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Background: Electronic nicotine delivery systems (ENDS) are the most used tobacco product among adolescents and young adults (AYAs) and are increasingly used to vape cannabis. It is unclear what vaping devices and ENDS modifications are used most frequently by AYAs who vape both nicotine and cannabis., Methods: AYAs (aged 14-29) reporting ENDS use in the past 30 days were recruited via Qualtrics (N = 1,011). We conducted three multivariable logistic regression models examining differences in likelihood of: 1) vaping cannabis in the past 30 days; 2) mixing cannabis and nicotine liquids; and 3) using nicotine devices to vape cannabis; based on type of vaping device used most often, controlling for age, socio-economic status, gender, race, frequency of ENDS use, and other cannabis use., Results: 40 % (n = 405) of AYAs reported vaping both nicotine and cannabis in the past 30 days. AYAs who used vape pens most often were more likely to have vaped cannabis concentrates in the past 30 days compared to individuals using disposable vapes (aOR = 2.72, 95 %CI = 1.75-4.21, p < 0.001). AYAs who used open systems most often (i.e., vape pens, mods, or e-hookah) were more likely than individuals using closed systems (i.e., disposable vapes, rechargeable pods or cigalikes) to combine nicotine and cannabis e-liquids (aOR = 2.03, 95 %CI = 1.43-2.89, p < 0.001) or use a nicotine device to vape cannabis (aOR = 1.66, 95 %CI = 1.17-2.34, p = 0.005)., Implications: Co-use of cannabis and nicotine via similar devices, particularly vape pens and other open-systems, warrants collaborative regulatory efforts to mitigate co-use of both substances, with a particular need for increased regulation of cannabis vaping products., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Youth e-cigarette use remains a public health concern and many youth want to quit. However, cannabis use is common among youth who use e-cigarettes, which may interfere with nicotine cessation efforts. This study aimed to investigate cannabis use among youth who vape nicotine and are motivated to quit nicotine., Methods: Connecticut youth (N=223, M age  = 17.3 [SD=1.7] years) who completed an intake for a vaping cessation study reported on their nicotine vaping, cannabis products used, reasons for use, frequency of use, and readiness to quit cannabis. Descriptives characterized population. Regressions were used to examine association of cannabis use and nicotine vaping., Results: Most reported cannabis use (lifetime: 92.4 %; past-month: 68.6 %). Cannabis smoking and vaping were highly prevalent (smoking: lifetime - 90.8 %, current - 63.6 %; vaping: lifetime - 90.8 %, current - 63.1 %). Most reported preferring smoking cannabis (58.7 %) over other routes of administration. Common reasons for cannabis use, were psychoactive (e.g., getting high), physical (e.g., improving sleep), and social (e.g., partying). Cannabis use frequency and preferring smoking cannabis (vs. other modes) was positively associated with more frequent nicotine vaping (ps < 0.05). Participants averaged 6.3 (of 10) on a readiness to quit cannabis scale, a moderate desire to quit., Conclusions: Cannabis use across multiple routes of administration was common among youth seeking help quitting vaping nicotine. Heaviness of cannabis and nicotine use appear to be associated, raising interesting harm-reduction challenges for those seeking to quit nicotine vaping. Understanding cannabis and nicotine co-use is important for targeting treatment for use of both substances., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Tobacco-free nicotine (TFN) is often marketed as being better tasting and healthier than tobacco-derived nicotine (TDN). Studies have yet to systematically characterize subjective experiences using TFN e-cigarettes. This qualitative study explored young adults' reasons for using TFN e-cigarettes and perceptions of differences between using TFN and TDN e-cigarettes., Method: We conducted a national online Qualtrics survey of U.S. young adults aged 18-25 years in October 2021. Respondents who reported lifetime TFN e-cigarette use (n = 317, mean age: 20.8 (SD:2.2), 53.9 % female) provided write-in responses to open-ended questions assessing reasons for using TFN e-cigarettes and perceptions of differences between TFN and TDN e-cigarettes. Responses from participants were thematically analyzed by independent raters., Results: Reasons for using TFN e-cigarettes included product taste/flavor, health reasons (e.g. believing TFN was healthy), and product accessibility. Perceptions of differences between TFN and TDN e-cigarettes included differences in taste/ flavor and acute psychoactive and physical effects (e.g., nicotine buzz, throat hit), with TFN e-cigarettes being described as generally stronger and superior relative to TDN e-cigarettes., Conclusion: These qualitative data suggest that taste and perceived health benefits are primary reasons that young adults try TFN e-cigarettes. Compared to TDN, young adults perceive TFN as better tasting with different psychoactive and less aversive effects. Determining if these perceived reasons for use and differences occur in blinded human experimental studies is a necessary next step to understanding TFN e-cigarette use. Additionally, understanding why young adults use TFN e-cigarettes is important in the development of prevention communication about these products., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: The Sensory E-cigarette Expectancies Scale (SEES) has demonstrated solid psychometric properties for use with adults. It assesses expectancies for enjoying the taste and smell of vaping, experiencing pleasurable physical sensations, and enjoying creating vapor clouds. We evaluated psychometric properties of the SEES for use with adolescents., Methods: In Fall 2022, 4,855 students from eight Connecticut high schools completed an anonymous, cross-sectional, online survey. Our analytic sample (n = 724) endorsed lifetime e-cigarette use and completed the SEES. Psychometric analyses included factor analyses, internal reliability, measurement invariance, between-groups differences, and relationships with vaping outcomes., Results: The three-factor SEES structure was confirmed. Internal reliability of each subscale was excellent (range: 0.88-0.95). The SEES was invariant by sex (male/female), race (Black/White/Other), Hispanic ethnicity (no/yes), nicotine e-cigarette use (no/yes), any past-month vaping (no/yes), daily vaping (no/yes), and vaping status (a variable created based on the distribution of past-month vaping frequency [0; 1-4; 5-20; 21+ days]). Those who reported using nicotine e-cigarettes, past-month vaping, daily vaping, and vaping on 21+ days in the past month reported stronger scores on each subscale compared to their respective counterparts. In adjusted models, expecting Pleasurable Physical Sensations was associated with total flavors used, past-month vaping frequency, and e-cigarette dependence. Enjoyment of Taste and Smell was positively associated with total flavors used and e-cigarette dependence. Enjoyment of Vapor Clouds was positively associated with total flavors used and past-month vaping frequency., Conclusions: Given its strong psychometric properties, the SEES can be used in future research to assess sensory-related vaping expectancies in youth., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Empirical evidence about the effectiveness of using e-cigarettes to quit smoking cigarettes remains inconclusive, yet e-cigarettes are commonly used for smoking cessation. Moreover, people who have longer duration quit attempts are likely to have even longer quit attempts in the future. Researchers analyzed 40 qualitative interviews to assess adults' experiences using e-cigarettes during their longest duration quit attempt. Interviewees quit smoking for ≥ one month (n = 20) or for shorter durations (n = 20). Thematic and comparative content analyses were used to analyze interview transcripts for factors facilitating or impeding the duration of quit attempts when using e-cigarettes. Participant narratives were mostly similar irrespective of their quit attempt duration. Six themes common across groups as well as themes more often discussed by people with shorter quit attempts are described. Most participants discussed using e-cigarette devices and flavors to either replace sensations similar to smoking combustible cigarettes (e.g., inhaling from a cylindrical object) or to distract themselves from cravings to smoke. E-cigarettes also were described by the majority of participants as useful for smoking cessation because they approximate combustible cigarette use, potentially reduce health-related harms, save money, and lead to reduced social stigma compared to smoking cigarettes. Those who reported shorter duration quit attempts shared e-cigarette product challenges, health concerns, needs for support. Study findings demonstrate the need for additional research on the factors that may increase the likelihood that using e-cigarettes will result in longer and sustained e-cigarette-based quit attempts among adults., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Introduction: Given high youth e-cigarette use, it is important to investigate how traits, like impulsivity, may be associated with youth e-cigarette use behaviors. The study aim is to determine if impulsivity is associated with trying more e-cigarette flavors and device types, and greater frequency of e-cigarette use., Method: Cross sectional survey data from CT high schoolers (n = 4875, 6 schools) were collected in 2019. Lifetime (ever) e-cigarette users (n = 2313) completed the Brief Barrett Impulsivity Scale, which contains two subscales; behavioral impulsivity and impaired self-control. Among lifetime users, associations between impulsivity subscales and number of e-cigarette flavors tried, e-cigarette devices tried, and past 30-day frequency of e-cigarette use were examined using regression models. Additionally, associations of impulsivity and use frequency were examined among only current e-cigarette users (≥1 day of use in past 30; n = 1327). School, age, race/ethnicity, vaping initiation age, other tobacco product use, and sex were included as covariates in models., Results: Higher behavioral impulsivity was associated with greater number of e-cigarette flavors tried (AOR: 1.06, 95% CI: 1.02, 1.11, p <.008) and higher frequency of past 30-day use both among ever and current e-cigarette users (AOR: 1.26, 95%CI:1.10,1.44, p <.001; AOR: 1.12, 95%CI:1.02,1.22, p <.02), but not number of e-cigarette devices tried. Impaired self-control was not associated with any outcomes., Conclusion: Youth with higher behavioral impulsivity may be more at risk for using more e-cigarette flavors and using e-cigarettes more frequently. Regulations aimed at reducing flavor availability among youth and interventions targeting impulsive behavior may be important for this population., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Introduction: Nicotine in e-cigarettes typically is labeled as mg/ml or percent nicotine, but these metrics may be difficult to understand. We examined whether adults who use e-cigarettes accurately can compare nicotine concentrations presented as mg/ml and percent and/or can identify the strength of concentrations presented using these metrics., Methods: 310 adults completed an online survey in 2020. Participants viewed nicotine concentration pairs (e.g., 24 mg/ml vs 3%) and indicated which concentration was stronger or if they were equal. Participants also categorized nicotine concentrations presented as mg/ml (0-60 mg/ml) and percent (0-6%) into strength categories (no nicotine, very low, low, medium, high, very high). "Correct" answers for the strength of each concentration (e.g., 30 mg/ml is "high" nicotine) were based on the subjective opinion of e-cigarette researchers., Results: When making direct comparisons, adults correctly identified that one concentration was stronger or that both were equivalent about half of the time (8.30 [5.08] of 19). Adults answered correctly more often when the stronger concentration was presented in mg/ml (4.75 [2.74] of 8) than percent (2.54 [2.60] of 8), p < .001). Adults "correctly" identified the strengths of 8.90 (3.22) of 18 nicotine concentrations, with more "correct" responses for mg/ml (5.27 [2.15]) than percent (3.63 [1.71], p < .001). Adults classified concentrations presented as percent as weaker than equivalent concentrations presented as mg/ml., Conclusions: Adults had difficulty understanding nicotine concentrations labeled using the most common metrics, especially percent nicotine. A singular, easy-to-understand labeling system may increase public knowledge about the nicotine concentration/strength of vaping products., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

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., (Copyright © 2020. Published by Elsevier Ltd.)

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background: Although weight-related reasons for smoking and vaping have been examined in adults, research in adolescents is lacking. Thus, we examined the prevalence and correlates of using flavored e-liquids for appetite control or weight loss in high school adolescents., Methods: The analytic sample included 529 students who completed a school-based survey in Connecticut in Spring 2017 (50.6% female, 79.5% White, mean age 16.27 [SD = 1.18], range 13-19 years). Inclusion criteria were past-30-day vaping, using ≥ 1 flavored e-liquid (past month), and having non-missing data on flavored e-liquid use for appetite control and weight loss. Participants reported on sex, age, race, past-30-day vaping and smoking frequency, nicotine e-liquid use, flavored e-liquid use (e.g., tobacco, mint, fruit, candy), and flavored e-liquid use for appetite control and/or weight loss., Results: Adolescent e-cigarette users (past 30-days) reported vaping flavored e-liquids for appetite control (13.8%) and weight loss (9.3%). Using flavored e-liquids for appetite control or weight loss, respectively, was associated with more frequent vaping (OR = 1.21; 1.21) and using more flavored e-liquids (OR = 1.33; 1.28, p-values < 0.01). Vaping candy-flavored e-liquids (OR = 1.16, p = 0.02) uniquely was associated with vaping for appetite control., Conclusions: A subset of adolescents reported using flavored e-liquids for weight-related reasons. These adolescents reported vaping more frequently than their counterparts, raising concerns about increased nicotine exposure. Research is needed to understand where adolescents learn about weight-motivated vaping (e.g., friends, social media) and whether weight-related motives promote e-cigarette initiation among e-cigarette naïve individuals or continued/escalating use among current users., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Background: Rates of legal medical cannabis (MC) use are increasing, but little is known about the prevalence and correlates of recreational cannabis (RC) use among medical users (MC/R)., Methods: 348 MC users who resided in a state in which MC is legal and had medical authorization to use MC legally completed an anonymous survey in Spring 2017 (64.1% female, 82.8% White, mean age 33.03[±10.37] years). Rates of endorsing MC/R and the following potential correlates of MC/R were examined: the legal status of RC in participants' states of residence, sex, age, race, primary medical condition, MC product(s) used, MC expectancies, features of MC sought out (e.g., high tetrahydrocannabinol [THC] content), and negative cannabis use consequences., Results: 55.5% of MC users engaged in MC/R. MC/R was associated with residing in a state in which RC is legal, being female, using MC for pain or mental health conditions, vaping MC concentrates, holding positive expectancies for combustible MC, and seeking out MC products with high THC concentrations. Preferring MC products with high cannabidiol (CBD) concentrations protected against MC/R., Conclusions: More than half of MC users endorsed MC/R, which is considerably higher than rates of misuse observed for other prescription medications. Findings raise concerns about circumvention of RC laws in states where RC remains illegal and could be used to inform MC regulatory efforts (e.g., reducing THC content, increasing CBD content). Findings also suggest that prevention/intervention efforts to reduce MC/R are needed, especially among high-risk populations of MC users (e.g., women, pain patients, psychiatric patients)., (Copyright © 2019 Elsevier Ltd. 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., (Copyright © 2018. Published by Elsevier Ltd.)

Introduction: The 4-item Patient-Reported Outcomes Measurement Information System Nicotine Dependence Item Bank is a psychometrically sound measure for assessing cigarette (PROMIS) and e-cigarette dependence (PROMIS-E). We evaluated whether dual-users of cigarettes and e-cigarettes self-report experiencing different levels of dependence on each product. We subsequently examined whether cigarette and e-cigarette dependence are associated with the frequency of using each product in dual-users., Methods: Dual-users completed an online survey in Summer 2017 (n = 326; 49.7% male, 85.3% White, mean age 38.17 [13.08] years). Measurement invariance of the PROMIS and PROMIS-E was evaluated. Mean differences in cigarette and e-cigarette dependence then were examined. The correlation between cigarette and e-cigarette dependence also was examined. Finally, one-way MANOVA was used to evaluate how cigarette and e-cigarette dependence relate to past-month frequency of e-cigarette use and cigarette smoking., Results: The PROMIS and the PROMIS-E were scalar measurement invariant, and, on average, dual-users reported stronger dependence on cigarettes than on e-cigarettes. Cigarette and e-cigarette dependence were related, yet distinct constructs (r = 0.35), suggesting that dual-users can discriminate between dependence on each product. Stronger cigarette dependence predicted more frequent past-month smoking and less frequent past-month vaping. Stronger e-cigarette dependence predicted more frequent past-month vaping and less frequent smoking., Conclusions: Overall, dual-users reported stronger dependence on cigarettes than on e-cigarettes. However, dependence on each product was associated with increased use of each respective product and with less frequent use of the other product. Future research using the PROMIS can evaluate how potential FDA regulations could reduce nicotine dependence across products., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Introduction: Drinking at an early age (AO) and quickly progressing to drinking to intoxication (Delay=Age of Intoxication[AI]-AO) confer risk for alcohol use and alcohol-related problems. However, inconsistencies exist in the literature, which may reflect the use of different definitions of AO and AI. We evaluated whether 1) defining AO as age at first sip of alcohol (AO sip) versus age at which at least one standard drink was consumed (AO drink); and 2) defining AI as age at first "drunk" (AI drunk) versus age at first binge episode (≥5 standard drinks consumed; AI binge) resulted in different self-reported ages or differentially predicted drinking outcomes., Methods: 248 high school students (53.6% male; 16.50[1.19] years; 71.4% White) completed anonymous surveys assessing alcohol use., Results: Participants reported a younger AO (sip) than AO (drink) and a younger AI (drunk) than AI (binge), resulting in significantly different Delay values for the four AO-AI pairings. Univariate general linear models indicated that AO-Delay pairings accounted for more variance in maximum drinks and alcohol-related problems than did the individual AO and AI variables. Pairings comprising AO (drink) and Delay (drink-binge) and AO (sip) and Delay (sip-binge), respectively, uniquely accounted for variance in both maximum drinks and problems., Conclusions: Clearly defining AO and AI using objective definitions that reflect specific amounts of alcohol (e.g., first sip; first standard drink; first binge) appears to outperform subjective definitions of alcohol use (e.g., first drunk)., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

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 naïve 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., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

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., (Copyright © 2016. Published by Elsevier Ltd.)

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=.08g/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., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Background: Impulsive adolescents have difficulty quitting smoking. We examined if treatments that provide behavioral incentives for abstinence improve treatment outcomes among impulsive adolescent smokers, who have been shown to be highly sensitive to reward., Methods: We ran secondary data analyses on 64 teen smokers (mean age=16.36 [1.44]; cigarettes/day=13.97 [6.61]; 53.1% female; 90.6% Caucasian) who completed a four-week smoking cessation trial to determine whether impulsive adolescents differentially benefit from receiving cognitive behavioral therapy (CBT), contingency management (CM), or the combination of the two (CM/CBT). Indices of treatment efficacy included self-report percent days abstinent and end of treatment biochemically-confirmed 7-day point prevalence abstinence (EOT abstinence). We assessed self-reported impulsivity using the Brief Barratt Impulsiveness Scale. We used univariate Generalized Linear Modeling to examine main effects and interactions of impulsivity and treatment condition as predictors of self-reported abstinence, and exact logistic regression to examine EOT abstinence., Results: CM/CBT and CM were comparably effective in promoting abstinence, so analyses were conducted comparing the efficacy of CBT to treatments with a CM component (i.e., CM and CM/CBT). CBT and deficient self-regulation predicted lower self-reported abstinence rates within the total analytic sample. Treatments containing CM were more effective than CBT in predicting 1) self-reported abstinence among behaviorally impulsive adolescents (% days abstinent: CM 77%; CM/CBT 81%; CBT 30%) and 2) EOT point prevalence abstinence among behaviorally impulsive adolescents and adolescents with significant deficits in self-regulation., Conclusion: CM-based interventions may improve the low smoking cessation rates previously observed among impulsive adolescent smokers., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

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.

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.