BACKGROUND: Smoking for weight control is a well-documented behavior. There is emerging evidence to suggest electronic cigarettes (e-cigarettes) may be used for similar motivations yet measure development for the use of e-cigarettes for weight control has received less attention. The objective of the current study was to adapt and explore the psychometric properties of The Smoking-Related Weight and Eating Episodes Test (SWEET) for e-cigarette users.
METHODS: Young adult (N=1875) current cigarette, e-cigarette, and dual users completed the original SWEET (SWEET-C) and/or adapted SWEET for e-cigarette use (SWEET-EC) based on current tobacco product use. Demographics, associated e-cigarette characteristics, nicotine dependence, outcome expectancies, and eating disorder behaviors were also assessed. Participants were recruited online and measures were completed via self-report.
RESULTS: Four exploratory factor analyses using principal components extraction and direct oblimin rotation methods were run to explore the SWEET-C and SWEET-EC. A one-factor solution explaining 66 % of the variance was retained for the SWEET-C, and a one-factor solution explaining 73 % of the variance was retained for the SWEET-EC. Both measures exhibited excellent internal consistency. Higher SWEET-EC scores were observed among dual users, and were associated with daily e-cigarette use, JUUL use, self-reported vaping for weight control, older age, higher body mass index, and problematic eating behaviors.
CONCLUSIONS: Our findings support the adaptation of the SWEET-EC to measure e-cigarette use for weight control. The SWEET-EC will help to better understand how individuals use e-cigarettes to curb eating behavior and for weight control.

BACKGROUND: E-cigarette use has increased considerably among US adolescents. While many studies have described cross-sectional prevalence trends of youth e-cigarette use, less is known about cohort or generational initiation and use patterns.
METHODS: We used data from the US National Youth Tobacco Survey (NYTS) from 2014 to 2022 and age-period-cohort models to analyze age-specific patterns of e-cigarette use initiation and prevalence by cohort and calendar. For comparison, we also examined initiation and prevalence for cigarettes, cigars, and smokeless tobacco, using NYTS data from 1999 to 2022.
RESULTS: Age-specific e-cigarette initiation and prevalence varied considerably by calendar year and birth cohort. There was a rapid increase in e-cigarette initiation and prevalence starting with the 1995 birth cohort, peaking with the 2005 birth cohort, and showing signs of decline with more recent cohorts. In contrast, there were substantial continuous reductions in cigarette, cigar, and smokeless use initiation and prevalence by birth cohort. While the reductions in cigarette smoking started with the 1980s birth cohorts, cigar and smokeless initiation and prevalence did not decrease until the 1990-1995 cohorts.
CONCLUSIONS: Despite their recent emergence, e-cigarette use has varied considerably across US adolescent cohorts. After early increases, e-cigarette use and initiation peaked with the 2005 birth cohort. These patterns are in contrast with the continuous decreases by cohort in cigarette, cigar, and smokeless use and initiation. As the tobacco product landscape continues to evolve, it will be essential to monitor patterns of use of adolescent and young adult cohorts as they age into adulthood.

BACKGROUND: Youth vaping is a serious public health concern, being more prevalent than any other tobacco use. To inform cessation interventions, we explored what adolescents perceive as their reasons for quitting and strategies to help them quit.
METHODS: Semi-structured interviews were conducted with a convenience sample of 11 adolescents reporting vaping in the past 90 days and recruited from a high school in Massachusetts. Interviews were transcribed and dual-coded. Inductive thematic analysis was employed, and thematic summaries were prepared.
RESULTS: Reasons adolescents reported for quitting included cost, experiencing \"nic-sick\" from nicotine withdrawal or excess intake, negative impacts on mood, concentration, or health, and experiencing symptoms of nicotine dependence. Nearly all tried to quit multiple times. Barriers to quitting included exposure to vaping, access to vape products, stress, and \"cool\" new products or flavors. Quit strategies included avoiding others vaping, seeking social support to quit, addressing peer pressure to continue vaping, learning successful quit strategies from peers, and using distraction strategies or alternatives to vaping.
CONCLUSIONS: Many adolescents who vape want to quit, and most have tried multiple times. Interventions need to engage adolescents with varying reasons to quit, barriers, and quit strategy preferences.
BACKGROUND: This study is registered through ClinicalTrials.gov. The trial registration number is NCT05140915. The trial registration date is 11/18/2021.

Electronic (e-)cigarettes may help adult cigarette smokers achieve cigarette cessation, depending on patterns of e-cigarette use. Among cigarette smokers who do not use e-cigarettes, it is unclear if and how a-priori intentions for use are related to uptake patterns. Longitudinal studies have focused on established e-cigarette users or adolescent and young adult populations exclusively.
Within a nationwide randomized clinical trial (N = 638), adult cigarette smokers not currently using e-cigarettes were randomized (2:1) to receive (or not) one-month sampling of e-cigarettes. An exploratory factor analysis (EFA) was performed on an established 15-item measure assessing a-priori intentions for e-cigarette use to identify latent variables. Among those receiving e-cigarette products, regression models examined relationships between intentions and: 1) uptake (yes/no), 2) frequency (number of days per week), and 3) amount (puffing episodes per day) of e-cigarette use at one-month follow-up.
Two factors emerged from the EFA: 1) cigarette-related intentions (e.g., cigarette cessation, no smell) and 2) novel appeal of e-cigarettes (e.g., flavors). Three items remained and were treated as separate intentions: \"feels like cigarette smoking\", \"curiosity\", and \"affordability\". In the final multivariable models, \"feel like cigarette smoking\" predicted more frequent e-cigarette use (β = 0.187, SE = 0.086, p = 0.03); however, none of the five factors/intentions were significantly associated with uptake or amount of use.
For adult cigarette smokers not currently using e-cigarettes, a-priori intentions for using e-cigarettes might not be predictive of if or how these products will be used in the future, suggesting that motives may not drive use behavior.

To determine the relationship between past-year internalizing symptoms and the time to first report of signs of nicotine dependence among young people.
Secondary analysis using data from the Population Assessment of Tobacco and Health (PATH) (Waves 1-5; 2013-2019). The study included 2,102 (N = 5,031,691) young people (age 12-23 years) who reported past-30-day (P30D) e-cigarette use in one or more waves. Kaplan Meier curves, stratified by past year internalizing symptoms were used to estimate the time to the first report of three nicotine dependence symptoms (i.e., use within 30 min of waking, cravings, and really needing to use) following the first P30D e-cigarette use. Cox proportional hazard models were used to estimate crude and adjusted hazard ratios (AHR), comparing any past year internalizing symptoms to no past year internalizing symptoms.
We found no significant differences between past year internalizing symptoms and the time to the first report of cravings (AHR = 1.30, 95 % CI = 92-1.85), really needing to use (AHR = 1.31; 95 % CI = 0.92-1.89) and use within 30 min of waking for follow-up times 0-156 weeks (AHR = 0.84; 95 % CI = 0.55-1.30) and > 156 weeks (AHR = 0.41; 95 % CI = 0.04-4.67) respectively.
Past year internalizing symptoms did not modify the time to the first report of nicotine dependence among youth with P30D e-cigarette use. Further research is needed to understand how changing internalizing symptoms and e-cigarette use frequency influence nicotine dependence over time and, how this relationship impacts cessation behavior.

Objective: Tobacco use and obesity are leading causes of preventable death in the U.S. E-cigarette use is on the rise; however, obesity prevalence among e-cigarette users is unknown. The present study characterized obesity prevalence among e-cigarette and tobacco users in a national sample of U.S. adults. Method: Data were obtained from the 2018 Behavioral Risk Factor Surveillance System. Approximately 249,726 participants provided data on e-cigarette and tobacco use, height, weight, and demographics, and were categorized as follows: Ever vaped, ever smoked; Ever vaped, never smoked; Never vaped, ever smoked; Never vaped, never smoked. Results: Obesity prevalence (BMI ≥30 kg/m2) differed significantly across groups: 33.0% (ever vaped, ever smoked); 27.7% (ever vaped, never smoked); 33.1% (never vaped, ever smoked); 32.1% (never vaped, never smoked), p < .001. Groups also differed demographically. Logistic regressions adjusted for demographics revealed subjects in the never vaped, ever smoked group were significantly more likely to have obesity relative to those in the never vaped, never smoked group (p < 0.001) with vaping status having no main effect. Secondary analyses using never smokers as the reference found current smokers were less likely to have obesity and former smokers were more likely to have obesity, p < .001. Discussion: The present study is the first to characterize U.S. obesity prevalence among e-cigarette and tobacco users. Obesity prevalence was lower in the ever vaped, never smoked group; however, this finding appears to be attributable to demographic variables. As e-cigarette use becomes more common, future research should examine the development and maintenance of obesity among users.

Background: Past year, month, and lifetime adolescent e-cigarette use rates remain persistently high, despite falling cigarette use rates. Previous investigations have noted a strong relationship between an individual\'s positive and negative cognitions related to a behavior, and subsequent initiation of that behavior.Objective: This investigation was conducted to determine the impact positive and negative explicit and implicit cigarette-related cognitions may have on the use of cigarettes and e-cigarettes among at-risk, cigarette-naive adolescents.Methods: A three-year longitudinal investigation evaluated the relationship between cigarette-related cognitions and subsequent cigarette and e-cigarette use among 586 alternative high school students (female: 50.8%; mean age: 17.4 years; Hispanic/Latino: 75.0%) who had never smoked cigarettes at the baseline assessment. Multilevel logistic regression models were used to generate demographics-adjusted odds ratios (OR) and 95% confidence intervals (95% CI).Results: Students with higher positive explicit cigarette cognitions at the baseline had greater odds of subsequent cigarette use (OR = 1.72, 95% CI 1.11-2.68). If students also reported an increase over time in positive (OR = 3.45, 95% CI 2.10-5.68) or negative (OR = 1.93, 95% CI 1.03-3.61) explicit cigarette cognitions, the odds of cigarette use increased. The odds of dual use of cigarettes and e-cigarettes were greater among students who had higher negative implicit cigarette cognitions at the baseline (OR = 2.07, 95% CI 1.03-4.17) compared to those with lower levels of negative implicit cognitions.Conclusion: Prevention programming that focuses on decreasing positive cognitions related to nicotine and tobacco use may have greater overall effect on decreasing use compared to programs that only focus on increasing negative cognitions individuals form surrounding cigarette or e-cigarettes.

BACKGROUND: The popularity of e-cigarettes is on the rise among current cigarette users. Therefore, there are concerns about their health implications. This study examined the impact of health-related social media use on e-cigarette use among current cigarette users. It assesses the mediating influence of online anti-tobacco messages and the moderating role of the harm perception of e-cigarettes.
METHODS: This study was focused on 563 current cigarette users from the 2022 Health Information National Trends Survey (HINTS). Three tasks were performed: (1) assessing the direct and indirect impacts of health-related social media use on e-cigarette use among current cigarette users, (2) exploring the mediating role of exposure to online anti-tobacco messages, and (3) examining the moderating influence of e-cigarette harm perception on the path from anti-tobacco messages to e-cigarette use.
RESULTS: Health-related social media use was positively associated with current cigarette users\' e-cigarette use directly (bp = 0.183, p < .01) and indirectly through exposure to online anti-tobacco messages (bp = 0.023, 95% CI: [0.001, 0.051]). Harm perception of e-cigarettes moderated the relationship between online exposure to anti-tobacco messages and e-cigarette use (bp=-0.467, p < .01). The relationship appeared weaker for individuals who perceived greater harm from e-cigarettes.
CONCLUSIONS: Health-related social media use positively correlates with e-cigarette use among current cigarette users through exposure to online anti-tobacco messages. The perceived harm of e-cigarettes moderates this indirect path. These findings have implications for public health interventions aimed at smoking cessation.

UNASSIGNED: Past research indicates that young adult cigarette smokers are at risk of engaging in maladaptive eating behaviors (MEBs); however, whether this relationship extends to nicotine vaping is unclear. The current study assessed bidirectional associations between four types of MEBs and nicotine vaping among young adults.
UNASSIGNED: 1,303 young adults (20.5 ± 2.3 years; 63 % female) from a public, urban university were recruited and completed online surveys at six-month intervals from spring 2021 (W1) to spring 2023 (W5). Past 30-day nicotine vaping and four types of MEBs (susceptibility to external cues, emotional eating, routine restraint, and compensatory restraint) were evaluated.
UNASSIGNED: Longitudinal cross-lagged models examined the bidirectional relationships between past 30-day nicotine vaping and each type of MEB across five waves. Nicotine vaping predicted both susceptibility to external cues (β = 0.10, p <.05; Wave 2 to 3) and emotional eating (β = 0.08, p <.05; Wave 1 to 2). A significant cross-lag regression (Wave 4 to 5) showed nicotine vaping predicted to routine restraint (β = 0.08, p <.05), and routine restraint predicted to nicotine vaping (β = 0.12, p <.05).
UNASSIGNED: Results indicated that nicotine vaping predicted MEBs; however, the type of MEB differed across waves, which may have been due to the COVID-19 pandemic context. Nicotine vaping predicted to MEBs reflecting vulnerability to the external environment and emotion regulation during a period of heightened restrictions, whereas later when pandemic restrictions had ceased nicotine vaping predicted only to routine restraint. Integrating research and practice on nicotine vaping and MEBs may inform public health efforts to decrease co-occurring health-risks in young adulthood.

BACKGROUND: Despite high rates of young adult e-cigarette use, research informing cessation interventions for this population, including those unready to quit, is limited.
METHODS: We analyzed 2022 cross-sectional survey data (from a larger longitudinal study) among 172 US young adult, past-month e-cigarette users (mean age=26.95 years; 57.6% female; 73.3% White). We examined: 1) perceived challenges to quitting e-cigarettes; 2) perceived impact of intervention messages targeting motivation and confidence, and their associations with quitting importance and confidence; and 3) poly-use with cigarettes and/or cannabis in relation to poly-product cessation preferences.
RESULTS: In all, 43.6% reported past-year e-cigarette quit attempts, and 55.3% reported quit readiness; 30.2% reported past-month poly-use with cigarettes, and 54.1% with cannabis. Frequently endorsed challenges to quitting/cutting down were related to stress/anxiety (41.9%), delaying cessation attempts (35.5%), and boredom (25.6%). Messages targeting motivation perceived as most impactful (scale: 1 = \'no impact at all\' to 7 = \'a lot of impact\') were related to saving money (mean score=4.78), improving health (mean score=4.15), and avoiding toxic chemicals (mean score=4.04), messages targeting confidence perceived as most impactful were related to patience (mean score=4.47), staying busy (mean score=4.27), and soliciting support (mean score=3.84). Perceiving greater impact of messages targeting motivation was associated with greater quitting importance (B=1.16; 95% CI: 0.71-1.60, p<0.001). Neither perceived impact of messages targeting motivation nor confidence were related to quitting confidence. E-cigarette-cannabis poly-users preferred to quit cigarettes first, e-cigarette-cigarette users preferred to quit cannabis first, and poly-users of all three products preferred to quit e-cigarettes first, followed by cigarettes, then cannabis.
CONCLUSIONS: E-cigarette cessation interventions must use relevant messages (e.g. target financial and health benefits of quitting) and consider poly-users\' preferences for quitting.