marijuana–Alcohol class was more likely to comprise Blacks and Latinos. Relative to the All Products and E-cigarette–Alcohol classes, the Marijuana–Alcohol class was more likely to comprise females, Blacks, and Latinos. Conclusions LCA identified four substance use classes, two of which included elevated e-cigarette use. Class membership differed by age, sex, and race. Additional research should evaluate characteristics that may explain the different product use profiles identified in the current study including cultural differences, peer group norms, and differing perceptions of the harmfulness of each substance.

Human laboratory studies have a long and rich history in the field of alcoholism. Human laboratory studies have allowed for advances in alcohol research in a variety of ways, including elucidating of the neurobehavioral mechanisms of risk, identifying phenotypically distinct sub-types of alcohol users, investigating of candidate genes underlying experimental phenotypes for alcoholism, and testing mechanisms of action of alcoholism pharmacotherapies on clinically-relevant translational phenotypes, such as persons exhibiting positive-like alcohol effects or alcohol craving. Importantly, the field of human laboratory studies in addiction has progressed rapidly over the past decade and has built upon earlier findings of alcohol's neuropharmacological effects to advancing translational research on alcoholism etiology and treatment. To that end, the new generation of human laboratory studies has focused on applying new methodologies, further refining alcoholism phenotypes, and translating these findings to studies of alcoholism genetics, medication development, and pharmacogenetics. The combination of experimental laboratory approaches with recent developments in neuroscience and pharmacology has been particularly fruitful in furthering our understanding of the impact of individual differences in alcoholism risk and in treatment response. This review of the literature focuses on human laboratory studies of subjective intoxication, alcohol craving, anxiety, and behavioral economics. Each section discusses opportunities for phenotype refinement under laboratory conditions, as well as its application to translational science of alcoholism. A summary and recommendations for future research are also provided.

Research has consistently identified a family history of alcoholism as a risk factor for alcohol-related problems, and global positive expectancies have been found to moderate this association. High rates of comorbidity between alcohol use and anxiety disorders suggest that a family history of anxiety disorders may also increase risk. Further, expectations of negative reinforcement (e.g., tension reduction) have been found to moderate the influence of anxiety-related traits. The current study sought to extend previous research by examining the influence of parental history of alcoholism, anxiety disorders, and the combination, as predictors of alcohol-related problems. Expectancies of global positive changes and tension reduction were hypothesized to moderate the influence of parental history of alcoholism and anxiety, respectively.Direct interviews with parents assessed their history of alcoholism and anxiety for 144 offspring (ages 18-32; 53.5% male) creating four groups: those with a parental history of alcoholism (27.80%), anxiety (22.20%), both alcoholism and anxiety (33.30%), and no history of psychopathology (16.70%). Established measures assessed the offsprings'alcohol expectancies, alcohol use, and alcohol-related problems.Although expected interactions between parental alcoholism and global positive expectancies and between parental anxiety and tension-reduction expectancies were not found, global positive expectancies were associated with alcohol-related problems among the group with parental history of both alcoholism and anxiety.The results suggest that the relation between parental history of alcoholism and global positive expectancies observed in previous studies may be strongest among individuals with a comorbid parental history of alcohol and anxiety disorders. Incorporating expectancies into interventions targeting individuals with a comorbid parental history of alcohol and anxiety disorders may have utility.

Expected and experienced negative consequences and expected positive consequences of alcohol use have been widely studied, while little attention has been given to experienced positive drinking consequences. Although existing studies suggest that positive consequences may be important [Park, C.L. (2004). Positive and negative consequences of alcohol consumption in college students. Addictive Behaviors, 29, 311-321.; Park, C.L. & Grant, C. (2005). Determinants of positive and negative consequences of alcohol consumption in college students: Alcohol use, gender, and psychological characteristics. Addictive Behaviors, 30, 755-765.], it is not clear if they are distinct from expected positive outcomes or uniquely associated with drinking behavior. The primary goal of the current study was to develop a measure that directly assessed specific, real life drinking consequences rather than relying on general past tense derivations ("I forgot my worries") of expectancy items. Such a measure is necessary to determine whether or not positive consequences are distinct from positive expectancies and to assess the unique contribution of positive drinking consequences to drinking behavior. Participants were 423 undergraduate students who completed an online survey; 277 drinkers (56.5% women) completed all data necessary for analyses. Principal components analysis of the Positive Drinking Consequences Questionnaire (PDCQ) identified a single-factor structure with good internal and split-half reliability. The PDCQ also demonstrated discriminant validity relative to a positive expectancy measure and incremental validity in relation to drinking behavior. Although additional studies with heavier drinking populations are needed, the PDCQ may ultimately serve as a valuable research and clinical assessment tool.

The Acquired Preparedness Model (APM) posits that alcohol expectancies mediate effects of personality traits on drinking outcomes, whereas the Dual Process Model (DPM) suggests that top down behavioral control (e.g. self-control) moderates the impact of bottom up risk factors like alcohol expectancies. This study sought to integrate the APM and DPM by examining the extent to which indirect effects of impulsive sensation-seeking on drinking outcomes are moderated by self-control. We hypothesized that the APM may hold more strongly for people who are higher in self-control, as they may engage in alcohol use for the explicit purpose of meeting sensation seeking goals. Data were from 462 participants (ages 15–63; 58.4% male) who completed one of five studies affiliated with the Center for the Translational Neuroscience of Alcoholism (CTNA). Consistent with the APM, higher levels of impulsive sensation seeking were associated with stronger positive expectancies which, in turn, contributed to heavier drinking and related problems. Consistent with the DPM, among non-dependent drinkers, indirect effects of impulsive sensation seeking on alcohol use were only present among those who were high in self-control. These findings suggest that expectancy challenges may be most effective for those with high levels of self-control prior to the development of alcohol dependence. However, future studies integrating the APM and DPM should include both implicit and explicit measures of expectancies to address the possibility that individuals with lower levels of self-control may be more influenced by automatic or implicit influences, and may therefore respond well to implicit expectancy challenges.

The current study presents a psychometric evaluation of the Yale Craving Scale (YCS), a novel measure of craving for cigarettes and alcohol, respectively. The YCS is the first craving measure to use a generalized Labeled Magnitude Scale (gLMS) as the scoring format, which facilitates between-group comparisons of subjective craving and eliminates ceiling effects by assessing the full range of imaginable sensation intensities.Psychometric evaluations of the YCS for use with cigarettes (YCS Smoking) and alcohol (YCS Drinking) included assessments of latent factor structure, internal consistency, ceiling effects, and test-criterion relationships. Study samples included 493 treatment-seeking smokers and 213 heavy drinkers.Factor analyses of the 5-item YCS Smoking and Drinking scores confirmed a 1-factor scale. The YCS Smoking and Drinking scores evidenced: (1) good internal consistency, (2) scalar measurement invariance within several subgroups (e.g., smoking/drinking status; nicotine/alcohol dependence), (3) convergent relationships with extant craving measures, and (4) concurrent relationships with smoking/drinking outcomes.These results suggest that the YCS represents a psychometrically sound scale for assessing smoking and drinking urges in dependent populations.

Background: This pilot study conducted a preliminary examination of whether Cognitive Bias Modification (CBM), a computerized task to retrain cognitive-approach biases towards smoking stimuli (a) changed approach bias for cigarettes, and (b) improved smoking cessation outcomes in adolescent smokers. Methods: Sixty adolescent smokers received four weeks of Cognitive Behavioral Therapy (CBT) for smoking cessation, with CBM (90% avoidance/10% approach for smoking stimuli and 10% avoidance/90% approach for neutral stimuli) or sham (50% avoidance/50% approach for smoking and neutral stimuli) training in the Netherlands (n = 42) and the United States (n = 18). Results: While we did not observe changes in action tendencies related to CBM, adolescents with higher smoking approach biases at baseline had greater decreases in approach biases at follow-up, compared to adolescents with smoking avoidance biases, regardless of treatment condition (p = 0.01). Intent-to-treat (ITT) analyses showed that CBM, when compared with sham trended toward higher end-of-treatment, biochemically-confirmed, seven-day point prevalence abstinence, (17.2% vs. 3.2%, p = 0.071). ITT analysis also showed that regardless of treatment condition, cotinine level (p = 0.045) and average number of cigarette smoked (p ≤ 0.001) significantly decreased over the course of treatment. Conclusions: The findings from this pilot study suggests that re-training approach biases toward cigarettes shows promise for smoking cessation among adolescent smokers. Future research should utilize larger samples and increased distinction between CBM and sham conditions, and examine mechanisms underlying the CBM approach.

Additional work is needed to determine how and/or why the relationship between alcohol use and increased risk for partner aggression exists. Researchers have begun to examine whether alcohol-related outcome expectancies (i.e., beliefs about the cognitive and behavioral effects of alcohol) are associated with partner aggression irrespective of alcohol use. We examined the relationship between alcohol use, alcohol expectancies, and partner aggression among 360 males arrested for a domestic violence offense and court-mandated to treatment. Results indicate that certain alcohol expectancies do play a role in the relationship between alcohol use and some forms of partner aggression.

Three decades of research demonstrate that individual differences in subjective response (SR) to acute alcohol effects predict heavy drinking and alcohol-related problems. However, the SR patterns conferring the greatest risk remain under debate. Morean and Corbin (2010) highlighted that extant SR measures commonly have limitations within the following areas: assessment of a comprehensive range of effects, assessment of effects over the complete course of a drinking episode, and/or psychometric validation. Furthermore, the consistent pairing of certain SR measures and theoretical models has made integration of findings difficult. To address these issues, we developed the Subjective Effects of Alcohol Scale (SEAS), a novel, psychometrically sound SR measure for use in alcohol administration studies. Pilot data ensured that the SEAS comprised a comprehensive range of effects that varied in terms of valence and arousal and were perceived as plausible effects of drinking. For validation purposes, the SEAS was included in a two-site placebo-controlled alcohol administration study (N=215). Exploratory and confirmatory factor analyses identified a 14-item, 4-factor model categorizing effects into affective quadrants (high/low arousal positive; high/low arousal negative). SEAS scores evidenced the following: (1) scalar measurement invariance by limb of the blood alcohol curve (BAC) and beverage condition (2) good internal consistency, (3) convergence/divergence with extant SR measures, alcohol expectancies, and alcohol use, and (4) concurrent/incremental utility in accounting for alcohol-related outcomes, highlighting the novel high arousal negative and low arousal positive subscales.

The Drug Effects Questionnaire (DEQ) is widely used in studies of acute subjective response (SR) to a variety of substances, but the format of the DEQ varies widely across studies, and details of its psychometric properties are lacking. Thus, the field would benefit from demonstrating the reliability and validity of the DEQ for use across multiple substances.The current study evaluated the psychometric properties of several variations of DEQ items, which assessed the extent to which participants (1) feel any substance effect(s), (2) feel high, (3) like the effects, (4) dislike the effects, and (5) want more of the substance using 100-mm visual analog scales.DEQ data from three placebo-controlled studies were analyzed to examine SR to amphetamine, nicotine, and alcohol. We evaluated the internal structure of the DEQ for use with each substance as well as relationships between scale items, measures of similar constructs, and substance-related behaviors.Results provided preliminary psychometric support for items assessing each DEQ construct (feel, high, dislike, like, and more).Based on the study results, we identify several common limitations of extant variants of the DEQ and recommend an improved version of the measure. The simplicity and brevity of the DEQ combined with its promising psychometric properties support its use in future SR research across a variety of substances.

Background: Subjective response to alcohol (SR), which reflects individual differences in sensitivity to the pharmacological effects of alcohol, may be an important endophenotype in understanding genetic influences on drinking behavior and alcohol use disorders (AUDs). SR predicts alcohol use and problems and has been found to differ by a range of established risk factors for the development of AUDs (e.g., family history of alcoholism). The exact pattern of SR associated with increased risk for alcohol problems, however, remains unclear. The Low Level of Response Model (LLR) suggests that high-risk individuals experience decreased sensitivity to the full range of alcohol effects, while the Differentiator Model (DM) asserts that high risks status is associated with increased sensitivity to alcohol's positive effects but decreased sensitivity to negative effects. Aims: The current paper (1) reviews two prominent models of subjective response, (2) reviews extant laboratory-based research on subjective response, (3) highlights remaining gaps in our understanding and assessment of subjective response, and (4) encourages collaborative efforts to address these methodological and conceptual concerns. Methods: This paper reviews studies which employed placebo-controlled and non-placebo-controlled alcohol challenge paradigms to assess a range of alcohol effects including impairment, stimulation, and sedation. Results: The research literature provides at least partial support for both the LLR and DM models. High-risk individuals have been shown to have a reduced response to alcohol with respect to sedative or impairing effects, particularly on the descending limb of the blood alcohol curve (BAC). There is also evidence that ascending limb stimulant effects are more pronounced or operate differently for high-risk individuals. Discussion: Despite commendable advances in SR research, important questions remain unanswered. Inconsistent results across studies may be attributable to a combination of an inadequate understanding of the underlying construct and methodological differences across studies (e.g., number and timing of assessments across the BAC, inclusion of a placebo condition). With respect to the underlying construct, existing measures fail to adequately distinguish between cognitive/behavioral impairment and sedation, aspects of which may be perceived positively (e.g., anxiolysis) due to their ability to act as negative reinforcers. Conclusions: Addressing the concerns raised by the current review will be integral to making meaningful scientific progress in the field of subjective response. Language: en

Objectives (1) To establish the reliability and validity of a modified version of the Self-Rating of Alcohol (SRE) form. (2) To differentiate early subjective alcohol response (SR) from acquired tolerance in the prediction of drinking outcomes. Method 353 undergraduates completed an online survey. SR was assessed using the SRE form and a modified SRE including items assessing global stimulant and sedative effects. The Daily Drinking Questionnaire-Revised (DDQ-R), and the Rutgers Alcohol Problems Index (RAPI) assessed alcohol use and problems, respectively. Results The revised version of the SRE showed good internal consistency and incremental validity. Early SR assessed by the modified SRE was consistently associated with use and problems. Acquired tolerance was significantly related to use and problems above and beyond early SR. Conclusions The modified SRE incorporating stimulant and sedative responses demonstrated good psychometric properties and the potential to capture unique variability in drinking outcomes. Differentiating early SR from tolerance showed that each contributes uniquely to drinking behavior and problems. Thus, future studies would benefit from examining the unique contribution of each aspect of SR.

There is a paucity of research developing and testing conceptual models of intimate partner violence, particularly for female perpetrators of aggression. Several theorists' conceptual frameworks hypothesize that distal factors-such as personality traits, drinking patterns, and marital discord-influence each other and work together to increase the likelihood of physical aggression. The purpose of the present study was to investigate these variables in a relatively large sample of men and women arrested for domestic violence and court-referred to violence intervention programs.We recruited 409 participants (272 men and 137 women) who were arrested for domestic violence. We assessed perpetrator alcohol problems, antisociality, trait anger, relationship discord, psychological aggression, and physical abuse. We also assessed the alcohol problems, psychological aggression, and physical abuse of their relationship partners. We used structural equation modeling to examine the interrelationships among these variables in both genders independently.In men and women, alcohol problems in perpetrators and their partners contributed directly to physical abuse and indirectly via psychological aggression, even after perpetrator antisociality, perpetrator trait anger, perpetrator relationship discord, and perpetrator and partner psychological and physical aggression were included in the model. The only significant gender difference found was that, in male perpetrators, trait anger was significantly associated with relationship discord, but this path was not significant for women perpetrators.The results of the study provide further evidence that alcohol problems in both partners are important in the evolution of psychological aggression and physical violence. There were minimal differences between men and women in the relationships of most distal risk factors with physical aggression, suggesting that the conceptual framework examined may fit equally well regardless of perpetrator gender. This finding suggests that, in arrested men and women, violence intervention programs might have improved outcomes if they offered adjunct or integrated alcohol treatment.