E-cigarette Dependence Research Articles

Co-occurrence of food addiction, obesity, problematic substance use, and parental history of problematic alcohol use.

The present study investigates the rates of co-occurrence among food addiction (FA), problematic substance use (alcohol, cannabis, cigarettes, nicotine vaping), parental history of problematic alcohol use, and obesity as an important step to understanding whether an addictive-like eating phenotype exists. A community sample of 357 U.S. adults (49.7% male, 77.6% White, Mage 40.7) completed the Yale Food Addiction Scale 2.0 (YFAS2.0), the Alcohol Use Disorders Identification Test, the Cannabis Use Disorders Identification Test, the Fagerstrom Test for Nicotine Dependence, the E-Cigarette Dependence Scale, the Family Tree Questionnaire, and demographic/self-report body mass index questions through Amazon Mechanical Turk. Risk ratios (RRs; unadjusted and adjusted for sociodemographic covariates) were calculated using modified Poisson's regression. Risk of FA was higher in participants with problematic alcohol use (RR = 2.13, 99% CI [1.32, 3.45]), smoking (RR = 1.86, 99% CI [0.82, 3.36]), cannabis use (unadjusted; RR = 2.22, 99% CI [1.17, 4.18]), vaping (RR = 2.71, 99% CI [1.75, 4.21]), and parental history of problematic alcohol use (RR = 2.35, 99% CI [1.46, 3.79]). Risk of FA in participants with obesity was only higher in adjusted models (RR = 1.87, 99% CI [1.06, 3.27]). Obesity was not significantly associated with problematic substance use and parental history of problematic alcohol use. FA, but not obesity, co-occurred with problematic substance use and a parental history of problematic alcohol use. Results support the conceptualization of FA as an addictive disorder. The inclusion of FA as an addictive disorder in diagnostic frameworks is an important area of future consideration. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

An 8-year longitudinal study of long-term, continuous users of electronic cigarettes

Background and AimsE-cigarettes have been available for over 15 years, but relatively little is known about long-term users. Our aim was to describe change over time in behaviours, attitudes and dependence in long-term users. Design and ParticipantsA longitudinal study of 375 e-cigarette users enrolled on the Internet in 2012–2016 and surveyed again in 2021 (8 years later on average), who continuously used e-cigarettes in the interval. FindingsFewer people in 2021 (11 %) than at baseline (33 %) had smoked tobacco in the past 31 days. Participants switched from second-generation models at baseline (e.g. Ego) to box mods in 2021 (e.g. iStick), they used larger refill bottles, they used home-made e-liquids twice as often, they used tobacco flavours less often and the nicotine concentration in e–liquids decreased from 12 to 6 mg/mL. There was no change over time in the time to the first e-cigarette puff of the day, but an e-cigarette dependence score of 0–100 decreased from 75 to 60, the frequency and strength of urges to vape decreased (from 31 % to 18 % of “strong” urges) and the proportion of people who said they would be likely to succeed if they tried to stop vaping increased. Compared to baseline, fewer people in 2021 reported vaping to cope with cravings or other smoking cessation symptoms, and fewer people reported vaping to quit smoking, to avoid relapse into smoking, or to reduce their tobacco consumption (p < 0.001 for all differences). ConclusionsIn long-term, continuous users, over a period of 8 years, substantial changes were observed in the models of e-cigarettes used, in the flavours and strength of e-liquids, and in the reasons for vaping. Their level of nicotine dependence tended to decrease over time. These users were satisfied with e-cigarettes and vaped mostly because they felt that vaping was less dangerous than smoking, and for enjoyment.

E-Cigarette Dependence and Depressive Symptoms Among Youth

Although the relationship between smoking and depression has been well-established, little is known about the association between use of e-cigarette and depression, particularly among youth and young adults. This study proposes that e-cigarette dependence, rather than simply use, serves as a potential stressor and may interact with pre-existing vulnerabilities to contribute to depression in youth, consistent with the diathesis-stress theory. This study examines the longitudinal association of vaping dependence and vaping frequency on depression symptoms among youth and young adults who have never smoked cigarettes. People who used e-cigarettes in the past month who reported never smoking a cigarette (N=1,226) aged between 16 and 25 years were followed longitudinally every 3 months for up to 1 year beginning in 2020. The Penn State E-Cigarette Dependence Index at time t was used to predict depression symptoms assessed using the Center for Epidemiologic Studies Depression Scale at time t+1. A total of 32.1% reported vaping in the past month with the Penn State E-Cigarette Dependence Index score (M=8.5) and a Center for Epidemiologic Studies Depression Scale score (M=15.8). Higher vaping dependence scores were significantly associated with increased depression symptoms scores at follow-up among youth and adults (β=0.08; 95% CI=0.01, 0.15), controlling for baseline depression symptom scores and covariates. Although vaping dependence was highly associated with vaping frequency level, no significant association between the frequency of vaping and depression was found (β= -0.33; 95% CI= 1.21, 0.54). These results are consistent with the diathesis-stress model of the relationship between substance use and depression. Vaping dependence but not vaping frequency was associated with increased depressive symptoms among people who never smoked cigarettes.

Psychometric evaluation of the sensory e-cigarette expectancies scale for use with adolescents

BackgroundThe 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. MethodsIn 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. ResultsThe 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. ConclusionsGiven its strong psychometric properties, the SEES can be used in future research to assess sensory-related vaping expectancies in youth.

Milestones in the natural course of the onset of e-cigarette dependence among adolescents and young adults: Retrospective study

IntroductionThere is considerable controversy about the development of dependence among e-cigarette users. This study describes the average amount of time using e-cigarettes before dependence milestones emerge and the differences in developing dependence between e-cigarette users who smoke cigarettes compared to those who do not. MethodsAdolescents and young adults aged 16–25 living in Canada were recruited into an online survey in 2021. Current (past-month) e-cigarette users completed 15 items assessing dependence from the Penn-State Electronic Cigarette Dependence Index and the E-cigarette Dependence Scale for a total of 12 behavioural (e.g., difficulty refraining from vaping) and 3 frequency (e.g., using e-cigarette daily, weekly, or monthly) indicators of dependence milestones. Number of years after e-cigarette onset at which the cumulative probability of attaining each milestone was 25 % was computed. ResultsAmong 1205 participants, most (80.6 %) were female, 73.7 % were Caucasian, and 49.7 % resided in Ontario. Ten of the 12 e-cigarette use milestones were attained by 25 % of respondents 2 years after starting vaping except for daily cigarette use (2.5 years after onset) and waking at night to vape (5.6 years after onset). Within the entire study population, frequency milestones (weekly, monthly, daily e-cigarette use) were attained faster by ever-smokers (hazard ratio compared to attainment by never-smokers: 1.12, 1.21, and 1.28 respectively), whereas for at least monthly users, behavioural milestones were attained faster by never-smokers. DiscussionMany current e-cigarette users developed symptoms of e-cigarette dependence between two and five years since onset. Never smokers may be at higher risk of becoming e-cigarette dependent since they attained e-cigarette dependence milestones faster than smokers.

Prevalence of use, perceptions of harm and addictiveness, and dependence of electronic cigarettes among adults in Kuwait: A cross-sectional study.

Electronic cigarettes (e-cigarettes) have become one of the most common forms of nicotine delivery used by youth and young adults worldwide. Given the lack of epidemiologic data in Kuwait, this study sought to estimate the prevalence of e-cigarette use, assess perceptions of harm and addictiveness of e-cigarettes, measure the level of dependence on e-cigarettes and assess factors associated with dependence level among adults. A cross-sectional study enrolled adults (n=3032, aged ≥18 years) living in Kuwait using a web-based questionnaire. Participants self-reported ever and current (past 30-day) e-cigarette use and self-completed the 10-item Penn State E-cigarette Dependence Index. Associations were evaluated using multinomial logistic regression. The prevalence of ever and current e-cigarette use was estimated to be 40.2% (1220/3032) and 29.4% (892/3032), respectively. The prevalence of current e-cigarette use was higher in males compared to females (47.6% vs 14.4%, p<0.001). Relative to cigarette smoking, 40.6% of participants reported that e-cigarettes are less harmful, and 41.8% indicated that e-cigarettes are equally addictive. Among current e-cigarette users (n=892), 84.8% were ascertained to have developed either low, medium, or high dependence. The use of pod-based devices compared to disposable devices was associated with a high dependence level (adjusted odds ratio, AOR=8.56; 95% CI: 4.52-16.22). These findings suggest that a large proportion of adults in Kuwait use e-cigarettes, and a considerable proportion of current users have developed dependence. Therefore, such results should alert public health authorities and warrant the development of evidence-based awareness campaigns, policies, and prevention measures to protect and improve the health of people.

Dependence motives and use contexts that predicted smoking cessation and vaping cessation: A two-year longitudinal study with 13 waves

IntroductionPrior studies examining the impact of e-cigarette use, dependence, cessation motivation/goals, and environmental restriction on smoking cessation were based on cross-sectional or shorter-term longitudinal data with binary outcomes. There is also a critical knowledge gap in corresponding impact on vaping cessation. This study aims to fill in these gaps by investigating these factors’ effects on speed of progression to smoking and vaping cessation. MethodsThis study conducted secondary analysis of data from 13 waves of assessment of adult cigarette users in Wisconsin from October 2015 through July 2019. Cox regression was employed to examine baseline predictors’ effects on speed of progression to smoking cessation (past-month abstinence) among 405 exclusive combustible cigarette users and dual users of combustible and electronic cigarettes, as well as progression to vaping cession among 178 dual users. ResultsDual use of e-cigarettes with cigarettes, lower primary dependence motives of smoking, higher secondary dependence motives of smoking, higher motivation to quit smoking, more ambitious future goals to quit smoking, and more restrictive environment for smoking all contributed to quicker progression to smoking cessation. Dual users with higher secondary dependence motives of smoking or with lower primary dependence motives of vaping progressed faster to vaping cessation. ConclusionsThe findings support that nicotine dependence is product-specific with two distinct constructs: the primary dependence motives are associated with more difficulty to quit, whereas the secondary dependence motives have the opposite effect. Dual users with strong instrumental reasons for smoking may not find e-cigarettes as an effective substitute for cigarettes.

Retrospective and Real-time Measures of the Quantity of E-cigarette Use: An Ecological Momentary Assessment Study.

Quantifying e-cigarette use is challenging because of the wide variety of products and the lack of a clear, objective demarcation of a use event. This study aimed to characterize the difference between retrospective and real-time measures of the quantity of e-cigarette use and identify the covariates that may account for discrepancies between the two types of measures. This study analyzed data from 401 college student e-cigarette users in Indiana and Texas who responded to a web survey (retrospective) and 7-day ecological momentary assessments (EMA) (real-time) on their e-cigarette use behavior, dependence symptomatology, e-cigarette product characteristics, and use contexts from Fall 2019 to Fall 2021. Generalized linear mixed models were used to model the real-time measures of quantity offset by the retrospective average quantity. Although the number of times using e-cigarettes per day seems to be applicable to both retrospective and real-time measures, the number reported via EMA was 8.5 times the retrospective report. E-cigarette users with higher e-cigarette primary dependence motives tended to report more daily nicotine consumption via EMA than their retrospective reports (ie, perceived average consumption). Other covariates that were associated with discrepancies between real-time and retrospective reports included gender, nicotine concentration, using a menthol- or fruit-flavored product, co-use with alcohol, and being with others when vaping. The study found extreme under-reporting of e-cigarette consumption on retrospective surveys. Important covariates identified to be associated with higher than average consumption may be considered as potential targets for future vaping interventions. This is the first study that characterizes the direction and magnitude of the difference between retrospective and real-time measures of the quantity of e-cigarette use among young adults-the population most likely to use e-cigarettes. An average retrospective account of vaping events per day may significantly underestimate e-cigarette use frequency among young adults. The lack of insight into the degree of consumption among users with heavy primary dependence motives illustrates the importance of incorporating self-monitoring into cessation interventions.

A Machine Learning Approach Reveals Distinct Predictors of Vaping Dependence for Adolescent Daily and Non-Daily Vapers in the COVID-19 Era.

Since 2016, there has been a substantial rise in e-cigarette (vaping) dependence among young people. In this prospective cohort study, we aimed to identify the different predictors of vaping dependence over 3 months among adolescents who were baseline daily and non-daily vapers. We recruited ever-vaping Canadian residents aged 16-25 years on social media platforms and asked them to complete a baseline survey in November 2020. A validated vaping dependence score (0-23) summing up their responses to nine questions was calculated at the 3-month follow-up survey. Separate lasso regression models were developed to identify predictors of higher 3-month vaping dependence score among baseline daily and non-daily vapers. Of the 1172 participants, 643 (54.9%) were daily vapers with a mean age of 19.6 ± 2.6 years and 76.4% (n = 895) of them being female. The two models achieved adequate predictive performance. Place of last vape purchase, number of days a pod lasts, and the frequency of nicotine-containing vaping were the most important predictors for dependence among daily vapers, while race, sexual orientation and reporting treatment for heart disease were the most important predictors in non-daily vapers. These findings have implications for vaping control policies that target adolescents at different stages of vape use.

Nicotine Intake in Adult Pod E-cigarette Users: Impact of User and Device Characteristics.

This study examined user behavior, e-cigarette dependence, and device characteristics on nicotine intake among users of pod-mod e-cigarettes. In 2019-2020, people who use pod-mods in the San Francisco Bay Area completed questionnaires and provided a urine sample for analysis of total nicotine equivalents (TNE). The relationship between TNE and e-cigarette use, e-cigarette brands, e-liquid nicotine strength, e-cigarette dependence, and urine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), as a measure of combustible cigarette exposure, were examined. Of 100 participants (64% male, 71% in the 18-34 age group, 45% white), 53 used JUUL primarily, 12 used Puff Bar primarily, and 35 used other brands, including Suorin; 48 participants reported current cigarette smoking. Participants most often reported use of e-liquid with 4.5%-6.0% nicotine (68%), fruit (35%), tobacco (28%), and menthol or mint flavors (26%), used e-cigarettes on 25.5 (SD = 6.3) days a month, 10.2 (SD = 14.2) times a day, and 40% used 1-2 pods/cartridges per week. In bivariate analysis, urinary TNE was higher with greater frequency (days used) and intensity (number of pods used) of e-cigarette use, e-cigarette dependence, and combustible cigarette use. In multivariable analysis, days of e-cigarette use in the last 30 days, number of pods used per week, and NNAL levels were significantly associated with TNE. There was no significant impact of e-liquid nicotine strength on TNE. Nicotine intake among people who used pod-mod e-cigarettes increased with e-cigarette consumption and e-cigarette dependence, but not with e-liquid nicotine strength. Our findings may inform whether FDA adopts a nicotine standard for e-cigarettes. The study examined how device and user characteristics influence nicotine intake among pod-mod e-cigarette users. Nicotine intake increased with frequency (days of e-cigarette use in past 30 days) intensity of use (number of pods used per day) and e-cigarette dependence but not with the flavor or nicotine concentration of the e-liquids. Regulation of nicotine concentration of e-liquids is unlikely to influence nicotine exposure among adult experienced pod-mod users.

Long-term impact of the COVID-19 pandemic on use behavior and risk perceptions of college student E-cigarette users

Objective: Work examining the long-term impact of the COVID-19 pandemic on e-cigarette use among college students is limited. Therefore, the current study examined differences in college student e-cigarette users’ changes in use behavior and risk perceptions as the pandemic continues. Participants: 129 undergraduate current e-cigarette users (Mage = 19.68, SD = 1.85; 72.1% female; 85.3% White). Methods: Participants completed an online survey between October 2020 and April 2021. Results: In terms of changes in frequency of e-cigarette use, 30.5% of participants increased their use and 23.4% decreased their use. Greater e-cigarette dependence and anxiety were associated with increased use. Nearly half of e-cigarette users reported increased motivation to quit, and 32.5% had made at least one quit attempt. Conclusions: A substantial number of students increased their e-cigarette use as a result of the COVID-19 pandemic. Cessation efforts targeting increased anxiety and dependence may be useful in this population.

E-cigarette Device Type, Source, and Use Behaviors of Youth and Young Adults: Findings from the Truth Longitudinal Cohort (2020–2021)

Background: E-cigarette device types vary in the amount of nicotine delivered to users. Given that youth and young adults are using pod-based and disposable e-cigarettes with high nicotine concentrations, it is important to determine how e-cigarette use behaviors associated with nicotine dependence may differ across e-cigarette device type. Methods: Baseline information was collected from September 2020 to March 2021 and follow-up information was collected from July to October 2021 from the Truth Longitudinal Cohort. The final analytic sample included respondents (aged 15–24) who reported current use of e-cigarettes at either baseline or follow-up and provided information on the 4-item E-cigarette Dependence Scale (EDS). Differences in endorsement of items from the EDS by e-cigarette device type (pod-based, disposable, or tank) were assessed using chi-square tests. Results: Participants (N = 308) were evenly split on age (15–20, 21+) and gender. Most 15–20-year-olds used disposable e-cigarettes, while those 21+ years primarily used tank devices. Although EDS score did not differ by e-cigarette device type, positive endorsement of two items from the EDS significantly differed by e-cigarette device type. More tank users endorsed reaching for a device without thinking about it (tank: 92.6%; pod-based: 79.0%; disposables: 79.9%, p = 0.04) and vaping more before going into a situation where vaping is not allowed (tank: 92.9%; pod-based: 71.0%; disposables: 73.0%, p < 0.01). Conclusions: Findings have the potential to inform policy implementation by providing evidence for specific targets for regulatory action that can help to reduce the burdens of e-cigarette use among youth and young adults, as results suggest that tank device users are more likely to endorse use behaviors associated with nicotine dependence.

Predictors of Discontinued E-Cigarette Use at One-Year Follow-Up in a Sample of Young Adults.

Currently, the research on factors associated with young adults' discontinuation of e-cigarette use behavior is limited. This study tested the predictors of self-reported e-cigarette abstinence at one-year follow-up among young adult baseline current e-cigarette users. The following variables were tested as predictors: demographics, cigarette smoking, e-cigarette use dependence, e-cigarette use duration, harm perceptions, and preferred aspects of e-cigarette use, including sensations, flavor, and device characteristics. Data were provided at two time-points one year apart by 435 ethnically diverse young adults (M age = 22.3, SD = 3.1; 63% women) who reported current e-cigarette use at baseline. Approximately 42% of those who reported current e-cigarette use at baseline (i.e., 184 out of 435 participants) reported discontinuation of e-cigarette use at one-year follow-up. Results indicated that higher e-cigarette dependence, longer history of e-cigarette use, lower e-cigarette harm perceptions, greater preference for both menthol and sweet flavors, for open-pod-based devices, and for e-cigarette use sensations such as buzz, taste and smell of flavors, and throat hit at baseline were associated with lower likelihood of e-cigarette use discontinuation at one-year follow-up. Characteristics associated with nicotine (e.g., dependence) and flavors (e.g., taste and smell) appear to drive the continuation/discontinuation of e-cigarette use among young adults. Thus, cessation strategies may need to be developed with a focus on dependence and harm perceptions related to nicotine and flavors. Furthermore, better regulating open-pod-based devices and sweet-menthol flavors may help e-cigarette use prevention.

Prevalence of substance use disorders and associations with mindfulness, impulsive personality traits and psychopathological symptoms in a representative sample of adolescents in Germany.

Adolescence is a critical phase for the development of substance use disorders (SUDs). For Europe and Germany, there are limited data on problematic substance use from representative youth samples. Trait mindfulness is relevant in buffering against substance use-related problems and associated deficits in self-regulatory control. The objective of this study is to estimate 12-month prevalence rates for SUDs in a representative sample of adolescents in Germany and to examine associations with mindfulness and related factors such as stress, impulsivity, sensation seeking and symptoms of psychopathology. A sample of 4001 adolescents aged 12-18years from Germany was surveyed based on DSM-IV diagnostic criteria for SUDs. Logistic regression analyses were used to examine associations with mindfulness-related variables. Criteria of at least one of the assessed SUDs were endorsed by 11.2% of the adolescents. Alcohol use disorders had the highest prevalence rate (10.1%) followed by cannabis use disorders (2.6%). For both substances, the criteria for abuse were met about twice as often as those for dependence. The prevalence of cigarette dependence was 1.7%, while the prevalence for e-cigarette dependence was only 0.1%. Prevalence rates were higher for male youth and increasing with age. SUD prevalence was also related to mindfulness, impulsivity and sensation seeking and externalizing symptoms of psychopathology. The statistically significant associations varied across different SUDs. SUDs appear highly prevalent among German adolescents. The results have public health implications with regard to treatment needs and prevention measures in the youth population in Germany.

An ecological momentary assessment study to examine covariates and effects of concurrent and simultaneous use of electronic cigarettes and marijuana among college students

IntroductionThe prevalence of concurrent and simultaneous use of e-cigarette and marijuana among college students is high. Yet, the literature was mainly based on cross-sectional surveys with emphasis on the smoking route. This is the first ecological momentary assessment (EMA) study that examined the vaping route of nicotine-marijuana co-use and the associated short-term psychological effects. MethodsThis study recruited 686 college student e-cigarette users to participate in an on-line survey and 7-day EMA. Frequent marijuana users (247) – using marijuana weekly or daily – were compared with infrequent/non-users (439) on academic performance, e-cigarette use patterns, and dependence and respiratory symptoms. EMA data from the frequent users were used to study the association between marijuana vaping and e-cigarette consumption and the short-term psychological effects of e-cigarette and marijuana use. ResultsThe results show that e-cigarette users who frequently used marijuana tended to have lower academic performance, be involved in higher-risk use patterns, and have higher levels of e-cigarette dependence, marijuana problems, and respiratory symptoms, compared to infrequent/non-users. Marijuana vaping was associated with a higher level of e-cigarette consumption. E-cigarette use and marijuana use were both associated with higher levels of positive affect, physiological sensation, and craving for e-cigarettes. While marijuana use was linked to a lower level of negative affect, e-cigarette use did not have a significant effect. Further, none of the interaction effects between e-cigarette and marijuana use on psychological states were significant. ConclusionsThe results showed additive effects of e-cigarette and marijuana use although the hypothesized synergistic effects were not supported.

Nicotine Dependence among Current Cigarette Smokers Who Use E-Cigarettes and Cannabis

Background Co-use of tobacco and cannabis and dual use of cigarettes and e-cigarettes are very common among young adults. However, it is unclear whether co-use of cigarettes, e-cigarettes, and/or cannabis is associated with higher levels of nicotine dependence than cigarette-only use. We investigated the relationship between cigarette/nicotine dependence and co-use of tobacco and cannabis among 4 groups of cigarette smokers aged 18–35: cigarette-only smokers, cigarette-e-cigarette (CIG-ECIG) co-users, cigarette-cannabis (CIG-CAN) co-users, and cigarette-e-cigarette-cannabis (CIG-ECIG-CAN) co-users. Methods Data were from a 2018 cross-sectional survey based on a national convenience sample of smokers aged 18–35 (n = 315). Cigarette/nicotine dependence was measured by the Fagerstrom Test of Nicotine Dependence (FTND) and e-cigarette dependence was measured by the Penn State E-cigarette Dependence Index. Bivariate analyses examined sociodemographic and tobacco/other substance use characteristics by co-use status and multivariable linear regression assessed the relationship between co-use and nicotine dependence. Results In the sample, 27.6% were cigarette-only smokers, 24.8% were CIG-ECIG, 27.6% were CIG-CAN, and 20.0% were CIG-ECIG-CAN co-users. Significant differences were observed in sociodemographic and tobacco/other substance use characteristics by co-use status. E-cigarette co-users had low e-cigarette dependence, but moderate FTND scores. In adjusted analyses, only CIG-ECIG co-use was associated with higher FTND scores compared to cigarette-only smoking. However, CIG-ECIG and CIG-ECIG-CAN co-use were associated with higher FTND scores compared to CIG-CAN co-use. Conclusions Co-use of cigarettes and e-cigarettes was associated with greater nicotine dependence among smokers aged 18–35. Additional research is needed to understand the underlying mechanisms of these relationships and inform prevention efforts.

The Roswell eND scale: Brief, valid assessment of nicotine dependence adults seeking to discontinue e-cigarette use

BackgroundMost adults who regularly use e-cigarettes or Electronic Nicotine Delivery Systems (ENDS) desire to discontinue use. ENDS use can result symptoms of nicotine withdrawal and dependence which can make it more difficult to discontinue use. Brief, valid assessment of nicotine dependence among adults who use ENDS is needed to guide treatment for nicotine dependence in this group. We sought to develop a brief, valid instrument to measure nicotine dependence among adults seeking to discontinue ENDS in a busy Quitline. MethodsIn this cross-sectional design, we examined content, construct, and concurrent validity of the Roswell ENDS Nicotine Dependence Scale (Roswell eND Scale) and the Penn State E-Cigarette Dependence Index (Penn State eCDI). Participants who called the New York Quitline from November 2019 to June 2020 seeking to discontinue ENDS use were invited to participate. Construct validity was examined with exploratory and confirmatory factor analyses. Instrument and factor scores were then correlated with cotinine, a biomarker of nicotine exposure. ResultsAll participants (n = 209) were highly dependent and co-used combustible cigarettes to varying degrees. Both instruments demonstrated content validity and construct validity, however only the 5-item Roswell eND Scale demonstrated criterion-related validity by showing a significant positive correlation with salivary cotinine levels. ConclusionsThe 5-item Roswell eND Scale can briefly and effectively assess nicotine dependence among treatment-seeking adults who co-use ENDS and cigarettes. These preliminary psychometric findings have the potential to be generalizable to other adults seeking to discontinue ENDS use, many of whom currently or formerly smoked cigarettes.

Teens Less Susceptible to Vaping When Restricted to Tobacco-Flavored E-cigarettes: Implications for Flavored Tobacco Policies.

Flavors added to tobacco products increase their appeal to youth and contribute to the youth vaping epidemic. To address this problem, over 340 localities have implemented various policies to restrict access to flavored tobacco products. Few studies have examined the extent to which restricting available e-cigarette flavors might affect e-cigarette initiation or cessation among youth. A representative sample of Minnesota teens were asked about their use of e-cigarettes, symptoms of e-cigarette dependence and their willingness to use an e-cigarette under four flavor conditions: unspecified (any flavor); menthol, tobacco, or unflavored. Respondents with data on all four flavor conditions were included in the analysis (N = 2151). Cochran's Q, McNemar, and exact binomial tests revealed that susceptibility to e-cigarette use was highest when the flavor was unspecified (38.2%), lower for unflavored (29.7%) and menthol-flavored e-cigarettes (26.7%), and lowest when the flavor was tobacco (21.0%). Among the subsets of students who had never tried e-cigarettes and students who reported signs of e-cigarette dependence, the largest decrease in susceptibility from unspecified flavor e-cigarettes was observed for tobacco-flavor, a decrease of 12.7 and 19.6 percentage points, respectively. Whether teens had no experience using e-cigarettes or showed signs of dependence, the percentage of teens who were susceptible to using e-cigarettes was significantly lower when the flavor available was restricted. Susceptibility was lower for tobacco- and menthol-flavored than unflavored e-cigarettes, suggesting that teens consider these flavors aversive. These results suggest that policies that eliminate all e-cigarette flavors except tobacco may be a powerful tool for advancing youth e-cigarette prevention and cessation goals by reducing the appeal of e-cigarettes to teens with different levels of experience with them, including teens who have never tried e-cigarettes and those who may find it difficult to quit using them.

Evaluation of the Psychometric Properties of Dependence Measures for Exclusive Electronic Cigarette Users.

Extant electronic cigarette (ECIG) dependence measures are largely adapted from those designed for cigarette smoking, though few have been evaluated for their psychometric properties. Never-smoking ECIG users (N = 134) participating in an online survey completed four dependence measures: Penn state electronic cigarette dependence index (PSECDI), e-cigarette dependence scale (EDS-4), diagnostic and statistical manual for tobacco use disorder (DSM-5), and Glover Nilsson behavioral questionnaire (GNBQ). They also reported on their ECIG use characteristics (eg, behaviors and reasons). Internal consistency was highest for the EDS-4 (Cronbach's α = 0.88) followed by the GNBQ (α = 0.75), PSECDI (α = 0.72), and DSM (α = 0.71). Confirmatory factor analyses revealed a single-factor structure for the PSECDI, EDS-4, and GNBQ. For the DSM-5, however, two items did not load significantly (ECIG use interferes with responsibilities; reduce/give up activities because of ECIG use). Significant correlations were observed between all measures and the number of ECIG use days/week and/or years using ECIGs, as well as between DSM-5 scores and the number of ECIG quit attempts and initiation age. Endorsement of using ECIGs because "I like flavors" was correlated positively with DSM-5 and GNBQ scores. All dependence measures evaluated herein demonstrated adequate reliability and construct validity. Future work should focus on determining which aspects of dependence are those that are unique to ECIG use, and subsequently developing a more comprehensive measure of ECIG dependence. The measures assessed herein-PSECDI, EDS-4, DSM-5, and GNBQ-demonstrated adequate to good reliability and construct validity among a sample of never-smoking ECIG users. The dependence domains covered across measures were related yet distinct. Findings demonstrate the need for future evaluation of these different domains to determine which are the most salient characteristics of ECIG dependence.

Predictors of electronic cigarette dependence among non-smoking electronic cigarette users: User behavior and device characteristics

IntroductionECIGs differ in their ability to deliver nicotine to the user and, consequently, they may differ in their ability to produce dependence. This study examined individual device characteristics, device type, and user behaviors as predictors of ECIG dependence in a sample of never-smoking ECIG users. MethodsParticipants (N = 134) completed an online survey that assessed demographics, ECIG use behavior, and ECIG dependence as measured via the Penn State Electronic Nicotine Dependence Index (PSECDI) and E-cigarette Dependence Scale (EDS-4). Participants uploaded a picture of their personal ECIG device/liquid, which was coded by raters to identify product features. Multivariable linear regressions examined device characteristics (e.g., adjustable power, nicotine concentration) and device type (e.g., vape pen, mod, pod, modern disposable) as predictors of dependence controlling for demographics and user behaviors (e.g., ECIG use duration and frequency, other tobacco use). ResultsLonger durations of ECIG use and more use days/week were associated significantly with higher PSECDI (β’s = 0.91 and 1.90, respectively; p’s < 0.01) and EDS-4 scores (β’s = 0.16 and 0.28, respectively; p’s < 0.01). Higher nicotine concentrations were associated with higher PSECDI scores only (β = 0.07, p =.011). Dependence scores did not differ as a function of ECIG device types after controlling for covariates. ConclusionsECIG dependence was observed among the never-smoking ECIG users in this sample, regardless of their ECIG device/liquid features. Findings suggest that regulatory efforts aimed at reducing the dependence potential of ECIGs in never smokers should focus on overall nicotine emissions rather than product features.