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The study aimed to assess the perception of a higher risk of COVID-19 infection among young people who used e-cigarettes, and its association with a change in the use of e-cigarettes during the pandemic in Nigeria. A secondary analysis of the Nigerian component of a multi-country online survey data, which was obtained from adolescents and young adults on e-cigarette use from November 1st to December 30th, 2021, was conducted. Multi-nominal regression analyses were done to determine the associations between the dependent (use of e-cigarettes) and independent (perception that e-cigarette users are more likely to be infected with COVID-19) variables after adjusting for confounders (health status, COVID-19 status, HIV status, anxiety level, age and sex). Of the 568 respondents (52.8% male), 122 (21.5%) perceived that e-cigarette users were more likely to be infected with COVID-19. In addition, 188 (33.1%) respondents increased e-cigarette smoking during the pandemic. A greater percentage of participants who perceived that e-cigarette use is associated with a greater risk of COVID-19 infection, and a significantly higher percentage of participants with high levels of anxiety reported decreased e-cigarette use (28.6% versus 13.3%, p = 0.029). The perception that e-cigarette use increased the risk for COVID-19 was associated with higher odds of an increase in e-cigarette use (AOR: 1.328) and lower odds of a decrease in e-cigarette use (AOR: 0.580) during the COVID-19 pandemic, though these associations were not statistically significant. The persistence of e-cigarette use among the youth in Nigeria despite awareness of COVID-19 risks highlights the need for stronger public health interventions. Simply providing information on risks is insufficient; targeted strategies addressing addiction, social factors, and accessibility are crucial for meaningful behavioural change. [ABSTRACT FROM AUTHOR]

Objectives: In this study, we aimed to investigate (1) the association of tobacco and e-cigarette use with sexual orientation (LGBTQ and heterosexual individuals) and (2) the difference in the association of tobacco and e-cigarette use with self-reported depression by sexual orientation. Methods: The data for this study were obtained from the Health Information National Trends Survey (HINTS 5, Cycle 4). Sample participants included 3583 adults (93.87% heterosexuals). We used multinomial regression to measure the relative risk ratios (RRRs) of being a former and current user versus never a user of tobacco and e-cigarettes and binomial regression to measure the odds ratios of depression between the LGBTQ and heterosexuals. Results: Current smoking prevalence is higher among LGBTQ participants (17.3%) compared to heterosexuals (11.0%). The disparity is even greater for e-cigarette use, with 7.3% of LGBTQ participants being current users versus 2.8% of heterosexuals and 24.5% of LGBTQ participants being former users compared to 9.3% of heterosexuals. Compared to heterosexuals, the relative risk ratio of being a current tobacco user among the LGBTQ participants was about 1.75 times higher [RRR = 1.75, 95%CI = 1.16, 2.64], and that of e-cigarette use was about 2.8 times higher [RRR = 2.81, 95%CI = 1.57, 5.05]. Among current e-cigarette users, heterosexual participants had 1.9 percentage points [risk difference = 1.94, 95%CI = 1.20, 3.13] higher probability of depression, whereas among the LGBTQ participants, the risk was about 3.7 times higher [OR = 3.67, 95%CI = 1.06, 12.74]. Conclusions: Our findings conclude that the LGBTQ are more likely to use tobacco and e-cigarettes compared to heterosexuals and that the risk of depression from e-cigarette smoking is more pronounced among the LGBTQ participants. [ABSTRACT FROM AUTHOR]

PURPOSE: Unhealthy lifestyle behaviors are associated with inferior health outcomes among cancer survivors, including increased mortality. It is crucial to identify vulnerable subgroups, yet investigations have been limited. Thus, this study aimed to examine sociodemographic and clinical characteristics associated with risky health behaviors among cancer survivors. METHODS: We used national, cross-sectional survey data (Health Information National Trends Survey, HINTS 2017-2020) for 2579 cancer survivors. We calculated the prevalence of risky alcohol use, current cigarette smoking, e-cigarette use, and not meeting physical activity guidelines. We performed weighted logistic regression to obtain multivariable-adjusted odds ratios (OR) for the association between each unhealthy behavior with sociodemographic and clinical characteristics. RESULTS: Overall, 25% showed risky alcohol use, 12% were current cigarette smokers, 3% were current e-cigarette users, and 68% did not meet physical activity guidelines. Cancer survivors who were males, non-Hispanic Whites or African Americans, without a college education, not married and with comorbidities or psychological distress were more likely to have unhealthy behaviors. Those with lung disease or depression were 2 times as likely to smoke cigarette or e-cigarettes and those with psychological distress were 1.6 times as likely to be physically inactive. Moreover, risky drinkers (OR = 1.75, 95% CI = 1.22-2.52) and e-cigarette smokers (OR = 16.40, 95% CI 3.29-81.89) were more likely to be current cigarette smokers. CONCLUSIONS: We identified vulnerable subpopulations of cancer survivors with multiple unhealthy lifestyle behaviors. IMPLICATIONS FOR CANCER SURVIVORS: Our findings inform clinicians and program and policy makers of the subgroups of cancer survivors to target for multiple health behavior interventions.

Abstract 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. Method 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. Conclusion 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. Clinical trial registration This study is registered through ClinicalTrials.gov. The trial registration number is NCT05140915. The trial registration date is 11/18/2021.

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. [ABSTRACT FROM AUTHOR]

This study examines the effectiveness of distance-framed narratives in deterring e-cigarette use among young adults. Through an online experiment (N = 916), this study investigates how narratives with different distance cues influence participants' narrative engagement, perceived psychological distance, and compliance with the message. The findings suggest that distance-framed narratives heighten identification. Increased identification reduces perceived psychological distance, leading to more negative attitudes, decreased e-cigarette use intention, and stronger policy support. E-cigarette use status also impacts persuasive outcomes. Non-users tend to be more receptive to narratives featuring congruent distance cues in character and scenario depictions. Users are motivated by narratives that present an uncertain scenario, regardless of whether the character is portrayed as socially close or distant. [ABSTRACT FROM AUTHOR]

The prevalence of e‐cigarette use among young adults in the USA is high (14%). Although the majority of users plan to quit vaping, the motivation to make a quit attempt is low and available support during a quit attempt is limited. Using wearable sensors to collect physiological data (eg, heart rate) holds promise for capturing the right timing to deliver intervention messages. This study aims to fill the current knowledge gap by proposing statistical methods to (1) de‐noise beat‐to‐beat interval (BBI) data from smartwatches worn by 12 young adult regular e‐cigarette users for 7 days; and (2) summarize the de‐noised data by event and control segments. We also conducted a comprehensive review of conventional methods for summarizing heart rate variability (HRV) and compared their performance with the proposed method. The results show that the proposed singular spectrum analysis (SSA) can effectively de‐noise the highly variable BBI data, as well as quantify the proportion of total variation extracted. Compared to existing HRV methods, the proposed second order polynomial model yields the highest area under the curve (AUC) value of 0.76 and offers better interpretability. The findings also indicate that the average heart rate before vaping is higher and there is an increasing trend in the heart rate before the vaping event. Importantly, the development of increasing heart rate observed in this study implies that there may be time to intervene as this physiological signal emerges. This finding, if replicated in a larger scale study, may inform optimal timings for delivering messages in future intervention. [ABSTRACT FROM AUTHOR]

Objective: Tobacco use is elevated among individuals with eating disorders (EDs). Yet, further research is needed to understand associations between cigarette and e-cigarette use patterns and ED symptomatology. To gain a more comprehensive understanding of tobacco use and EDs, this study characterized ED symptomatology and tobacco use patterns, including exclusive cigarette use, e-cigarette use, dual use, and nonuse. Method: Young adults aged 18-24 years who self-reported exclusive cigarette, e-cigarette, dual, or nonuse (N = 2500) were recruited via Lucid, an online survey management company. Participants completed questionnaires assessing body dissatisfaction, global ED psychopathology, binge eating and self-induced vomiting frequency, and demographics. ED diagnostic groups included: anorexia nervosa (AN), bulimia spectrum eating disorders (BSED), atypical AN, and night eating syndrome (NES). Results: Multinomial logistic models revealed those with AN were more likely to be dual users, those with atypical AN were more likely to be exclusive e-cigarette users, and participants with a BSED or NES were more likely to be exclusive e-cigarette or dual users, compared to those without an ED. General linear models suggested body dissatisfaction and global ED psychopathology were higher among exclusive e-cigarette and dual users, while binge eating and self-induced vomiting frequencies were greater among all tobacco use groups compared to nonusers. Discussion: Our findings suggest young adults with ED symptomatology were more likely to be users of e-cigarettes exclusively or dual users. It will be necessary to examine how these associations manifest using longitudinal and clinical populations in future research. [ABSTRACT FROM AUTHOR]

Abstract 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

Background: Youth vaping is a public health concern in Canada. However, there is a dearth of evaluation data for school-based vaping prevention programs in Canada. This pilot study assessed short-term changes in knowledge, subjective norms, and intentions to vape among a sample of high school students in Ontario, Canada exposed to the ‘CATCH My Breath’ (CMB) vaping prevention curriculum. Methods: A convenience sample of 10 high schools across Ontario delivered CMB lessons between October 2022 and April 2023. Students completed an online survey before being exposed to CMB and 4-weeks after the lessons. McNemar’s Chi-square exact tests of paired proportions assessed significant changes in knowledge, subjective norms, and intentions to vape before/after exposure to the curriculum among n = 116 students who could be linked over time. Results: After exposure to CMB, students exhibited a significant increase in their knowledge: pre-test scores averaged 5.5 and post-test scores averaged 7.5. At post-test, significantly fewer students thought that most people in high school vape. There were no significant changes in intentions to vape and pre/post changes were similar for boys and girls. Discussion: After exposure to CMB, high school students in Ontario demonstrated significant increases in knowledge of the risks of vaping and modest reductions in perceptions of subjective norms of vaping. CMB has been adapted for use in high schools in Canada, and implementing this program could help to reduce youth vaping.

IntroductionSince 2016, California has implemented a series of policies, including prohibiting the sale of tobacco products and electronic cigarettes (e-cigarettes) to persons under 21, cigarette tax increase, and recreational marijuana legalization. The study aims to examine the use of cigarettes, e-cigarettes, and marijuana among young adults (ages 18-25) and their associations with other factors in the context of these policy changes.MethodsWe used the data from the California Health Interview Survey (CHIS) 2017-2018 to compare the rates of using cigarettes, e-cigarettes, and marijuana separately or any use of the three. Using CHIS 2018 data, weighted logistic regression models were used to examine associations of using cigarettes, e-cigarettes, and marijuana separately or any use of these products/substance with demo-socioeconomic factors, psychological distress, and use of each product/substances.ResultsCigarette smoking remained flat while the use of e-cigarettes and marijuana escalated among young adults from 2017 to 2018. Using tobacco products increased the use of marijuana or vice versa among young adults. Severe psychological distress was significantly associated with cigarette use (adjusted odds ratio [AOR] = 4.06; 95% CI = 1.32, 12.55), marijuana use (AOR = 2.32; 95% CI = 1.10, 4.48), and any use (AOR = 4.11; 95% CI = 1.93, 8.77). Moderate psychological distress was also significantly associated with the use of these products/substance. Underage (ages 18-20) young adults had lower odds of using cigarettes than other young adults (ages 21-25).ConclusionsOur findings highlight the importance of addressing the use of cigarettes, e-cigarettes, and marijuana simultaneously through policies to curtail tobacco and marijuana use among young adults.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Explore the factors associated with the changes in smoking and electronic cigarette (e-cigarette) use and susceptibility among adolescents during the COVID-19 pandemic. We surveyed a cohort of students (7th–12th grade) from private schools in Guatemala. Baseline (May–September 2019) was conducted in-person and follow-up (June–November 2020) online during the lockdown. Separate Generalized Estimating Equations logistic models regressed current smoking (n = 3,729), current e-cigarette use (n = 3,729), smoking susceptibility among never-smokers (n = 2,596), and susceptibility to e-cigarette use among never-users (n = 1,597) on online ad exposure, visiting stores, social network smoking/e-cigarette use, substance use (alcohol, marihuana, and cigarette or e-cigarette), perceived harm of using cigarettes/e-cigarettes, sociodemographic characteristics, and survey wave. Interactions were assessed between time and ad exposures, friends smoking and e-cigarette use. Frequency of store visits, exposure to online ads, and the use of cigarette and e-cigarette lowered at follow-up. Online e-cigarette ads, having family and friends who smoke, and current e-cigarette use increased the likelihood of being a current smoker. Frequent exposure to online e-cigarette ads, having family who use e-cigarettes, and being a current smoker were associated with higher likelihood of current e-cigarette use. Exposure to either online ads or having friends that smoke or use e-cigarettes, increased susceptibility to using either product. Interaction results showed that high exposure to online e-cigarette ads overtime increased the susceptibility to use e-cigarettes. Exposure to online ads and friends and family cigarette and e-cigarette use increased adolescent consumption and susceptibility during the pandemic. [ABSTRACT FROM AUTHOR]

Studies on the association between e-cigarette use and mental health are mostly among adolescents and young adults, leaving limited evidence of this association among general US adults. Besides, few studies have examined how e-cigarette use or dual use of e-cigarette and combustible cigarette is related to cognitive function. Cross-sectional data of 56,734 adults from the 2020–2021 National Health Interview Survey were analyzed. Weighted multivariable logistic regression models were applied to examine the independent association between e-cigarette use or dual use and anxiety symptoms, depression symptoms, serious psychological distress (SPD), and cognitive impairment. Compared with never e-cigarette users, current e-cigarette users had 2.10-fold (95 % CI: 1.84, 2.39), 2.53-fold (95 % CI: 2.13, 3.00), 2.02-fold (95 % CI: 1.47, 2.76), and 2.00-fold (95 % CI: 1.47, 2.72) higher odds of reporting anxiety symptoms, depression symptoms, SPD, and cognitive impairment, respectively. Former e-cigarette use was also associated with all three mental conditions and cognitive impairment (AOR ranged from 1.38 to 2.53, all P < 0.01). Dual users were more likely to report all three mental conditions and cognitive impairment than those who never used combustible cigarette and e-cigarette (AOR ranged from 1.89 to 2.83, all P < 0.01). Dual users also had a greater likelihood of having anxiety or depression symptoms than exclusive combustible cigarette users (AOR ranged from 1.46 to 1.47, all P < 0.01). E-cigarette use or dual use is associated with poor mental health and cognitive impairment among US adults. Regulations on e-cigarette use are needed to prevent mental illness and improve cognitive function. • Current or former e-cigarette use was significantly associated with mental conditions including anxiety symptoms, depression symptoms, and serious psychological distress among overall US adults. • Current or former e-cigarette users were more likely to report cognitive impairment than never e-cigarette users. • Dual users had significantly higher odds of having all three mental conditions and cognitive impairment than never smokers. • Dual users were also more likely to report symptoms of anxiety or depression than exclusive combustible cigarette users. • The magnitude of the association between e-cigarette use and anxiety, depression, or cognitive impairment differs by sex groups. [ABSTRACT FROM AUTHOR]

Introduction: Research characterizing substance use disparities between gender minority youth (GMY) and non-GMY (i.e. girls and boys) is limited. The aim of this study was to examine the differences in substance use behaviours among gender identity (GI) groups and identify associated risk and protective factors. Methods: Cross-sectional data from Canadian secondary school students (n = 42 107) that participated in Year 8 (2019/20) or Year 9 (2020/21) of the COMPASS study were used. Hierarchal logistic regression models estimated current substance use (cigarettes, e-cigarettes, binge drinking, cannabis and nonmedical prescription opioids [NMPOs]). Predictor variables included sociodemographics, other substances, mental health outcomes, school connectedness, bullying and happy home life. Interaction terms were used to test mental health measures as moderators in the association between GI and substance use. Results: Compared to non-GMY, GMY reported a higher prevalence for all substance use outcomes. In the adjusted analyses, GMY had higher odds of cigarette, cannabis and NMPO use and lower odds for e-cigarette use relative to non-GMY. The likelihood of using any given substance was higher among individuals who were involved with other substances. School connectedness and happy home life had a protective effect for all substances except binge drinking. Bullying victimization was associated with greater odds of cigarette, e-cigarette use and NMPOs. Significant interactions between GI and all mental health measures were detected. Conclusion: Findings highlight the importance of collecting a GI measure in youth population surveys and prioritizing GMY in substance use-related prevention, treatment and harm reduction programs. Future studies should investigate the effects of GI status on substance use onset and progression among Canadian adolescents over time. [ABSTRACT FROM AUTHOR]

INTRODUCTION 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 polyproduct 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. [ABSTRACT FROM AUTHOR]

BACKGROUND: The rising prevalence of electronic cigarette (e-cigarette) and hookah use among youth raises questions about medical trainees' views of these products. We aimed to investigate medical trainees' knowledge and attitudes toward e-cigarette and hookah use. METHODS: We used data from a large cross-sectional survey of medical trainees in Brazil, the United States, and India. We investigated demographic and mental health aspects, history of e-cigarettes and tobacco use, knowledge and attitudes toward e-cigarettes and hookah, and sources of information on e-cigarettes and hookah. Although all medical trainees were eligible for the original study, only senior students and physicians-in-training were included in the present analysis. RESULTS: Of 2,036 senior students and physicians-in-training, 27.4% believed e-cigarette use to be less harmful than tobacco smoking. As for hookah use, 14.9% believed it posed a lower risk than cigarettes. More than a third of trainees did not acknowledge the risks of passive e-cigarette use (42.9%) or hookah smoking (35.1%). Also, 32.4% endorsed e-cigarettes to quit smoking, whereas 22.5% felt ill equipped to discuss these tobacco products with patients. Fewer than half recalled attending lectures on these topics, and their most common sources of information were social media (54.5%), Google (40.8%), and friends and relatives (40.3%). CONCLUSIONS: Medical trainees often reported incorrect or biased perceptions of e-cigarettes and hookah, resorted to unreliable sources of information, and lacked the confidence to discuss the topic with patients. An expanded curriculum emphasis on e-cigarette and hookah use might be necessary because failing to address these educational gaps could risk years of efforts against smoking normalization. [ABSTRACT FROM AUTHOR]

Background: 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. Methods: 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. Results: 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

Abstract Background Marketing and sales of e-cigarettes are unregulated in Malaysia. We analyzed content displayed on e-cigarette retailer websites to identify marketing claims, promotional strategies, and product details in the year 2022. Methods We analyzed 30 Malaysia-based retailer websites using a mixed methods approach. Data were extracted as the frequency of occurrences of marketing claims, presence of regulatory information, product types, and flavors of e-juice as per a predefined codebook based on published literature. We also extracted textual details published on the websites about marketing claims, and slogans. Results Most retailer websites provided contact information and physical store addresses (83%) but only half had ‘click through’ age verification (57%) that seldom needed any identification proof for age (3%). Marketing claims were related to health (47%), smoking cessation (37%), and modernity/trend (37%) and none had health warnings. Promotional strategies were discounts (80%). starter kits (57%) and email subscriptions (53%). Product types displayed were rechargeable (97%) and disposable (87%) devices and e-liquids (90%) of an array of flavors (> 100). Nicotine presence, its concentration, and “nicotine is an addictive chemical” were displayed in 93%, 53%, and 23% of websites respectively. Conclusion Surveillance of content displayed online on e-cigarette retailer websites and regulation of online marketing and sales should be implemented by the Ministry of Health, Malaysia. Such measures are needed to prevent access to, and initiation of e-cigarette use among the youth and adults who do not smoke.

To examine the associations between e-cigarette use or dual (e-cigarette and combustible cigarette) use and short sleep duration and trouble sleeping among U.S. adults. We used 2015–2018 data from the National Health and Nutrition Examination Survey (NHANES) (n = 11,659). E-cigarette use and dual use were categorized as current, former, and never use. Short sleep duration was defined as sleep duration ≤6 h. Trouble sleeping was self-reported. Weighted logistic regression analyses were performed. Among those with current e-cigarette use, 53.9 % were with current dual use and 23.8 % were with former dual use. Compared to never e-cigarette use, current e-cigarette use was associated with significantly higher odds of trouble sleeping (OR = 2.16, 95 % CI: 1.49–3.13), adjusting for potential confounders. Significant associations were also observed for former e-cigarette use versus never use with trouble sleeping (OR = 1.54, 95 % CI: 1.15–2.07) after full adjustment. Current cigarette use was associated with both short sleep duration (OR = 1.65, 95 % CI: 1.28–2.14) and trouble sleeping (OR = 1.36, 95 % CI: 1.03–1.79) after full adjustment. Additionally, the fully adjusted ORs for short sleep duration and trouble sleeping were 1.64 (95 % CI: 1.06–2.54) and 2.14 (95 % CI: 1.34–3.42) among those with current dual use, and 1.46 (95 % CI: 1.17–1.81) and 2.11 (95 % CI: 1.66–2.67) among those with former dual use, compared to those without dual use. Current cigarette use or dual use is associated with significantly higher odds of short sleep duration and trouble sleeping. Moreover, former e-cigarette use or dual use is associated with increased odds of trouble sleeping. [Display omitted] • Current cigarette use and dual use (combustible & e-cigarette) are linked to short sleep duration and trouble sleeping. • E-cigarette use was significantly associated with higher odds of users complaining of trouble sleeping, after adjustment. • Future longitudinal studies are needed to examine the effects of cigarette/e-cigarette cessation on sleep health. [ABSTRACT FROM AUTHOR]

Introduction: To address gaps in existing research, the current study used a mixed‐methods approach to describe, contextualise and understand harm perceptions of vaping nicotine relative to cigarette smoking and associations with nicotine and tobacco (NT) use among young adults who identify their genders and sexualities in ways that classify them as sexual and gender minorities (SGM). Methods: Results are based on cross‐sectional surveys and online qualitative interviews with 98 SGM young adults (18–25 years old) in California's San Francisco Bay Area who currently or formerly used combustible tobacco. We generated a measure assessing participants' relative harm perceptions of e‐cigarette use versus cigarette smoking and identified those who perceived cigarette smoking as more harmful than e‐cigarette use compared to those who perceived it to be equally or less harmful. Results: We found that relative harm perceptions of cigarette smoking versus e‐cigarette use are likely related to much uncertainty and confusion about the harms of e‐cigarette use. Moreover, findings illustrate that public health messages regarding the risks of e‐cigarette use may have unintended consequences of increasing cigarette use to replace e‐cigarette use for some SGM young adults, a practice that is incongruent with scientific evidence demonstrating that cigarettes and other combustible tobacco products are riskier than e‐cigarettes and other forms of NT use. Discussion and Conclusions: Results suggest the need for evidence‐based, clear, and direct messaging about the relative harms of cigarettes versus e‐cigarettes to reduce NT‐related inequities in SGM populations. [ABSTRACT FROM AUTHOR]

Background: Marketing and sales of e-cigarettes are unregulated in Malaysia. We analyzed content displayed on e-cigarette retailer websites to identify marketing claims, promotional strategies, and product details in the year 2022. Methods: We analyzed 30 Malaysia-based retailer websites using a mixed methods approach. Data were extracted as the frequency of occurrences of marketing claims, presence of regulatory information, product types, and flavors of e-juice as per a predefined codebook based on published literature. We also extracted textual details published on the websites about marketing claims, and slogans. Results: Most retailer websites provided contact information and physical store addresses (83%) but only half had 'click through' age verification (57%) that seldom needed any identification proof for age (3%). Marketing claims were related to health (47%), smoking cessation (37%), and modernity/trend (37%) and none had health warnings. Promotional strategies were discounts (80%). starter kits (57%) and email subscriptions (53%). Product types displayed were rechargeable (97%) and disposable (87%) devices and e-liquids (90%) of an array of flavors (> 100). Nicotine presence, its concentration, and "nicotine is an addictive chemical" were displayed in 93%, 53%, and 23% of websites respectively. Conclusion: Surveillance of content displayed online on e-cigarette retailer websites and regulation of online marketing and sales should be implemented by the Ministry of Health, Malaysia. Such measures are needed to prevent access to, and initiation of e-cigarette use among the youth and adults who do not smoke. [ABSTRACT FROM AUTHOR]

Aims: The aims of this study were to measure whether household bans on vaping were associated with lower odds of youth past‐month vaping when compared with (1) otherwise similar youth whose households did not have a vaping ban (using coarsened exact matching); and (2) themselves in waves when their household did not have a ban (using hybrid panel models). We used the same analytical strategies to examine cross‐sectional associations between household smoking bans and adolescents' past‐month cigarette smoking. Design: This was a longitudinal study using data from a nationally representative sample of youth (age 12–17 years) in the Population Assessment of Tobacco and Health Study. Setting: United States of America. Participants: A total of 16 214 adolescents followed over 48 103 total observations (approximately three waves). Measurements Measurements comprised youth past‐month e‐cigarette and cigarette use and parent‐reported household bans on vaping and smoking. Potential confounders were prior adolescent smoking, vaping, and other nicotine product use; parent current smoking, vaping, and other nicotine use; adolescent peer e‐cigarette/cigarette use; parental monitoring; and demographic characteristics. Findings Before matching, smoking bans were associated with 46% lower odds of youth smoking [odds ratio (OR) = 0.54; 95% confidence interval (CI) = 0.41–0.70] and vaping bans with 37% lower odds of youth e‐cigarette use (OR = 0.63; 95% CI = 0.50–0.80). However, households with and without bans differed significantly on all confounders before matching. After matching, household vaping bans were associated with 56% lower odds of youth vaping (OR = 0.44; 95% CI = 0.33–0.58). Results from hybrid panel models also revealed 37% lower odds of vaping in waves when youth lived in a vape‐free household compared to waves when they did not (OR = 0.63; 95% CI = 0.50–0.78). Associations between smoking bans and youth smoking were not statistically significant after matching or when using hybrid panel models. Conclusions: Household vaping bans appear to be associated with lower odds of past‐month vaping among US adolescents, compared with similar youth whose households did not have a ban and to themselves in waves when their households did not have a ban. [ABSTRACT FROM AUTHOR]

Background and Aims: It is unknown whether young adults who vape nicotine and have poor mental health have greater risk of smoking initiation than expected based on individual risks of vaping and mental health alone. This study aimed to estimate the joint association of vaping and mental health symptoms with smoking initiation among young adults, and test for additive interaction between vaping and mental health in smoking initiation risk. Design: Using five waves of the Population Assessment of Tobacco and Health (wave 1, 2013–2014; wave 2, 2014–2015; wave 3, 2015–2016; wave 4, 2016–2018; wave 5, 2018–2019), we estimated risk differences (RD) for the association of time‐varying and time‐lagged vaping and internalizing (e.g., anxiety, depressive) and externalizing (e.g., inattention/hyperactivity) mental health symptoms with cigarette smoking initiation at follow‐up, over four 1‐year intervals. We calculated interaction contrasts (IC) to estimate the excess risk of smoking initiation attributable to the interaction of vaping and mental health symptoms. Setting: United States. Participants: A total of 6908 cigarette‐naïve individuals aged 18–24 years. Measurements Exposures included current (past‐30 day) vaping and internalizing and externalizing mental health symptoms (high vs moderate/low symptoms). The outcome was smoking initiation (ever cigarette use) after 1 year. Findings The per‐interval risk of smoking initiation was 7.6% (1039 cases/13 712 person‐intervals). Compared with noncurrent vaping and moderate/low mental health symptoms, adjusted RDs for current vaping and high mental health symptoms were 17.2% (95% confidence interval [CI]: 7.2% to 27.3%) for internalizing and 18.7% (95%CI: 8.1% to 29.2%) for externalizing symptoms. The excess risk attributed to interaction of current vaping and high externalizing symptoms was IC = 11.3% (95%CI: 1.3% to 21.2%; P = 0.018), with inconclusive findings for internalizing symptoms (IC = 7.7% [95%CI: −2.2% to 17.7%; P = 0.097]). Conclusions: There is possible, but inconclusive, superadditivity between vaping and mental health in risk of smoking initiation among young adults in the United States. [ABSTRACT FROM AUTHOR]

Purpose: Unhealthy lifestyle behaviors are associated with inferior health outcomes among cancer survivors, including increased mortality. It is crucial to identify vulnerable subgroups, yet investigations have been limited. Thus, this study aimed to examine sociodemographic and clinical characteristics associated with risky health behaviors among cancer survivors. Methods: We used national, cross-sectional survey data (Health Information National Trends Survey, HINTS 2017–2020) for 2579 cancer survivors. We calculated the prevalence of risky alcohol use, current cigarette smoking, e-cigarette use, and not meeting physical activity guidelines. We performed weighted logistic regression to obtain multivariable-adjusted odds ratios (OR) for the association between each unhealthy behavior with sociodemographic and clinical characteristics. Results: Overall, 25% showed risky alcohol use, 12% were current cigarette smokers, 3% were current e-cigarette users, and 68% did not meet physical activity guidelines. Cancer survivors who were males, non-Hispanic Whites or African Americans, without a college education, not married and with comorbidities or psychological distress were more likely to have unhealthy behaviors. Those with lung disease or depression were 2 times as likely to smoke cigarette or e-cigarettes and those with psychological distress were 1.6 times as likely to be physically inactive. Moreover, risky drinkers (OR = 1.75, 95% CI = 1.22–2.52) and e-cigarette smokers (OR = 16.40, 95% CI 3.29–81.89) were more likely to be current cigarette smokers. Conclusions: We identified vulnerable subpopulations of cancer survivors with multiple unhealthy lifestyle behaviors. Implications for Cancer Survivors: Our findings inform clinicians and program and policy makers of the subgroups of cancer survivors to target for multiple health behavior interventions. [ABSTRACT FROM AUTHOR]

Abstract Background This study explores the association between psychosocial stressors and current e-cigarette use among adolescents in the United States. Methods We used data from 12,767 participants in the 2019 National Youth Risk Behavioral Survey to examine the association between psychosocial stressors (bullying, sexual assault, safety-related absence from school, depressive symptoms, suicidal ideation, physical altercation, and weapon threats) and past-30-day e-cigarette use using multivariable-adjusted logistic regression models. We examined the association for each stressor and then as a burden score (0–7). To compare the strength of the association between stressors and current e-cigarette use to current combustible cigarette use, we additionally examined the association between each stressor and current combustible cigarette use. Results Approximately 32.7% reported current e-cigarette use. The weighted prevalence of current e-cigarette use was higher among individuals who experienced stressors than those who did not. For example, bullying (43.9% vs. 29.0%). Similar prevalence patterns were seen among other stressors. Individuals who experienced stressors had significantly higher adjusted odds of current e-cigarette use than those who did not (OR [Odds Ratio] range: 1.47–1.75). Similarly, individuals with higher burden scores had a higher prevalence (zero [20.5%], one [32.8%], two [41.4%], three [49.6%], four to seven [60.9%]) and higher odds of current e-cigarette use (OR range: 1.43–2.73) than those with a score of zero. The strength of the association between the stressors and e-cigarette use was similar to that between the stressors and combustible cigarette use. Conclusion The study demonstrates a significant association between psychosocial stressors and adolescent e-cigarette use, highlighting the potential importance of interventions, such as targeted school-based programs that address stressors and promote stress management, as possible means of reducing adolescent e-cigarette use. Future research directions include exploring underlying mechanisms linking stressors to e-cigarette use and evaluating the effectiveness of interventions addressing stressors in reducing adolescent e-cigarette use.

This observational study examines the association of current e-cigarette use and dual use of e-cigarettes and cigarettes (dual use) with psychological distress among U.S. adults. We differentiate dual use based on the smoking frequency and compare the relationship between dual use and psychological distress to that of exclusive cigarette smoking with the same smoking frequency.Using data from the 2015–2018 National Health Interview Surveys, we analyzed adults aged 18+ (N = 55,780) who currently use e-cigarettes or/and cigarettes and have no history of using other tobacco products, and adults who never used any tobacco. Multinomial logistic regression models estimate the association of current e-cigarette use and dual use with psychological distress severity (no/mild, moderate, and severe).In the sample, 15.3% and 2.9% of adults experienced moderate and severe psychological distress. Compared to never tobacco users, current exclusive e-cigarette users and dual users who smoke daily had higher odds of moderate and severe psychological distress. Dual users who smoke nondaily had higher odds of moderate, but not severe psychological distress than never tobacco users. Compared to exclusive daily smokers, dual users with daily smoking had higher odds of moderate and severe psychological distress. Compared to exclusive nondaily smokers, dual users with nondaily smoking had higher odds of moderate but not severe psychological distress.Our findings suggest that exclusive e-cigarette use is associated with psychological distress severity. Dual use is associated with higher odds of psychological distress severity compared to never tobacco users and exclusive cigarette smoking, and this association differs by smoking frequency.

The use of e-cigarette among Korean adolescents is spreading with alarming rapidity, but it has not been studied along with the severity level of GAD-7. This study aims to identify adolescents' e-cigarette use and its associated factors among four different anxiety groups using the problem behavioral theory (PBT). A cross-sectional secondary dataset was retrieved from the 2020 Korea Youth Risk Behavior Survey. Of the total sample of 54,948, four anxiety groups were formed: minimal (score 0–4; n = 36,711), mild (score 5–9; n = 12,138), moderate (score 10–14; n = 4143), and severe (score above 15; n = 1965). A total of 11 variables were selected based on the PBT domains. Descriptive analysis, Chi-square, ANOVA, univariate analysis, and multiple linear regression analysis were performed. E-cigarette use was the highest in the order of severe, mild, moderate, and minimal. While cigarette use was associated with vaping in all anxiety groups, adolescents with minimal or mild anxiety levels were more likely to be influenced by tobacco accessibility and other behavior system factors such as sexual intercourse, alcohol use, and smartphone addiction. Meanwhile, secondhand smoke exposure in public areas was only associated with those with severe anxiety levels, and secondhand smoke exposure at school was a significant factor in all anxiety groups except for those with moderate anxiety levels. Due to the nature of cross-sectional dataset, the study could not draw causal links between vaping and other identified factors, include all the necessary PBT components. These findings underscore the need to consider different levels of anxiety when addressing the problems related to vaping among Korean adolescents. • E-cigarette usage varies by the severity level of anxiety. • Factors associated with e-cigarette use across different levels of anxiety groups were examined. • The severe anxiety group was more likely to use e-cigarette than minimal group. • Adolescents with moderate level of anxiety are more tolerant to risk factors of e-cigarette use. [ABSTRACT FROM AUTHOR]

IntroductionUsing the tenets underlying social identity theory and the theory of planned behavior, the current study compared the perceptions, attitudes, and behaviors of e-cigarette users that reported vaping as self-defining ("vapers") compared to users that denied vaping was central to their identity ("non-vapers").MethodSecondary analyses of data from the 2017-2018 California Student Tobacco Survey were utilized. A weighted, multivariable regression model (N = 82,217) compared the demographic characteristics, beliefs, and behaviors of vapers and non-vapers. A path analytic model examined whether norms and attitudes mediated the relationship between vaper identity and use behavior.ResultsSelf-identified sexual and/or gender minority youth were more likely to identify as vapers compared to heterosexual and cisgender respondents. Youth that identified as vapers viewed e-cigarette use as more normative, held more favorable attitudes (i.e., lower harm beliefs), used e-cigarettes more frequently and in greater quantities, were more likely to use fruit and mint flavored e-cigarettes, and were more likely to acquire e-cigarettes from commercial sellers (i.e., vape/tobacco shops; all p < 0.05). Additionally, descriptive norms and attitudes mediated the relationship between vaper identity and use frequency/quantity.ConclusionsDifferences in e-cigarette beliefs and behaviors were found for youth e-cigarette users that perceived vaping as self-defining versus those that did not view vaping as part of their self-concept. Future studies are needed to examine causal directionality between identity, norms, attitudes, and behavior. Tobacco control efforts might use these findings to further denormalize vaping using evidence-based media campaigns and policy implementation.

PurposeSexual minority young adults report greater cigarette and cannabis use. Emerging evidence suggests this trend may extend to e-cigarettes. The current study evaluated the relationship between sexual identity and prevalence of e-cigarette, cigarette, and cannabis use and whether such associations differ by gender.MethodsCross-sectional, regionally representative data of young adults (M[SD]age = 20.02 [0.60] years; n heterosexual = 1314; n bisexual = 77; n lesbian/gay = 28) from Wave III (2016) of the Southern California Children's Health Study were analyzed in 2019. Logistic regression analyses were conducted with sexual identity as the predictor and product use (never, prior, infrequent past 30-day [1-2 days], frequent past 30-day [3-5+ days]) as the outcome in separate models by substance (e-cigarettes, cigarettes, cannabis).ResultsBisexual individuals were the highest-risk sub-group for nearly all outcomes, with over five times the odds of reporting frequent past 30-day use for e-cigarettes (Odds Ratio [OR]: 6.68; 95% Confidence Interval [CI]: 2.80, 15.9), cigarettes (OR: 5.42; 95% CI: 2.37, 12.4), and cannabis (OR: 8.43; 95% CI: 4.40, 16.1) compared to heterosexual individuals. Although the sample size for lesbian/gay participants was small, bisexual (vs. lesbian/gay) participants also had greater odds of reporting prior use of nicotine products and frequent past 30-day cannabis use. A significant sexual identity × gender interaction emerged for lifetime cigarette use, wherein bisexual (vs. heterosexual) identity was only associated with greater odds of use for females (p

Background: Young adult sexual minoritized women (SMW) are at disproportionate risk for e-cigarette use, which may in part be due to excess minority stress imposed by discrimination exposure. While discrimination exposure is associated with risk for combustible tobacco/nicotine use among SMW, similar associations have yet to be tested with e-cigarettes. Moreover, it is unknown if discrimination-related risk may be mitigated by protective factors such as social support. This study examined concurrent associations of discrimination, perceived stress, and social support with past 30-day e-cigarette use in a sample of young adult SMW during the COVID-19 pandemic. Methods: N = 501 SMW and nonbinary people assigned female at birth (AFAB) aged 18–30 completed an online survey. A series of logistic regressions examined associations of discrimination, perceived stress, and four forms of social support received during the COVID-19 pandemic with past-30-day e-cigarette use. Results: Among SMW, greater perceived stress (OR = 1.10, p =.03), but not discrimination exposure, was associated with e-cigarette use. Associations of discrimination with e-cigarette use were nonsignificant when most forms of social support (emotional, material/financial, and virtual) were accounted for. Associations of perceived stress with e-cigarette use were strongest among those who needed but did not receive material support. Conclusions: Perceived stress, but not discrimination exposure, was associated with risk for e-cigarette use among young SMW during the COVID-19 pandemic. Effects of nonspecific stress may be compounded by insufficient material/financial support. [ABSTRACT FROM AUTHOR]

Abstract Introduction In August 2019, an outbreak of “e-cigarette or vaping product use-associated lung injury” (EVALI) prompted many states and health organizations to warn against the use of electronic cigarettes, or e-cigarettes, due to the presumed link between e-cigarette use and the illness. However, it was later shown that vitamin E acetate, a component of some illicit vaporizable THC products, was the causative agent in this outbreak. Methods We conducted a series of cross-sectional surveys of the websites of all state departments of health to determine how they communicated the risk of e-cigarette use during and after the EVALI outbreak. We then paired this analysis with data from the 2016 through 2020 Behavioral Risk Factor Surveillance System to measure changes in cigarette and e-cigarette use. Results Website data from 24 states was available for analysis at all three time points of interest, and BRFSS data was only available for 8 of these states. We found that by January 2020, a majority of the states surveyed did not list vaporizable THC use as a cause of EVALI; however, differences in state messaging did not appear to be associated with changes in e-cigarette and cigarette use. Conclusions Given the number of states that did not appear to update their messaging regarding the cause of EVALI, we believe that states should re-evaluate this messaging to accurately communicate the risks of e-cigarette use.

Abstract Background This study examines associations between psychological distress, intentions to use e-cigarettes, and cigarette smoking, e-cigarette use, and cannabis consumption through e-cigarette use among a diverse sample of U.S. young adults. Procedures Young adults (N = 314; 72.5% female) were recruited to complete an online survey during the first few months of the COVID-19 pandemic. Results Associations between psychological distress and cigarette smoking, e-cigarette use, cannabis vaping, and intentions to use e-cigarettes were found. Current e-cigarette use (OR = 1.23, 95% CI 1.17, 1.28, p

The theory of planned behaviour (TPB) is recognized as powerful predictive model to explain consumer purchase behaviour. However, there have been relatively few studies that determine the role of TPB’s constructs in e-cigarettes decision-making process. Moreover, the TPB ignores the impulsive motivation (i.e., hedonism) and unconscious motivation (i.e., habit) and perceived knowledge in the literature. This study adopted a quantitative method based on a survey with 293 young respondents using e-cigarettes. The proposed hypotheses were empirically tested with SPPS and AMOS. This study revealed that perceived knowledge positively influenced attitude, subjective norm (SN), and perceived behavioural control (PBC) respectively. The results showed a positive relationship between attitude, SN, PBC and intention, and intention positively influenced actual e-cigarettes use behaviour. The results also demonstrated how consumers’ hedonic motivation and habit influence intention. Lastly, the theoretical and practical implications and limitations were discussed.

Abstract Background Cigarette smoking, secondhand cigarette smoke (SHS) exposure, and e-cigarette use (“vaping”) are each associated with increased rates of depressive symptoms and other internalizing mental health disorders. The prevalence of vaping has increased greatly, yet the mental health correlates of secondhand exposure to e-cigarette emissions are as yet to be investigated. This study examined the potential adverse mental health outcomes associated with different tobacco exposures (direct and passive), with a particular focus on the mental health correlates of secondhand exposure to e-cigarette emissions. Methods The Population Assessment of Tobacco and Health Study data collected from a sample of 16,173 Wave 4 adults were used to test the hypothesis that secondhand e-cigarette emissions exposure is associated with increased odds of internalizing mental health disorders. Individuals were categorized as exclusive cigarette smokers, exclusive e-cigarette users, cigarette and e-cigarette dual users, exclusive noncombustible tobacco users, secondhand smoke exposed non-users, secondhand e-cigarette emissions exposed non-users, and non-users with no current SHS/secondhand e-cigarette aerosol exposure. Adjusted weighted logistic regression analysis was used to investigate the association between exposure type and internalizing problems as assessed by scores on the Global Appraisal of Individual Needs-Short Screener (GAIN-SS), a widely used instrument for assessing mental health problems. Results Cigarette smokers (AOR = 2.53, 95% CI: 2.19–2.92), e-cigarette users (AOR = 3.14, 2.41–4.09), dual users (AOR = 3.37, 2.85–4.00), noncombustible tobacco users (AOR = 1.48, 1.01–2.17), SHS exposed non-users (AOR = 1.63, 1.37–1.94), and secondhand e-cigarette emissions exposed non-users (AOR = 1.43, 1.03–1.99) were each associated with increased odds of moderate to severe internalizing mental health problems as compared to unexposed non-users. Odds of internalizing problems among SHS and secondhand e-cigarette emissions exposed non-users did not differ (p = 0.46). Conclusions This is the first study, to our knowledge, to identify an association between recent secondhand exposure to e-cigarette emissions and mental health problems, and the risk is comparable to that of SHS. Corroboration of this relationship needs further research to explicate directionality and mechanisms underlying this association.

Introduction: E-cigarettes emerged in the U.S. market in the late 2000s. In 2017, E-cigarette use among U.S. adults was 2.8%, with higher use among some population groups. Limited studies have assessed E-cigarette use among persons with diagnosed HIV. The purpose of this study is to describe the national prevalence estimates of E-cigarette use among persons with diagnosed HIV by selected sociodemographic, behavioral, and clinical characteristics. Methods: Data were collected between June 2018 and May 2019 as part of the Medical Monitoring Project, an annual cross-sectional survey that produces nationally representative estimates of behavioral and clinical characteristics of persons with diagnosed HIV in the U.S. Statistically significant differences (p

Youth vaping is a public health concern in Canada. Researchers have explored factors associated with vape use, but rarely differentiated between types of use. This study estimates the prevalence and correlations among past-month nicotine vaping, nicotine-free vaping, and dual-use vaping (nicotine and nicotine-free) in grades 9–12 high school students. Data came from the 2019 Canadian Student Tobacco, Alcohol and Drugs Survey (CSTADS). The total sample consisted of 38,229 students. We used multinomial regression to assess for the correlations among different categories of vape use. Approximately 12% of the students reported past-month vape use exclusively with nicotine, 2.8% reported exclusively nicotine-free vape use, and 14% reported both nicotine vaping and nicotine-free vaping. Substance use (smoking, alcohol, cannabis) and being male were associated with membership in every category of vape use. Age was associated with vape use, but in different directions. Grade 10 and 11 students were more likely than grade 9 students to vape exclusively with nicotine (aOR 1.36; 95% CI: 1.05, 1.77 and aOR 1.46; 95% CI: 1.09, 1.97), while grade 9 students were more likely than grade 11 and 12 students to vape with both nicotine and nicotine-free vapes (aOR 0.82; 95% CI: 0.67, 0.99 and aOR 0.49; 95% CI: 0.37, 0.64). The prevalence of nicotine and nicotine-free vaping is high, with many students reporting the use of both. [ABSTRACT FROM AUTHOR]

Objectives: This study examined the prevalence of tobacco and e-cigarette use, attitudes toward tobacco control, training on tobacco control in the dental curriculum, and attitudes toward e-cigarette use among Thai dental students. Materials and Methods: An online survey among 1968 Thai dental students was conducted in 2021. The questionnaire was modified from the Global Health Professions Student Survey with information collected on tobacco products, e-cigarette use, attitudes, and training toward tobacco control in the dental curriculum and personal information (e.g., sex, course year, regions, and types of dental schools). Descriptive analyses and χ2 tests were performed. Results: The prevalence of tobacco and e-cigarette use among Thai dental students was 4.2%. Out of current users, 95% used e-cigarettes and 36.6% used multiple products, with a 1.7% prevalence of conventional cigarettes and other forms of tobacco use. Tobacco and e-cigarette use was higher in male than female dental students and was not associated with course year, region, and type of dental school. Conclusions: A small percentage of Thai dental students used tobacco or e-cigarettes, with the majority of current tobacco users being e-cigarette users. Thai dental students generally had a favorable view of tobacco control and a negative view of e-cigarette use. However, fewer than half of the surveyed students had received training in tobacco cessation therapy. [ABSTRACT FROM AUTHOR]

• This study modified an existing, self-report measure assessing smoking for eating/weight control to include e-cigarettes. • Higher scores on this new measure were primarily observed among young adult dual users. • This new measure may be used to understand young adult motivations for using tobacco products for eating/weight control. 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. 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. 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. 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. [ABSTRACT FROM AUTHOR]

• Time to first cravings did not differ by internalizing symptoms among young people. • Time to first really needing to use did not differ by internalizing symptoms. • Time to first use within 30 min did not differ by internalizing symptoms. 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. [ABSTRACT FROM AUTHOR]

• E-cigarette use intentions clustered around cigarette cessation and/or appealing e-cigarette-related reasons. • A-priori e-cigarette intentions were unrelated to uptake or amount of use following one-month unguided provision.. • Lack of cigarette cessation-related motives for e-cigarette use might not impact uptake and long-term use patterns. 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. [ABSTRACT FROM AUTHOR]

Objectives: There are few studies describing longitudinal changes in vaping patterns among current youth e-cigarette users. The objective of this study was to identify-one-year changes in e-cigarette use patterns among a longitudinal sample of Canadian youth e-cigarette users between 2017/18 and 2018/19. Methods: The longitudinal sample included n = 4,071 current (past 30-day) e-cigarette users in grades 9–11 attending schools in four Canadian provinces. Students reported the number of days they used e-cigarettes in the past 30 days in 2017/18 and 2018/19. Based on responses, students could have escalated, reduced, stopped, or maintained their level of vaping. The prevalence of each e-cigarette use pattern was identified across demographic characteristics and regression models identified significant predictors of each use pattern. Results: Over one year, 49.2% of current youth e-cigarette users escalated, 12.8% reduced, 20.2% stopped, and 17.8% maintained their frequency of e-cigarette use. Baseline e-cigarette use frequencies varied according to use pattern. Current youth e-cigarette users with higher baseline vaping frequencies had lower odds of escalating and stopping e-cigarette use and higher odds of reducing e-cigarette use relative to maintaining the same frequency of use. Conclusions: While about half of current youth e-cigarette users increased their frequency of e-cigarette use over a 1-year period, a significant number also decreased or stopped vaping at a time when the prevalence of youth e-cigarette use increased rapidly in Canada. There is a need for longitudinal data to monitor and evaluate changes to e-cigarette use patterns that may be in response to changing public health policies.

Introduction: Since 2016, California has implemented a series of policies, including prohibiting the sale of tobacco products and electronic cigarettes (e-cigarettes) to persons under 21, cigarette tax increase, and recreational marijuana legalization. The study aims to examine the use of cigarettes, e-cigarettes, and marijuana among young adults (ages 18–25) and their associations with other factors in the context of these policy changes. Methods: We used the data from the California Health Interview Survey (CHIS) 2017–2018 to compare the rates of using cigarettes, e-cigarettes, and marijuana separately or any use of the three. Using CHIS 2018 data, weighted logistic regression models were used to examine associations of using cigarettes, e-cigarettes, and marijuana separately or any use of these products/substance with demo-socioeconomic factors, psychological distress, and use of each product/substances. Results: Cigarette smoking remained flat while the use of e-cigarettes and marijuana escalated among young adults from 2017 to 2018. Using tobacco products increased the use of marijuana or vice versa among young adults. Severe psychological distress was significantly associated with cigarette use (adjusted odds ratio [AOR] = 4.06; 95% CI = 1.32, 12.55), marijuana use (AOR = 2.32; 95% CI = 1.10, 4.48), and any use (AOR = 4.11; 95% CI = 1.93, 8.77). Moderate psychological distress was also significantly associated with the use of these products/substance. Underage (ages 18–20) young adults had lower odds of using cigarettes than other young adults (ages 21–25). Conclusions: Our findings highlight the importance of addressing the use of cigarettes, e-cigarettes, and marijuana simultaneously through policies to curtail tobacco and marijuana use among young adults.

Introduction: In August 2019, an outbreak of "e-cigarette or vaping product use-associated lung injury" (EVALI) prompted many states and health organizations to warn against the use of electronic cigarettes, or e-cigarettes, due to the presumed link between e-cigarette use and the illness. However, it was later shown that vitamin E acetate, a component of some illicit vaporizable THC products, was the causative agent in this outbreak. Methods: We conducted a series of cross-sectional surveys of the websites of all state departments of health to determine how they communicated the risk of e-cigarette use during and after the EVALI outbreak. We then paired this analysis with data from the 2016 through 2020 Behavioral Risk Factor Surveillance System to measure changes in cigarette and e-cigarette use. Results: Website data from 24 states was available for analysis at all three time points of interest, and BRFSS data was only available for 8 of these states. We found that by January 2020, a majority of the states surveyed did not list vaporizable THC use as a cause of EVALI; however, differences in state messaging did not appear to be associated with changes in e-cigarette and cigarette use. Conclusions: Given the number of states that did not appear to update their messaging regarding the cause of EVALI, we believe that states should re-evaluate this messaging to accurately communicate the risks of e-cigarette use. [ABSTRACT FROM AUTHOR]

Objective: E-cigarette use is associated with subsequent cigarette smoking among youth. The current study examined the mediating role of social-cognitive factors in this association., Methods: Data from four waves of the Population Assessment of Tobacco and Health study (2013/4 - 2017/8) were analyzed. Among youth who had heard about e-cigarettes at Wave 1 but never used cigarettes before Wave 2, we conducted both causal and traditional mediation analyses to examine the mediated effect of social-cognitive factors (including relative harm perception of e-cigarettes versus cigarettes, harm perception of e-cigarette use, perceptions of addictiveness of e-cigarette use, and e-cigarette use among best friends) in the association between e-cigarette use and subsequent cigarette ever or current smoking, adjusting for covariates. We included sampling weights in all analyses; hence, results are generalizable to the U.S. youth (12 - 14 years) from the 2013-2014 cohort., Results: Results from causal mediation analyses indicated that the total effect of e-cigarette use, compared to no use, increased the risk of cigarette ever smoking (20.9 %) and current smoking (4.6 %). A portion of this effect (4.2 % - 15.1 % for ever smoking; less than 10.6 % for current smoking) can be attributed to changes in social-cognitive factors induced by e-cigarette use. However, these mediated effects were small in magnitude relative to their standard errors and not statistically significant. Results from the traditional mediation analyses largely aligned with these findings, except for a few small sized pathways., Conclusions: For the U.S. youth population, social-cognitive factors may only minimally or not at all mediate the association between e-cigarette use and subsequent cigarette smoking. Further investigation into the mediation role of social-cognitive factors is warranted. Tobacco control interventions that focus on cigarette smoking initiation among youth should target other mediating factors., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [SX, DLC, GL, AM, and NJ report no financial or other relationship relevant to the subject of this article. RSN receives funding from the FDA CTP via contractual mechanisms with Westat and the NIH. The work presented here is independent of this funding and does not represent the views or opinions of any government institutes or agencies]., (Copyright © 2024 Elsevier Ltd. All rights reserved.)