"I cannot live without my vape": Electronic cigarette user-identified indicators of vaping dependence

Identifying facilitators and barriers to the uptake of medication for opioid use disorder in Washington, DC: A community-engaged concept mapping approach

INTRODUCTION

Opioid overdose is a major public health challenge. We aimed to understand facilitators and barriers to engagement in medication for opioid use disorder (MOUD) among persons with OUD in Washington, DC.

METHODS

We used a cross-sectional mixed-methods concept mapping approach to explore MOUD engagement between 2021-2022. Community members at-large generated 70 unique statements in response to the focus prompt: "What makes medication for opioid use disorder like buprenorphine (also known as Suboxone or Subutex) difficult to start or keep using?" Persons with OUD (n = 23) and service providers (n = 34) sorted and rated these statements by theme and importance. Data were analyzed with multidimensional scaling and hierarchical cluster analysis, producing thematic cluster maps. Results were validated by our community advisory board.

RESULTS

Seven themes emerged in response to the focus prompt: availability and accessibility; hopelessness and fear; unmet basic needs; characteristics of treatment programs; understanding and awareness of treatment; personal motivations, attitudes, and beliefs; and easier to use drugs. "Availability and accessibility," "hopelessness and fear," and "basic needs not being met" were the top three identified barriers to MOUD among consumers and providers; however, the order of these priorities differed between consumers and providers. There was a notable lack of communication and programming to address misconceptions about MOUD's efficacy, side effects, and cost. Stigma underscored many of the statements, showcasing its continued presence in clinical and social spaces.

CONCLUSIONS

This study distinguishes itself from other research on MOUD delivery and barriers by centering on community members and their lived experiences. Findings emphasize the need to expand access to treatment, dismantle stigma associated with substance use and MOUD, and address underlying circumstances that contribute to the profound sense of hopelessness and fear among persons with OUD-all of which will require collective action from consumers, providers, and the public.

Targeting GLP-1 receptors to reduce nicotine use disorder: Preclinical and clinical evidence

Nicotine use disorder (NUD) remains a leading cause of preventable death in the U.S. Unfortunately, current FDA-approved pharmacotherapies for smoking cessation have limited efficacy and are associated with high rates of relapse. One major barrier to long-term smoking abstinence is body weight gain during withdrawal. Nicotine withdrawal-induced body weight gain can also lead to development of chronic disease states like obesity and type II diabetes mellitus. Therefore, it is critical to identify novel pharmacotherapies for NUD that decrease relapse and nicotine withdrawal symptoms including body weight gain. Recent studies demonstrate that glucagon-like peptide-1 receptor (GLP-1R) agonists attenuate voluntary nicotine taking and seeking and prevent withdrawal-induced hyperphagia and body weight gain. Emerging evidence also suggests that GLP-1R agonists improve cognitive deficits, as well as depressive- and anxiety-like behaviors, which contribute to smoking relapse during withdrawal. While further studies are necessary to fully characterize the effects of GLP-1R agonists on NUD and understand the mechanisms by which GLP-1R agonists decrease nicotine withdrawal-mediated behaviors, the current literature supports GLP-1R-based approaches to treating NUD.

Interest in quitting e-cigarette use by device type and smoking history in US adults

BACKGROUND

The use of e-cigarettes has been increasing, especially since the introduction of 'pod' devices to the marketplace since 2018. Most adults who vape report interest in quitting. The present study examined level of interest in e-cigarette cessation between users with varying cigarette smoking histories and device types.

METHODS

Data obtained from wave 5 (2018-2019) of the Population Assessment of Tobacco and Health study (n=34 309). Analyses were conducted on adult current established e-cigarette users, categorised on cigarette smoking history (current, former or never) and device type (disposable, cartridge/pod, tank or mod). Participants reported if they planned to ever quit e-cigarettes, attempted to quit in the past year and attempted to quit by cutting back in the past year.

RESULTS

Of the 2922 established e-cigarette users, 68.21% reported plans to quit vaping; 17.27% reported attempting to quit e-cigarettes in the past year; and 29.28% reported attempting to quit by cutting back in the past year. Cartridge users had higher odds of interest in quitting than tank and mod users. Disposable and cartridge users had higher odds of reporting a past year quit attempt than tank and mod users. Individuals with no smoking history had higher odds of reporting a past year quit attempt or cutting back relative to those reporting dual use (of both e-cigarettes and cigarettes) and former smoking.

CONCLUSIONS

Tobacco control should consider the type of e-cigarette device that is being used, alongside users' cigarette smoking history, when developing interventions and other resources for vaping cessation.

Uncontrolled vaping and restraint strategies: A qualitative study

INTRODUCTION

Little is known about uncontrolled vaping, defined as vaping more than the user prefers. We sought to understand e-cigarette users' experiences with uncontrolled vaping and how they restrain their vaping.

METHODS

Participants were 24 US adult e-cigarette users recruited in 2021. We conducted semi-structured qualitative interviews about uncontrolled vaping and restraint strategies and analyzed findings based on behavioral categories described in the Process Model of Self-Control.

RESULTS

While most participants (21 of 24) described experiences of uncontrolled vaping, some expressed ambivalence about how much they vaped. To restrain vaping, willpower was rarely used and was not perceived as effective. Distraction, deployment of attention away from the urge to vape, and reappraisal, thinking differently about vaping such as reminding oneself of health consequences, were common and helped some participants limit use in the moment of wanting to vape. Participants described using both situation selection, choosing to be in situations where e-cigarette use was less possible, and situation modification, modifying their circumstances to restrict opportunities to vape.

DISCUSSION

Uncontrolled vaping is not yet a well-defined concept for many e-cigarette users. E-cigarette users employed proactive situational strategies that required planning ahead to restrain use and found these strategies more effective compared to reactive strategies. Tobacco control programs and interventions should consider leveraging restraint strategies that people who vape are naturally using and perceive to be effective.

Psychometric properties of measures for electronic cigarette dependence among former-smoking electronic cigarette users

BACKGROUND

Measures designed to assess electronic cigarette (ECIG) dependence are largely adapted from those developed for cigarette smoking, and have been evaluated mainly among dual ECIG-cigarette users. The present study evaluated the psychometric properties of four dependence measures among former-smoking ECIG users.

METHODS

Respondents (N = 187) were daily ECIG users who had formerly smoked cigarettes regularly. As part of an online survey, they completed four dependence measures: Penn State Electronic Cigarette Dependence Index (PSECDI); E-Cigarette Dependence Scale (EDS-4); Glover Nilsson Behavioral Questionnaire (GNBQ); and Diagnostic and Statistical Manual 5th Edition (DSM-5).

RESULTS

Confirmatory factor analysis revealed a single factor structure for all four measures, and fit indices were adequate for all models. Most inter-item correlations (mean r's = 0.21 to 0.45) and all item-total correlations (mean r's = 0.53 to 0.80) were significant for all four measures. Internal consistency was highest for the GNBQ (α = 0.86) followed by the EDS-4 (α = 0.81), PSECDI (α = 0.76), and DSM-5 (α = 0.75). Age of ECIG initiation was correlated negatively with scores on the EDS-4 and DSM-5, while number of ECIG quit attempts was correlated positively with scores on all measures except the GNBQ. Convergent validity was highest for comparisons between the EDS-4 and PSECDI (r = 0.75) though all comparisons were significant (p's < 0.001).

CONCLUSIONS

All four measures demonstrated acceptable reliability and validity in this sample of former-smoking ECIG users.

Reactions to a Hypothetical Ban of Open-System Electronic Cigarettes Among People Who Currently Use Electronic Cigarettes

INTRODUCTION

Policies limiting electronic cigarette (ECIG) device and liquid characteristics have been considered to prevent dependence potential and youth product appeal. "Open-system" ECIGs allow people to adjust device and liquid characteristics, which may undermine these policies. This study examined anticipated reactions to a policy prohibiting the sale of open-system ECIG devices in the United States using concept mapping.

METHODS

In 2020, adults who reported ECIG use in the past 30 days (n = 70; 45.1% women; mean age = 33.0, SD = 10.6) recruited from a research registry of individuals from across the United States provided statements into a shared list that completed a prompt: "If open-system vaping devices were no longer sold in the US and only closed-system vaping devices were available, what is a specific reaction or response you would have?" at a study website. Participants rated statements (1-7) on how true the statements were for them. Multidimensional scaling and hierarchical cluster analyses were used to identify thematic clusters. Mean ratings of statements were calculated and compared based on the type of ECIG used and current cigarette smoking status.

RESULTS

Participants generated 85 unique statements. The analysis identified eight themes that were organized into two broad groups. The first group of five clusters described behavioral responses to the hypothetical policy (Loopholes, Switch to Closed-System ECIGs, Legal Approaches to Use Open-System ECIGs, ECIG Use Cessation, Switch to non-ECIG Products). The second group of three clusters described psychological responses to the hypothetical policy (Closed-System ECIG Cons, Psychological Responses, Policy Outcome Concerns).

CONCLUSIONS

While a ban on open-system ECIG devices may have positive impacts on public health, policy loopholes, and consumer behaviors may undermine the policy. Efforts to support policy enforcement could increase policy effectiveness.

IMPLICATIONS

Open-system electronic cigarettes (ECIGs) that allow people who use ECIGs to modify ECIG device and liquid characteristics may limit the effectiveness of policies that establish product standards which attempt to limit nicotine delivery and flavor content in ECIG liquids. This study identified predicted reactions to a hypothetical policy prohibiting the sale of open-system ECIGs in the United States. Results suggest that people who use ECIGs may view a policy prohibiting open-system ECIGs unfavorably, but would be willing to use closed-system ECIGs. However, many ECIG users may attempt to find loopholes in the policy or alternative sources to purchase open-system ECIGs if open-systems were banned. Future research should identify strategies for tobacco regulatory policy enforcement to increase effectiveness.

Culturally specific health-related features on cigarette packs sold in China

BACKGROUND

China is the country with the highest burden of tobacco-caused disease. We characterised the extent to which cigarette pack marketing features (eg, imagery, text, pack color) could potentially mislead consumers by suggesting products are healthy.

METHODS

We used two methods: group concept mapping and content analysis. First, we used a group concept mapping approach to generate and sort Chinese consumer responses to an open-ended prompt asking what marketing features suggest a product is 'healthy' or 'good for you'. Second, based on the concept mapping results, we developed a codebook of health-related features on cigarette packs that were relevant to the unique cultural context of product marketing in China. Two trained coders who were native Chinese speakers double-coded a sample of 1023 cigarette packs purchased in 2013 (wave 1) and 2017 (wave 2). We examined differences in the presence of features overall and over time.

RESULTS

Overall, 83.5% (n=854) of Chinese cigarette packs in our sample contained at least one 'healthy' or 'good for you' feature, and the presence of health-related features on packs remained constant between wave 1 (83.5%, n=354) and wave 2 (83.5%, n=500; p=1.00). Across both waves, the most common categories of culturally specific health features present related to recycling symbols, rare animal imagery, bright colours (eg, bright yellow) and botanical imagery (eg, bamboo, mint).

CONCLUSION

Health-related features on cigarette packs sold in China are common. Enhanced policies to address tobacco packaging, labelling and branding could support and facilitate a reduction in the high tobacco burden in China.

Electronic Cigarette Users' Reactions and Responses to a Hypothetical Nicotine Concentration Reduction in Electronic Cigarette Liquids

Background: Regulations limiting nicotine in electronic cigarettes (e-cigarettes) have been proposed or implemented. Little is known about e-cigarette users' reactions to reducing e-cigarette liquid nicotine concentration. Methods: We used concept mapping to describe e-cigarette users' reactions to a 50% reduction in the nicotine concentration of their e-cigarette liquids. In 2019, current e-cigarette users who used e-cigarette liquid with greater than 0 mg/ml nicotine concentration completed an online study. Participants (n = 71, mean age = 34.9 (SD = 11.0), 50.7% women), brainstormed statements completing a prompt: "If the e-liquid that I use now in my e-cigarette/vaping device was only available in half the nicotine concentration or amount that I use now, a specific action I would take or a specific reaction I would have is…", Participants then sorted a final list of 67 statements into piles of similar content and rated statements on how true the statements would be for them. Multidimensional scaling and hierarchical cluster analyses identified thematic clusters. Results: Eight clusters were identified: (1) Replacement Product Seeking, (2) Mental Preparations and Expectations, (3) Use the New Liquid, (4) Information Seeking, (5) Compensation Behaviors, (6) Opportunity for E-Cigarette Reduction, (7) Physical and Psychological Effects, and (8) Replacement with non-E-Cigarette Products and Behaviors. Cluster ratings suggested many participants would search for other e-cigarette products/liquids to replace their current liquids, but using other tobacco products (e.g., cigarettes) may be less likely. Conclusions: If nicotine concentrations were decreased in e-cigarette liquids, e-cigarette users may attempt to purchase different e-cigarette products or modify their products to achieve desired effects.

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.

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

INTRODUCTION

Extant electronic cigarette (ECIG) dependence measures are largely adapted from those designed for cigarette smoking, though few have been evaluated for their psychometric properties.

AIMS AND METHODS

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).

RESULTS

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.

CONCLUSIONS

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.

IMPLICATIONS

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

INTRODUCTION

ECIGs 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.

METHODS

Participants (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).

RESULTS

Longer 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.

CONCLUSIONS

ECIG 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.

Electronic nicotine delivery systems (ENDS) dependence among Texas Young Adults, 2014-2019: Increasing trajectory after the 2017 surge in vape pod popularity

INTRODUCTION

Use of electronic nicotine delivery systems (ENDS) increased significantly after 2017. The increase is attributed to a surge in popularity of vape pods containing nicotine salts, which are high nicotine concentration ENDS that may heighten risk for dependence. However, little is known about changes in ENDS dependence before and after the 2017 surge. We examined the trajectory of ENDS dependence among young adults from 2014 to 2019.

METHODS

Participants were 1700 18-25-year-olds (57.6 % female) from 24 Texas colleges who reported past 30-day ENDS use in at least one of eight study waves. ENDS dependence was assessed at all waves with one item, use of ENDS within 30 min of waking. A discontinuous growth curve model was fit to test the hypothesis that the ENDS dependence trajectory would increase only after 2017, from 2018 to 2019. The model included socio-demographic and cigarette dependence covariates RESULTS: The proportion of young adults reporting ENDS dependence ranged from 2.3 % in 2014 to 8.2 % in 2019. Results from the discontinuous growth curve model indicated that the ENDS dependence trajectory was flat from fall 2014 to spring 2017. However, the post-2017 trajectory, from spring 2018 to spring 2019, was positive and significant indicating that the proportion of young adults reporting ENDS dependence increased after 2017.

CONCLUSIONS

The increase in ENDS dependence after 2017 likely resulted from the surge in popularity of vape pods containing nicotine salts. These vape pods are a disruptive technology that may result in more young adults developing nicotine dependence symptoms than do earlier generation devices.

Electronic cigarette users' reactions and responses to a hypothetical ban of flavoured electronic cigarette liquids

Regulations have been proposed to limit e-cigarette flavours, but limited research has examined potential impacts of such policies. This study examined adult e-cigarette users’ reactions to a hypothetical e-cigarette flavour ban.

Increased JUUL Emissions from Initial Puffs after Removing and Reinserting Pod

Standard laboratory electronic cigarette (ECIG) puffing protocols that do not consider user behaviors, such as removing and resinserting a pod, may underestimate emissions. This study compared JUUL emissions from four 10-puff bout procedures. We generated ECIG aerosol in a chamber using a JUUL device and measured concentrations of particulate matter ≤2.5 μm in diameter (PM_2.5). The JUUL pod was removed and reinserted 0 times, 1 time, 4 times, and 9 times in experiments 1-4, respectively. Mean real-time PM_2.5 concentration was 65.06 μg/m³ (SD = 99.53) for experiment 1, 375.50 μg/m³ (SD = 346.45) for experiment 2, 501.94 μg/m³ (SD = 450.00) for experiment 3, and 834.69 μg/m³ (SD = 578.34) for experiment 4. In this study, removing and reinserting a JUUL pod resulted in greater PM_2.5 concentrations compared to puffing protocols in which the JUUL pod was not removed and reinserted. ECIGs should be examined and evaluated based on ECIG users' real-world behaviors.

E-cigarette device and liquid characteristics and E-cigarette dependence: A pilot study of pod-based and disposable E-cigarette users

BACKGROUND

E-cigarette device and liquid characteristics, such as electrical power output and liquid nicotine concentration, determine the rate at which nicotine is emitted from the e-cigarette (i.e., nicotine flux), and thus are likely to influence user nicotine dependence. We hypothesize that nicotine flux would be associated with the E-cigarette Dependence Scale (EDS) among pod-based and disposable e-cigarette products.

METHODS

Data were obtained from online panel participants between 18 and 65 years of age, who had indicated that they were either former or current e-cigarette users and resided within the United States (N = 1036). To be included in these analyses, participants had to provide information regarding device type (pod-based or disposable), power (watts), and nicotine concentration (mg/mL), from which we could determine nicotine flux (µg/s) (N = 666). To assess the relationship between nicotine flux and EDS, a series of multivariable linear regressions were conducted. Each model was separated by device type and adjusted for by age and past 30-day e-cigarette use.

RESULTS

Greater nicotine flux was associated with higher EDS scores among pod-based e-cigarette users (beta = 0.19, SE = 0.09, p-value = 0.043), but not users of disposable e-cigarettes. Neither power nor nicotine concentration were associated with EDS scores among users of either e-cigarette device type.

CONCLUSION

Results support the hypothesis that nicotine flux is positively associated with nicotine dependence in a sample of current users of pod-based and disposable e-cigarettes.

Characterizing symptoms of e-cigarette dependence: a qualitative study of young adults

Background

While rates of e-cigarette use (‘vaping’) continue to potentiate concern, there is limited data on common symptoms of e-cigarette dependence among young adults who vape. This study sought to critically explore how young adults experience, manifest, and conceptualize vaping dependence symptoms in their everyday lives.

Methods

Between June 2018 and 2019, in-depth qualitative interviews were conducted with 62 young adults who use e-cigarettes (aged 18–25) and live in Southern California. We explored participants’ product preferences, daily e-cigarette use patterns, vaping history, withdrawal experiences, and quit attempts or periods of cessation. We used a thematic analysis approach to interpret the transcripts.

Results

Young adults discussed nine dimensions of vaping dependence that were organized into two categories: 1) general nicotine dependence symptoms, and 2) unique dependence symptoms related to vaping. Nicotine dependence symptoms included cravings and urgency to use, increased use to achieve desired effects, and unsuccessful quit attempts and withdrawal. Symptoms unique to vaping dependence included greater nicotine consumption due to accessibility and lack of restrictions, habitual vaping, inability to track vaping frequency, immediate gratification and comfort, social acceptability and norms, and awareness of vaping dependency.

Conclusions

In addition to nicotine dependence symptoms that have been characterized for other tobacco products, young adult e-cigarette users described unique symptoms of vaping dependence that necessitate the need for more refined measures. All dimensions of vaping dependence should be considered in discussions of policies as well as treatment and education efforts intended to protect young people from e-cigarette dependence.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10945-z.

Indicators of dependence and efforts to quit vaping and smoking among youth in Canada, England and the USA

OBJECTIVE

The current study examined indicators of dependence among youth cigarette smokers and e-cigarette users in Canada, England and the USA, including changes between 2017 and 2019.

METHODS

Data are from repeated cross-sectional online surveys conducted in 2017, 2018 and 2019 with national samples of youth aged 16-19 years, in Canada (n=12 018), England (n=11 362) and the USA (n=12 110). Measures included perceived addiction to cigarettes/e-cigarettes, frequency of experiencing strong urges to smoke/use an e-cigarette, plans to quit smoking/using e-cigarettes and past attempts to quit. Logistic regression models were fitted to examine differences between countries and changes over time.

RESULTS

The proportion of ever-users who vaped frequently was significantly higher in 2019 compared with 2017 for all outcomes in each country. Between 2017 and 2019, the proportion of past 30-day vapers reporting strong urges to vape on most days or more often increased in each country (Canada: 35.3%, adjusted OR (AOR) 1.69, 95% CI 1.20 to 2.38; England: 32.8%, AOR 1.55, 1.08 to 2.23; USA: 46.1%, AOR 1.88, 1.41 to 2.50), along with perceptions of being 'a little' or 'very addicted' to e-cigarettes (Canada: 48.3%, AOR 1.99, 1.44 to 2.75; England: 40.1%, AOR 1.44, 1.03 to 2.01; USA: 53.1%, AOR 1.99, 1.50 to 2.63). Indicators of dependence among smokers were consistently greater than e-cigarette users, although differences had narrowed by 2019, particularly in Canada and the USA.

CONCLUSIONS

Prevalence of dependence symptoms among young e-cigarette users increased between 2017 and 2019, more so in Canada and the USA compared with England. Dependence symptom prevalence was lower for e-cigarettes than smoking; however, the gap has narrowed over time.

Effects of Negative Emotion on Abstinence Induced Change in Urge to Vape and Measures of Vaping Dependence

INTRODUCTION

Negative emotion and craving to smoke are established factors driving the maintenance of combustible cigarette use and dependence. The current study aimed to examine whether these findings extend to e-cigarette use. Toward that aim, change in vaping urge following abstinence was examined as a function of negative emotion. Additionally, a mediation model which previously demonstrated relationships between negative emotion, craving, and combustible cigarette dependence was tested in e-cigarette users.

METHOD

Daily e-cigarette users (N = 32, M_age = 21 years, SD_age = 7 years; 78% white) completed a battery of psychological, behavioral, and smoking-related measures in a human laboratory setting. Using their personal devices, participants completed a 5-minute ad-libitum vaping session, a baseline measure of vaping urge, followed by a 2-hour observed abstinence period and a final assessment of vaping urge.

RESULTS

Multivariate regression and two mediation models were utilized to examine factors associated with vaping dependence. The results of these models indicated that negative affect predicted vaping urge following observed abstinence. The relationship between negative affect and measures of vaping dependence and habit, respectively, were significantly mediated by changes in urge during the abstinence period.

CONCLUSIONS

These preliminary results indicate that psychological constructs underlying vaping dependence are similar to those previously found to be associated with combustible cigarette dependence. Further research examining whether these constructs, namely negative affect and change in urge following abstinence, will be important variables to target for vaping cessation treatments is needed.

Impacts of COVID-19 on Electronic Cigarette Purchasing, Use and Related Behaviors

Background: COVID-19 has caused health impacts and disruptions globally. Electronic cigarette (ECIG) users may face additional impacts. This study examined impacts of COVID-19 on ECIG users. Methods: Concept mapping, a mixed-methods approach, was used to identify COVID-19 impacts on adult ECIG users. ECIG users (n = 93) provided statements completing a prompt: "A specific way Coronavirus/COVID-19 has affected my vaping/e-cigarette use, my vaping/e-cigarette related purchasing, or other vaping/e-cigarette related behaviors or issues is…". Participants generated 85 unique statements, sorted statements into groups of similar content and rated each statement on how true they were. Multidimensional scaling and hierarchical cluster analysis identified thematic clusters. Mean cluster ratings were compared between sample subgroups. Results: Ten clusters were identified: Stocking up and Bulk Purchasing, Challenges in Obtaining ECIG Supplies, Alternative Purchasing Procedures, Increased ECIG use, Disruption of Routine and ECIG Use, Efforts to Decrease ECIG Use, Improving ECIG Skills, COVID-19 Health Concerns, Perceptions of ECIG Use and COVID-19, and COVID-19 Protection. More dependent ECIG users and dual users of ECIGs and cigarettes rated clusters higher than less dependent ECIG users and non-dual users. Conclusions: ECIG users may experience or perceive they face additional COVID-19 impacts, such as increased exposure, financial burdens, stress, and health risks.

Unique, long-term effects of nicotine on adolescent brain

Adolescence is a time of major plasticity of brain systems that regulate motivated behavior and cognition, and is also the age of peak onset of nicotine use. Although there has been a decline in teen use of cigarettes in recent years, there has been a huge increase in nicotine vaping. It is therefore critically important to understand the impact of nicotine on this critical phase of brain development. Animal studies have shown that nicotine has unique effects on adolescent brain. The goal of this review is therefore to systematically evaluate age- and sex-differences in the effects of nicotine on brain and behavior. Both acute and chronic effects of nicotine on brain biochemistry and behavior, particularly drug reward, aversion, cognition and emotion, are evaluated. Gaps in our current knowledge that need to be addressed are also highlighted. This review compares and integrates human and animals findings. Although there can be no experimental studies in humans to confirm similar behavioral effects of teen nicotine exposure, an emerging observational literature suggests similarities across species. Given the substantial evidence for long-term negative impact of adolescent nicotine exposure on brain and behavior, further longitudinal assessment of health outcomes in teen and young adult e-cigarette users is warranted.