Introduction: India is one of the few countries to have banned production, manufacture, import, export, transport, sale, distribution, storage and advertisement of electronic cigarettes (e-cigarettes). With the advent of technology, these product are being marketed extensively on internet despite the ban. Objective: To assess promotion and sales of e-cigarettes on the internet, and social networking sites (SNS); and to assess the levels of awareness regarding e-cigarettes among youth participants and the source of receiving information on e-cigarettes. Methodology: In 2022, a survey was conducted with youth (18-24 years), along with a desk review to identify influencers promoting, and e-stores selling e-cigarettes in India. Further, a content analysis was conducted on the identified influencers and online stores. Results: 370 youth with a mean age of 21.1 ± 1.7 years participated in the survey. 66.6% of participants reported being aware of e-cigarettes through social media. Instagram (46%) was identified as the most popular social networking platform for promoting e-cigarettes. 189 influencers promoting e-cigarettes on Instagram were identified and their posts positively portrayed e-cigarettes (trendy/cool, flavours, hedonic value, features cessation aid and cost-effective). Additionally, 83 e-stores (49 Indian and 34 international) were identified as selling e-cigarettes in India. Findings from content analysis of both influencers and e-stores highlighted issue of international cross-border marketing. Conclusion: To safeguard youth and achieve a path to Tobacco-free generation; there is a dire need for strengthening the monitoring and enforcement of PECA 2019, especially to address international cross-border advertisements and sales of e-cigarettes. Additionally establishing strong reporting violation mechanisms is also needed. Furthermore, educating youth, retailers, policy makers and community via sensitization programs on detrimental effects of e-cigarette use and existing policies related to e-cigarettes in India is crucial.

BackgroundSmoking cessation is linked to improved mental health that encompasses the overall well-being and psychological functioning of an individual.ObjectiveExamine relationships between smoking, mental health, and social connectedness among adults in Maryland, US in 2020.MethodologyThis cross-sectional study used data from the Maryland 2020 Behavioral Risk Factor Surveillance System Survey of adults during the onset of COVID-19. Primary outcomes measured include demographics, depression, and number of not good mental health days among individuals with current and former smoking statuses compared to those who have never smoked.ResultsCompared to those who never smoked, individuals who currently smoked had an increased relative risk of reporting 14 or more days of not good mental health (RRR = 1.63, 95% CI: 1.35-1.97, P < .001) and a history of depression (RRR = 1.99, 95% CI: 1.69-2.35, P < .001). Individuals with former smoking status also showed elevated risk, with RRR = 1.24 (95% CI: 1.06-1.45, P = .006) for 14 or more days of not good mental health and RRR = 1.46 (95% CI: 1.28-1.66, P < .001) for a history of depression. Widowed, separated, or divorced; unemployed or unable to work; without a high school diploma; or recent physical exam were inclined to have a current or former smoking status.ConclusionWe identify critical subpopulations vulnerable to life-long smoking behaviors amid the COVID-19 pandemic including adults under 35 years old, and those suffering from depression, a lack of social connectedness due to unemployment, changes in marital status, and outdated physical exams. The US Surgeon General’s 2023 Advisory on the epidemic of loneliness and the 2021 Youth Mental Health Report emphasize the mental health crises among the young in which these findings serve as a compelling call to action for innovating targeted public health interventions.

Electronic nicotine delivery systems ("e-cigarettes") are the nicotine product most commonly used by adolescents. Research, treatment, and policy could benefit from measures of adolescent e-cigarette beliefs about outcomes of use (ie, expectancies). In the current study, we developed and tested an adolescent electronic nicotine vaping expectancy measure. A focus group with adolescents evaluated potential e-cigarette expectancy items. A panel of national experts assisted in revision of these items. Finally, items were administered to a sample of adolescents 14-17years old (N = 267, Mean age 15.6, SD = 1.1, 50.9% Female, 50.2% Non-Hispanic White, 22.5% Non-Hispanic Black, 14.2% Hispanic) in a large Southeastern metropolitan area in the United States. Exploratory Factor Analysis revealed a four factor solution: Negative Consequences (Cronbach's α = .92); Positive Reinforcement (α = .83); Negative Affect Reduction (α = .95); and Weight Control (α = .89). Subscales were significantly correlated with vaping susceptibility and lifetime vaping. Subscales successfully differentiated susceptible adolescents from confirmed non-susceptible adolescents, with susceptible adolescents reporting more positive expectancies, eg, Positive Reinforcement, M = 5.0, SD = 2.0 vs M = 3.0, SD = 2.1, P < .001, η2 = 0.19, and less negative expectancies, M = 5.5, SD = 2.3 vs M = 6.5, SD = 2.6, P = .001, η2 = 0.04. Similar results were found comparing adolescents who have never vaped nicotine with those who have vaped nicotine. Hierarchical linear regression demonstrated subscales were significant predictors of lifetime vaping after controlling for demographics, vaping ad exposure, and peer/family vaping. A preliminary version of an adolescent expectancy measure appears reliable and valid based on expert input and pilot testing with adolescents. Promising results were found in the domains of concurrent validity, discriminant validity, and incremental validity. Future research and evaluation efforts will be able to use this tool to further prevention and treatment goals.

Supporting smoking cessation at pharmacies can be challenging owing to difficulties in recruiting smokers to participate in cessation programs, insufficient communication skills among pharmacists, and lack of knowledge and self-efficacy in successfully quitting smoking in Japan. This study evaluates the effectiveness of a smoking cessation training program on community pharmacists' knowledge, attitude, and self-efficacy in supporting smoking cessation. The study, conducted in Japanese pharmacies with 100 community pharmacists, employed a quasi-experimental design. Two online training programs were implemented. Participants completed a web-based survey assessing their knowledge, attitude, and self-efficacy in supporting smoking cessation before, immediately after, and 1 year after the training program. A two-way analysis of variance with a mixed model was used to examine score changes at each time point. Total knowledge scores significantly increased between baseline and immediately after training and baseline and 1year after training. The total attitude scores between baseline and immediately after training differed significantly. However, no differences were noted between baseline and 1year after training. Total self-efficacy scores significantly increased at baseline, immediately after training, and between baseline and 1year after training. Despite no significant interactions between the programs, there was a partial interaction effect on knowledge, with only the customized program having items whose knowledge levels improved after 1year. The training program improved community pharmacists' knowledge, attitude, and self-efficacy regarding smoking cessation support. The customized program must be reinforced to improve support performance and maintain attitude.

This study aimed to assess tobacco and vaping habits among university students, exploring awareness of university policies, attitudes, and behaviors related to smoking and vaping. An online questionnaire was distributed among students from various universities, including institutions in Pakistan, covering demographics, smoking and vaping behaviors, awareness of policies, and beliefs. Data was analyzed using descriptive statistics, Binomial tests, Chi-square tests, and logistic regression. Out of the total 683 respondents, 65.02% were female, and 34.98% were male. Most participants were undergraduate students (71.31%), with Dentistry being the most represented field (50.36%). Most students perceived smoking or vaping as socially acceptable (58.3%) and were aware of university policies (59.3%). However, 46.6% were aware of cessation programs. Most of the students expressed concern about long-term vaping health risks (74.5%). Logistic regression identified gender (Male) and field of study (Dentistry) as significant predictors of policy awareness. University students exhibit varied perceptions and behaviors related to smoking and vaping. The study highlights the importance of implementing effective policies and interventions to address tobacco and vaping use among them.

E-cigarettes have been shown to be effective for tobacco smoking cessation. Predicting those who are most likely to achieve smoking abstinence after receiving an e-cigarette based smoking cessation intervention could help to target interventions more efficiently. A secondary analysis of baseline characteristics of 505 people who received an emergency department based smoking cessation intervention incorporating brief advice, provision of an e-cigarette starter kit and referral to stop smoking services. Gender, ethnicity, age, employment status, deprivation, partner smoking status, cigarettes per day, motivation to quit, cigarette dependence and previous e-cigarette use were assessed as predictors of abstinence. Self-reported smoking status was collected 6 months after intervention delivery. At 6 months 169/505 (33%) of those who received the intervention self-reported abstinence. The groups that were more likely to report having quit were females (37.4% of females vs 31.0% of males), older people (41.1% of over 50s vs 33.3% of under 35s), lighter smokers (36.4% of those who smoked less than 10 cigarettes per day vs 30.7% for those who smoked over 20) and more motivated quitters (35.6% for those with high motivation vs 29.2% for those with low motivation). However, in multiple logistic regression, when adjusting for the other factors, no factors significantly predicted smoking abstinence. Degree of nicotine dependence was very similar between those who quit and those who did not. The study found no baseline factors that could predict successful smoking cessation with e-cigarettes. Consequently, this study does not support the use of a targeted e-cigarette-based smoking cessation intervention, suggesting the adoption of a more universal approach.

Biochemical verification of smoking status prior to recruitment into smoking cessation trials is widely used to confirm smoking status, most commonly using exhaled carbon monoxide (CO). There is variation in the level of CO used as a biochemical inclusion criterion, and thus the possibility for people reporting to be current smokers to be incorrectly excluded from trials. As part of the Cessation of Smoking Trial in the Emergency Department, people attending the Emergency Department (ED) who reported being current daily smokers underwent CO testing to confirm eligibility. Elective semi-structured interviews were undertaken with the researchers who recruited participants. As part of the interviews, researchers were asked their views and experiences with CO testing. Of the 1320 participants who reported being current daily smokers and underwent CO testing, 300 (22.7%) blew a CO reading of 7ppm or less and were excluded from taking part. Possible explanations offered by researchers for participants blowing low CO readings were (1) long wait times in the ED, therefore a long period having elapsed since people had last smoked and (2) patients having reduced smoking for the period before the ED attendance due to ill health. Biochemical verification has the potential to improve internal validity of smoking cessation for inclusion in trials, but at the cost of reduced generalisability through exclusion of participants who would receive the intervention if it were implemented in practice. We would recommend researchers carefully consider whether it is appropriate and necessary to include biochemical verification as an inclusion criterion.

AimsTo identify, visualize, and describe the prevalence of within-product patterns of tobacco use behaviors for e-cigarettes, cigarettes, and hookah (TP) by 3 age groups (ie, 12-14-year-old, 15-17-year-old, and 18-20-year-old) with U.S. nationally representative data.MethodsIn 2014-2015, never users of each (TP) and age group were followed-up longitudinally between 2015-2019 using five transition states: non-susceptible to (TP) use, susceptible to (TP) use, ever (TP) use, past 30-day (TP) use, and discontinued past 30-day (TP) use. Sankey diagrams were used to graphically visualize patterns in tobacco use behaviors across time.ResultsAmong 12-14-year-old who were never users and susceptible to each TP from 2014-2017, 7% initiated ever e-cigarette use and 9.4% first reported past 30-day use by 2018-2019; 5.8% initiated ever cigarette use and 3% first reported past 30-day cigarette use by 2018-2019; and, 4.5% initiated ever hookah use and 1.0% first reported past 30-day hookah use by 2018-2019. Among 15-17-year-old who were never users and susceptible to each TP from 2014-2017, 4.2% initiated ever e-cigarette use and 9.0% first reported past 30-day use by 2018-2019; 4.5% initiated ever cigarette use and 3% first reported past 30-day cigarette use by 2018-2019; and, 4.5% initiated ever hookah use and 2.4% first reported past 30-day hookah use by 2018-2019. Among 18-20-year-old who were never users and susceptible to each TP from 2014-2017, 3.2% initiated ever e-cigarette use and 3.6% first reported past 30-day e-cigarette use by 2018-2019; 3.0% initiated ever cigarette use and 2.3% first reported past 30-day cigarette use; and, 2.8% initiated ever hookah use and 1.0% first reported past 30-day hookah use by 2018-2019.ConclusionsFrom 2014 to 2019, onset and progression of e-cigarette, cigarette, and hookah use occurred more frequently in 12-14 and 15-17-year-old than in young adults 18-20-year-old.

IntroductionOur primary purpose is to understand comorbidities and health outcomesassociated with electronic nicotine delivery systems (ENDS) use.MethodsStudy participants were Kaiser Permanente (KP) members from eight US regionswho joined the Kaiser Permanente Research Bank (KPRB) from September 2015through December 2019 and completed a questionnaire assessing demographicand behavioral factors, including ENDS and traditional cigarette use.Medical history and health outcomes were obtained from electronic healthrecords. We used multinomial logistic regression to estimate odd ratios(ORs) and 95% confidence intervals (CIs) of current and former ENDS useaccording to member characteristics, behavioral factors, and clinicalhistory. We used Cox regression to estimate hazard ratios (HRs) and 95% CIscomparing risk of health outcomes according to ENDS use.ResultsOf 119 593 participants, 1594 (1%) reported current ENDS use and 5603 (5%)reported past ENDS use. ENDS users were more likely to be younger, male, gayor lesbian, and American Indian / Alaskan Native or Asian. After adjustmentfor confounding, current ENDS use was associated with current traditionalcigarette use (OR = 39.55; CI:33.44-46.77), current marijuana use (OR =6.72; CI:5.61-8.05), history of lung cancer (OR = 2.64; CI:1.42-4.92),non-stroke cerebral vascular disease (OR = 1.55; CI:1.21-1.99), and chronicobstructive pulmonary disease (OR = 2.16; CI:1.77-2.63). Current ENDS usewas also associated with increased risk of emergency room (ER) visits (HR =1.17; CI: 1.05-1.30) and death (HR = 1.84; CI:1.02-3.32).ConclusionsConcurrent traditional cigarette use, marijuana use, and comorbidities wereprevalent among those who used ENDS, and current ENDS use was associatedwith an increased risk of ER visits and death. Additional research focusedon health risks associated with concurrent ENDS and traditional cigaretteuse in those with underlying comorbidities is needed.