Waterpipe Tobacco Brands and Flavors Sold Online in the USA.

INTRODUCTION: Flavor additives are commonly used in combustible tobacco products to mask harshness and increase appeal. However, research on the availability of flavored waterpipe tobacco (WT) is lacking, yet is important to support implementation of policies. METHODS: We completed a comprehensive online search in 2020 to identify WT brands and flavors sold online in the USA. We conducted a descriptive content analysis categorizing flavors as explicit (i.e., clear taste/flavor) or concept (i.e., no clear taste/flavor); and coded for 23 flavor descriptors (e.g., fruit, mint/menthol, tobacco). Flavor names were double-coded and discrepancies were resolved by a third coder. RESULTS: We identified 66 WT brands with 118 product lines (i.e., sub-brands). We found 2953 flavors, including 1871 unique flavors. Brands averaged 45 flavors (range: 1-183). Almost three quarters (73.5%, n = 2171) used explicit flavor names and 26.5% (n = 782) used concept flavor names. Concept flavors varied widely, and included names such as 1001 Nights and California Dream. The most common flavor descriptors were fruit (54.1%) and mint/menthol (12.5%). Tobacco was rarely (0.2%) used as a flavor descriptor. Flavor descriptors also included location (10.7%), color (11.1%), candy (6.3%), cool/ice (5.3%), and alcohol (5.5%). CONCLUSIONS: WT is available in 1871 unique flavors, likely contributing to product appeal and use. Like other tobacco products, fruit and mint/menthol are common flavors. Given the significant health consequences associated with WT smoking and the role of flavors in product use, regulatory action specifically targeting WT flavors is urgently needed.

Hidden flaws in e-cigarette industry-funded studies.

Electronic cigarette (e-cigarette) use has increased since e-cigarettes were introduced to the market nearly 20 years ago. Researchers continue to conduct studies to understand the health risks and benefits of e-cigarettes to inform health education and promotion efforts as well as public policy. Studies funded by the tobacco industry examining the potential risks and benefits of e-cigarettes have also been conducted and are sometimes published in the scientific literature. Frequently, tobacco and e-cigarette industry-funded researchers report findings that contradict research funded by other sources. While many industry-funded studies may appear methodologically sound at first glance, in some cases, industry-funded studies include methodological flaws that result in misleading conclusions. The tobacco industry's use of biased research to influence tobacco-related policy decisions in the past is well-documented. This commentary provides specific examples of recent e-cigarette research funded by the tobacco/e-cigarette industry in which methodological flaws result in misleading conclusions that support industry goals. Given the long history of biased research conducted by the tobacco industry, there is a need to assess whether research funded by the e-cigarette industry similarly contains methodological flaws. We emphasise the need for tobacco and e-cigarette-funded research to be scrutinised by non-industry-funded subject matter experts and call for journals to not consider manuscripts that have received support from the tobacco or e-cigarette industry.

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.

Use of real-time monitors to evaluate the potential exposure of secondhand electronic cigarette particulate matter inside vehicles.

Electronic cigarette (ECIG) use continues to be highly prevalent, especially among youth and young adults. Potential exposure from secondhand ECIG particulate matter (PM) places bystanders in danger of inhaling harmful substances, especially in confined spaces. This study was conducted to measure the potential exposure from secondhand ECIG PM exposure in vehicles, with participants completing a 30-min ECIG use session in their own vehicle with their preferred ECIG device. Sessions included a 5-min, 10-puff directed bout (30-s interpuff interval), followed by a 25-min ad libitum bout in which participants could take as many puffs as desired. Real-time PM1, PM2.5, and PM10 (the 50% efficiency mass cut-off of that passes through a size-selective inlet at 1 µm, 2.5 µm, and 10 µm aerodynamic diameters, respectively) measurements were captured during the sessions using portable PM monitors (MiniWRAS, pDR, SidePak, and GeoAir2 low-cost monitors). A total of 56 participants with valid measurements were included in the study, with a total of 13 unique ECIG device brands, including Vuse Alto, Box Air Bar, ElfBar, Esco Bar, Aegis Legend, Hyde Edge, JUUL, Kang Onee Stick, Kang Onee Stick Plus, Nord X, Nord 2, Nord 3, and Vaporesso. During the 5-min directed bout, the highest real-time PM2.5 mean concentrations were 175 µg/m3 for the MiniWRAS, 1050 µg/m3 for pDR and 3314 µg/m3 for SidePak. The filter measurements were not detectable in most experiments, except for two participants, with one taking 205 puffs and the other taking 285 puffs, approximately 10 times the mean (30) puffs of all participants. The evaluation of GeoAir2 with the MiniWRAS showed a wide range of Pearson correlation coefficient (r) values, ranging from -0.03 to 1.00, for the 13 ECIG brands. The mass median diameter (0.31 µm-3.42 µm) and geometric standard deviation (2.47-8.21) were different based on the participants for the same ECIG brand.

Secondhand electronic cigarette aerosol in vehicles impacts indoor air quality.

BACKGROUND: Electronic cigarette (ECIG) use in vehicles represents a public health concern due to the potential for exposure to high concentrations of particulate matter (PM) and other toxicants. This study examined the impact of ECIG use on air quality in vehicles. METHODS: People who reported current ECIG use (n=60; mean age=20.5, SD=2.3) completed a brief survey and a 30-min ECIG use session in their own vehicle. Using a protocol similar to clinical laboratory studies involving tobacco use, participants took 10 directed puffs (i.e., a directed bout with one puff every 30s for 5min) followed by a 25-min ad libitum period in which participants took as many puffs as desired. PM 2.5µm in diameter or smaller (PM2.5) were measured using aerosol monitors set up to sample air from the breathing zone of the passenger seat and total puffs were recorded. The association between peak PM2.5 concentration and puff count was examined. RESULTS: Participants took a median 18 total puffs during the sessions. Median PM2.5 concentrations increased from 4.78µg/m3 at baseline to 107.40µg/m3 after the directed bout. Median peak PM2.5 concentration was 464.48µg/m3 and ranged from 9.56µg/m3 to 143,503.91µg/m3 (IQR=132.72-1604.68). After removing two extreme outliers for puff count and PM2.5 concentrations, puff count was significantly correlated with peak PM2.5 concentration during the ad libitum bout (r=0.32, p=0.015). CONCLUSIONS: ECIG use in vehicles impacts air quality negatively and may pose health risks to those present in vehicles when ECIG use is occurring.

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.

Absence of Age Verification for Online Purchases of Cannabidiol and Delta-8: Implications for Youth Access.

PURPOSE: This study assessed the age verification process for purchasing and shipping cannabidiol (CBD) and Delta-8 tetrahydrocannabinol products from online retailers. METHODS: We purchased CBD and Delta-8 products online from 20 brick-and-mortar shops located in the United States that sold products online and shipped products to consumers. We documented online age verifications at the time of purchase and whether identification or a signature was required at delivery. RESULTS: 37.5% of the CBD and 70.0% of the Delta-8 websites required the customer to confirm their age (18 + or 21+ years). Age verification or contact with the customer was not requested at the point of home delivery for all products. DISCUSSION: Methods for age verification at time of purchase are self-reported and easily circumvented. Policies and policy enforcement are needed to prevent youth access to CBD and Delta-8 products from online sources.

Reactions to a Hypothetical Menthol Cigarette Ban among Sexual- and Gender-Minoritized Communities: A Concept Mapping Study.

Menthol cigarette use is disproportionately higher among sexual- and gender-minoritized (SGM; 36%) individuals compared to cisgender, heterosexual (29%), individuals. The FDA has announced intentions to ban menthol in cigarettes, citing these use and health disparities as partial motivation. This study identified potential outcomes of a menthol cigarette ban among SGM individuals who smoke menthol cigarettes (N = 72). Potential outcomes were identified via concept mapping using the prompt: "If menthol in cigarettes was banned, a specific action I would take related to my tobacco use is…" Participants generated 82 response statements, sorted them, and rated them on personal relevance. Eight thematic clusters were identified: (1) Thoughtful Consideration of the Ban, (2) Negative Reactions to the Ban, (3) Positive Aspects of the Ban, (4) Strategies to Reduce Cravings, (5) Intent to Quit and Cessation Strategies, (6) Support-Seeking and Engagement in Positive Behaviors, (7) Strategies to Maintain Menthol-Flavored Product Use, and (8) Substance Use Alternatives to Menthol Cigarettes. Cluster differences based on sociodemographic factors, smoking behavior, and quitting interest were identified. Results provide insight into potential responses to a menthol cigarette ban and can contribute to public health prevention and intervention efforts, messaging campaigns, and support services for SGM people who smoke menthol cigarettes, specifically.

Impact of Canada's menthol cigarette ban on quitting among menthol smokers: pooled analysis of pre-post evaluation from the ITC Project and the Ontario Menthol Ban Study and projections of impact in the USA.

INTRODUCTION: Between 2015 and 2018, Canada banned menthol cigarettes. This study pooled data from two pre-post cohort studies (the Ontario Menthol Ban Study, and the International Tobacco Control Policy Evaluation (ITC) Canada Survey, conducted in seven provinces) to derive more precise estimates of the impact of Canada's menthol ban on quitting and to apply these estimates to project the impact of a menthol ban in the USA. METHODS: Weighted multivariable logistic analyses compared post-ban quit success of menthol smokers with non-menthol smokers (for daily smokers and for all (daily + non-daily) smokers), controlling for sex, age, ethnicity, education, baseline smoking status, baseline cigarettes per day and study regions. Projections to the USA were created by multiplying the effect size of the Canadian menthol ban on quitting (percentage of increased quitting among menthol smokers) by the number of menthol smokers overall and among African Americans, from the 2019 National Survey on Drug Use and Health. RESULTS: After the menthol cigarette ban, menthol smokers were more likely than non-menthol smokers to have quit smoking among daily smokers (difference=8.0%; 95% CI: 2.4% to 13.7%,p=0.005) and all (daily+non-daily) smokers (difference=7.3%; 95% CI: 2.1% to 12.5%,p=0.006). The projected number of smokers who would quit after a US menthol ban would be 789 724 daily smokers (including 199 732 African Americans) and 1 337 988 daily+non-daily smokers (including 381 272 African Americans). CONCLUSIONS: This pooled analysis of Canada's menthol cigarette ban provides the foundation for estimating the impact of menthol bans in the USA and other countries. Projections suggest that a US menthol cigarette ban would have a substantial impact on increasing quitting.

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 (ß's = 0.91 and 1.90, respectively; p's < 0.01) and EDS-4 scores (ß's = 0.16 and 0.28, respectively; p's < 0.01). Higher nicotine concentrations were associated with higher PSECDI scores only (ß = 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 Cigarette Nicotine Flux, Nicotine Yield, and Particulate Matter Emissions: Impact of Device and Liquid Heterogeneity.

INTRODUCTION: Electronic cigarettes (ECIGs) heat a nicotine-containing liquid to produce an inhalable aerosol. ECIG power (wattage) and liquid nicotine concentration are two factors that predict nicotine emission rate ("flux"). These factors can vary greatly across devices and users. AIMS AND METHODS: The purpose of this study was to examine ECIG device and liquid heterogeneity in "real world" settings and the association with predicted nicotine flux, nicotine yield, and total particulate matter (TPM) emissions. Past 30-day ECIG users (n = 84; mean age = 23.8 years [SD = 9.6]) reported device and liquid characteristics. Device power was measured via multimeter, device display screens, or obtained via labeling. Liquid nicotine concentration was obtained via labeling or through chemical analysis. Predicted nicotine flux, nicotine yield, and TPM associated with 10 4-second puffs were calculated for participants' primary devices. RESULTS: Participants' primary devices were box mods (42.9%), disposable vapes (20.2%), and pod mods (36.9%). Most participants (65.5%) reported not knowing their primary device wattage. Rebuildable/box mods had the greatest power range (11.1-120.0 W); pod mod power also varied considerably (4.1-21.7 W). Unlike device wattage, most participants (95.2%) reported knowing their liquid nicotine concentration, which ranged from 3.0 to 86.9 mg/ml (M = 36.0, SD = 29.3). Predicted nicotine flux varied greatly across products (range =12.0-160.1 µg/s, M = 85.6 µg/s, SD = 34.3). Box mods had the greatest variability in wattage and predicted nicotine flux, nicotine yield, and TPM yield. CONCLUSIONS: ECIG device and liquid heterogeneity influence nicotine and other toxicant emissions. Better measurement of ECIG device and liquid characteristics is needed to understand nicotine and toxicant emissions and to inform regulatory policy. IMPLICATIONS: ECIG device and liquid heterogeneity cause great variability in nicotine flux and toxicants emitted. These data demonstrate the need to examine device and liquid characteristics to develop empirically informed, health-promoting regulatory policies. Policies may include setting product standards such that ECIG products cannot (1) have nicotine fluxes much greater than that of a cigarette to decrease the risk of dependence, (2) have nicotine fluxes that are very low and thus would have minimal appeal to cigarette smokers and may serve as starter products for youth or nontobacco users, and (3) emit large amounts of particulate matter and other toxicants.

Assessing toxicant emissions from e-liquids with DIY additives used in response to a potential flavour ban in e-cigarettes.

SIGNIFICANCE: Electronic cigarettes (e-cigarettes) aerosolise liquids that contain nicotine, propylene glycol, glycerol and appealing flavours. In the USA, regulations have limited the availability of flavoured e-cigarettes in pod-based systems, and further tightening is expected. In response, some e-cigarette users may attempt to make their e-liquids (do-it-yourself, DIY). This study examined toxicant emissions from several aerosolised DIY e-liquids. METHODS: DIY additives were identified by reviewing users' responses to a hypothetical flavour ban, e-cigarette internet forums and DIY mixing internet websites. They include essential oils, cannabidiol, sucralose and ethyl maltol. E-liquids with varying concentrations and combinations of additives and tobacco and menthol flavours were prepared and were used to assess reactive oxygen species (ROS), carbonyl and phenol emissions in machine-generated aerosols. RESULTS: Data showed that adding DIY additives to unflavoured, menthol-flavoured or tobacco-flavoured e-liquids increases toxicant emissions to levels comparable with those from commercial flavoured e-liquids. Varying additive concentrations in e-liquids did not have a consistently significant effect on the tested emissions, yet increasing power yielded significantly higher ROS, carbonyl and phenol emissions for the same additive concentration. Adding nicotine to DIY e-liquids with sucralose yielded increase in some emissions and decrease in others, with freebase nicotine-containing e-liquid giving higher ROS emissions than that with nicotine salt. CONCLUSION: This study showed that DIY additives can impact aerosol toxicant emissions from e-cigarettes and should be considered by policymakers when restricting commercially available flavoured e-liquids.

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

BackgroundRegulations 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. METHODS: In 2019, a convenience sample of current e-cigarette users in the USA (n=81, 53.1% women, mean age=37.6, 59.3% dual users of cigarettes) completed an online concept mapping study. Participants provided statements describing anticipated reactions to a hypothetical policy in which only tobacco, menthol or unflavoured e-cigarettes were available for purchase. Seventy-one unique statements were generated. Participants sorted statements into thematic groups and rated statements on how likely they would be to have each reaction. Multidimensional scaling was used to identify thematic clusters of statements. RESULTS: Twelve clusters were identified: negative reaction, take action against flavour limitation, youth prevention effectiveness perception, tolerance, acceptance, willingness to try new flavours, maintain vaping, reduce vaping, new flavours as vaping cessation transition, alternative sources for banned flavours, do-it-yourself mixing behaviours and alternative tobacco products. The highest rated cluster (negative reaction) described being angry or upset that flavours were banned, while the lowest rated clusters related to quitting/reducing e-cigarette use or switching to other tobacco products. Non-tobacco or non-menthol/mint flavoured e-cigarette users had higher ratings for clusters describing negative sentiment for the hypothetical policy. CONCLUSIONS: Some e-cigarette users may dislike an e-cigarette flavour ban; however, some e-cigarette users would likely be willing to use tobacco, menthol or unflavoured e-cigarette liquids with lower likelihood of quitting vaping or switching to other tobacco products.

Perceived Barriers to Serving on National Institutes of Health Scientific Review Groups Experienced by Black and African American Scientists.

Importance: African American and Black scientists are awarded disproportionately fewer National Institutes of Health (NIH) grants than White scientists. Increasing Black representation on NIH scientific review groups (SRGs) likely will contribute to increased equity in funding rates because research topics of Black and African American scientists' submitted applications will be more highly valued; however, Black and African American scientists often perceive barriers that prevent them from serving on NIH SRGs. Objective: To examine perceived barriers that prevent Black and African American scientists from serving on NIH SRGs. Design, Setting, and Participants: This qualitative study used a mixed methods online approach with a convenience sample of Black and African American scientists to identify barriers to NIH grant review participation. Eligible participants were recruited online from professional organizations with primarily Black and African American membership. From February through April 2021, participants were asked to identify barriers to serving on NIH SRGs using concept mapping. Participants brainstormed statements describing barriers to serving on NIH SRGs, sorted statements into content themes, and rated statements on how true they were. Multidimensional scaling and a hierarchical cluster analysis identified content themes. Data analysis was conducted in May and June of 2021. Main Outcomes and Measures: Self-reported barriers to serving on an NIH SRG among Black and African American scientists. Results: A total of 52 scientists participated in both phases of the study (mean [SD] age, 42.3 [8.2] years; 46 women [88.5%]). Participants provided 68 unique statements that were organized into 9 thematic clusters describing barriers to serving on NIH SRGs. Themes included structural racism, diversity not valued, toxic environment, review workload demand, lack of reward, negative affect about the review process, competing demands at home institution, lack of opportunity, and perceptions of being unqualified. Conclusions and Relevance: Black and African American scientists reported many barriers to serving on NIH SRGs that are unique to Black and African American scientists, as well as barriers that transcend race but are exacerbated by structural racism. This study provides NIH with concrete opportunities to address realized barriers to increase inclusion of Black and African American scientists on NIH SRGs, fund more Black and African American scientists, and ultimately reduce health inequities in the US.

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 (PM2.5). The JUUL pod was removed and reinserted 0 times, 1 time, 4 times, and 9 times in experiments 1-4, respectively. Mean real-time PM2.5 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 PM2.5 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.

Aerosol, vapor, or chemicals? College student perceptions of harm from electronic cigarettes and support for a tobacco-free campus policy.

Objective: This study is the first to examine the influence of e-cigarette emission phrasing on perceived harm of secondhand exposure, and whether harm perception was associated with support for a tobacco-free campus policy. Participants: In the fall 2018 and spring 2019 semesters, 52 sections of a college English course (N = 791 students) were cluster randomized to one of three conditions ("vapor," "aerosol," or "chemicals") assessing harm of secondhand exposure to e-cigarette emissions. Methods: Regression models adjusted for demographic characteristics, tobacco use, and other potential confounders. Results: Compared to the "vapor" condition, "chemicals" and "aerosol" conditions were associated with increased odds of perceiving secondhand exposure to e-cigarettes to be harmful/very harmful (AOR = 2.0, p < 0.01). Greater perceived harm of secondhand e-cigarette exposure was associated with increased odds of supporting a tobacco-free campus policy (AOR = 2.22, p < 0.001). Conclusions: Health campaigns should use accurate terminology to describe e-cigarette emissions, rather than jargon that conveys lower risk.

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.

Impacts of COVID-19 on cigarette use, smoking behaviors, and tobacco purchasing behaviors.

BACKGROUND: The COVID-19 pandemic has had a significant global impact. As a respiratory illness, COVID-19 may pose unique risks to cigarette smokers. This study used concept mapping, a mixed-method participatory approach, to identify impacts of COVID-19 on cigarette smokers. METHODS: Cigarette smokers across the United States (U.S.) were recruited to complete this online, multi-step study. Of the 126 participants who were invited to participate in this study, 91 participants (mean age = 40.9; SD = 11.3) completed at least one of the three study tasks (i.e., brainstorming, sorting, and rating). Participants completed a brief demographic survey and brainstormed statements that completed a focus prompt: "A specific way that Coronavirus/COVID-19 has impacted/affected my cigarette use, smoking behaviors, tobacco purchasing behaviors, and/or other tobacco-related behaviors is." After duplicate statements were removed, participants sorted the final list of 87 statements by similarity of content and rated how true statements were from them (1-Definitely NOT true to 7-Definitely true). RESULTS: Nine thematic clusters were identified: Smoking More, Smoking to Cope/Reduce Stress, Change in Smoking Behaviors Due to COVID-19, Concerns about Smoking and COVID-19 Risk, Social Impacts, Maintaining and Rationing Cigarette Supply, Impacts on Obtaining Cigarettes, Use of Other Tobacco Products/Drugs, and Minimal/No Impacts/Concerns of COVID-19. The highest rated cluster (i.e., most true) was the Smoking More cluster followed by the Concerns about Smoking and COVID-19 Risk cluster. The highest rated statement in the study was the statement "Smoking keeps me calm". CONCLUSIONS: Cigarette smokers may endure additional impacts of COVID-19, such as increased COVID-19 health burdens, stressors related to risk of exposure, social stigma and isolation, financial burdens, and increased toxicant exposure from increased smoking frequency.