Associations Between Family and Peer E-Cigarette Use With Adolescent Tobacco and Marijuana Usage: A Longitudinal Path Analytic Approach

Psychological predictors of vaping uptake among non-smokers: A longitudinal investigation of New Zealand adults

INTRODUCTION

Demographic and health factors are known to predict vaping. Less is known about psychological predictors of vaping uptake, particularly among non-smoking adults using longitudinal designs. We aimed to model how psychological factors related to personality and mental health predicted the likelihood of vaping uptake over time in non-smoking adults ages 18+ using longitudinal data.

METHODS

Longitudinal regression models utilised data from the 2018-2020 waves of the New Zealand Attitudes and Values Study to assess how the Big Five personality traits, mental distress and self-control predicted who began vaping over time among non-users (non-vapers and non-smokers), controlling for gender, age, ethnicity and economic deprivation.

RESULTS

Analyses included 36,309 adults overall (ages 18 to 99; M = 51.0). The number of non-users who transitioned into current vaping was small (transitioned from 2018 to 2019, n = 147; 0.48%; 2019 to 2020, n = 189, 0.63%). Fully adjusted models showed that adults with higher mental distress (adjusted odds ratio [aOR] 1.43; 95% confidence interval [CI] 1.09-1.88), lower self-control (aOR 0.79; 95% CI 0.69-0.89) and higher extraversion (aOR 1.09; 95% CI 1.06-1.13) were more likely to begin vaping at the next time point compared to adults who remained non-users. Higher neuroticism and lower conscientiousness also predicted vaping uptake in initial models, but inclusion of mental distress and self-control superseded these traits.

DISCUSSION AND CONCLUSIONS

Psychological factors related to mental distress, impulse control and sociability predicted who was more likely to begin vaping as non-smoking adults. Harm prevention interventions could target these factors to reduce vaping uptake in non-smokers.

Exploring the prevalence, knowledge, attitudes and influencing factors of e-cigarette use among university students in Palestine: a cross-sectional study

OBJECTIVES

E-cigarettes have gained popularity, especially among young adults. This study aims to determine the prevalence of e-cigarette smoking, assess knowledge and attitudes and identify associated factors among Palestinian university students.

DESIGN

A cross-sectional study.

SETTING AND PARTICIPANTS

The study was conducted among Palestinian university students in early 2023.A self-administered questionnaire was used to survey 1792 students from six Palestine universities in the West Bank. The questionnaire covered various aspects, including sociodemographic information, daily habits, exposure to smoking, attitudes and knowledge about e-cigarettes. Data were analysed using descriptive statistics, χ2 tests and multivariate regression analysis.

RESULTS

The study revealed a high prevalence of tobacco use (41.2%), with e-cigarette use prevalent among 19.7% of participants. Knowledge about e-cigarettes was suboptimal, with misconceptions regarding their safety and health effects. Negative attitudes towards e-cigarettes were common, and students with negative attitudes were more likely to use e-cigarettes (aOR=2.6, 95% CI: 1.9 to 3.6). Gender (aOR=2.1, 95% CI: 1.4 to 3.0), waterpipe smoking (aOR=4.5, 95% CI: 3.2 to 6.3), physical inactivity (aOR=1.4, 95% CI: 1.1 to 1.9), high coffee consumption (aOR=1.6, 95% CI: 1.1 to 2.3), spending time with friends (aOR=2.4, 95% CI: 1.5 to 3.7), having a mother who is a smoker (aOR=1.5, 95% CI: 1.1 to 2.2) and having a friend who uses e-cigarettes (aOR=1.5, 95% CI: 1.1 to 2.1) were significantly associated with e-cigarettes use.

CONCLUSIONS

E-cigarette use is a growing concern among Palestinian university students. Combating this trend should include educational initiatives, social interventions and policy measures to promote informed decision-making and discourage e-cigarette use. Comprehensive tobacco control programs considering various tobacco and nicotine products and involving multiple stakeholders are warranted.

Associations between use of specific social media sites and electronic cigarette use among college students

OBJECTIVE

To examine dose-response associations between use of specific social media sites and the use of electronic cigarettes (e-cigarettes) and traditional cigarettes.

METHODS

This was a cross-sectional study of 298 first-year college students enrolled in the fall 2019 semester at a large state university. Heckman selection and Probit model were used to estimate associations between use of specific social media sites and e-cigarette/traditional cigarette use.

RESULTS

Each additional hour per day spent on Snapchat was associated with a 4.61% increase in the probability of lifetime e-cigarette use. In addition, among current e-cigarette users, more time spent on Snapchat was associated with more frequent e-cigarette use (marginal effects: 0.13, p = 0.001). Facebook, Twitter, Snapchat and Instagram were not associated with traditional cigarette smoking.

CONCLUSION

Snapchat was the only major social media platform associated with both lifetime and current e-cigarette use.

Mutual pathways between peer and own e-cigarette use among youth in the United States: a cross-lagged model

BACKGROUND

Electronic cigarettes (e-cigarettes) have become the most common tobacco product used among adolescents in the United States (US). Prior research has shown that peer e-cigarette use was associated with increased risk of own e-cigarette use. Nonetheless, there is little empirical evidence on the directionality of these associations-if peer use predicts own use (peer influence) or if own use predicts peer use (peer selection).

METHODS

We estimated the association between peer and own e-cigarette use among US adolescents 12-17 years of age. We used the cross-lagged model to investigate the mutual relationship between peer and own e-cigarette use over time using data from a population-based longitudinal study, Population Assessment of Tobacco and Health. Stratified analyses were conducted by sex and age subgroups.

RESULTS

Results from a cross-lagged model showed a statistically significant predicting path leading from peer use at the prior time point to own use at the following time point, but not vice versa.

CONCLUSIONS

We found strong relationships between peer e-cigarette use and own e-cigarette use at within-individual levels. Peer influence paths were more robust than peer selection paths for e-cigarette use. Incorporating peers into prevention and intervention programs may help enhance these strategies.

Socio-temporal contextual and community factors associated with daily exclusive ENDS use and dual use with tobacco cigarettes among adolescent vapers: an ecological momentary assessment study

BACKGROUND

Adolescents who dual use ENDS with tobacco cigarettes are more likely to have an increased risk of developing dependence. Yet, little is understood about the factors driving dual use among adolescents. The current study sought to reveal the day-to-day socio-temporal contextual and community factors associated with adolescents' use of electronic nicotine delivery systems (ENDS), and how these factors predict dual use with tobacco cigarettes.

METHODS

We collected ecological momentary assessments (EMA) from a sample of 50 adolescent past two-week vapers (ages 14-17 years old) over 14 days. Daily EMA data were collected on ENDS and tobacco cigarette use, as well as a range of contextual (i.e., motivations to vape, location of vaping, who with when vaping) and community factors (i.e., exposure to peers vaping, to adults vaping, to ENDS advertising, to ENDS warning messages). Our primary analyses were multilevel regressions, accounting for daily observations nested within individuals (N = 700 observations).

RESULTS

Participants used ENDS exclusively on 44% of days and dual used ENDS and tobacco cigarettes on 8% of the days. Dual use days (versus exclusive ENDS use days) were associated with "vaping because tobacco use was prohibited" (OR = 34.65, p < .05). Also, dual use days (versus no use days) were associated with greater exposure to adults vaping (OR = 5.59, p < .05), peers vaping (OR = 7.48, p < .05), and (c) ENDS advertisements or promotions (OR = 2.12, p < .01), whereas exclusive use days (versus no use days) were only associated with greater exposure to peers vaping (OR = 2.58, p < .01).

CONCLUSIONS

Results showed that exposure to peers and adults vaping and exposure to ENDS marketing were associated with same day dual use behaviors. And, that adolescents who dual used were motivated to use ENDS because they were easy to conceal. Findings support stricter regulation of ENDS marketing and for smoke-free air laws that include ENDS. In addition, these findings support prioritizing family- and school-based prevention programming that effectively communicates risk associated with ENDS use, including heightened risk of dual use and dependence. Such efforts can reduce the number of adolescents who use ENDS as well as the number who transition to tobacco cigarette use.

Dual Use of Nicotine and Cannabis Through Vaping Among Adolescents

INTRODUCTION

This study seeks to identify adolescent nicotine and cannabis vaping patterns and the characteristics of those adolescents who comprised each pattern.

METHODS

This prospective longitudinal survey study measured the relationship between nicotine and cannabis vaping among 1,835 adolescents from 4 public high schools outside of Philadelphia, Pennsylvania. Adolescents completed in-classroom surveys, including questions of lifetime and past 30-day nicotine and cannabis vaping, at Wave 1 (fall 2016, ninth grade) and 6-month intervals for the following 36 months (fall 2019, 12th grade). Data were analyzed in 2021.

RESULTS

A sequential processes growth mixture model revealed 4 latent conjoint classes of nicotine and cannabis vaping: early, declining dual use (Class 1: n=259); rapidly increasing dual use (Class 2: n=128); later, slower dual use (Class 3: n=313); and no use (Class 4: n=1,136). Increased odds of belonging to Class 1 and Class 2 versus belonging to Class 4 were significantly associated with cigarette smoking (OR=3.71, OR=2.21), alcohol use (OR=2.55, OR=4.39), peer vaping (OR=1.24, OR=1.20), sensation seeking (OR=1.03, OR=1.11), positive E-cigarette expectations (OR=1.21, OR=1.17), and cigar smoking (OR=2.39 Class 2 only). Increased odds of belonging to Class 3 versus Class 4 were significantly associated with alcohol use (OR=1.66), perceived benefits of E-cigarette use (OR=1.03), positive E-cigarette expectations (OR=1.08), depressive symptoms (OR=1.02), and sensation seeking (OR=1.03).

CONCLUSIONS

From middle to late adolescence, vaping of nicotine and cannabis develop in close parallel. Regulatory policy and prevention interventions should consider the interplay between these 2 substances during this period of adolescence.

The Indirect Effect of Cigarette Smoking on e-Cigarette Progression via Substitution Beliefs

PURPOSE

This study sought to evaluate whether associations between adolescent combustible cigarette smoking and e-cigarette progression were explained by beliefs that e-cigarettes substitute for cigarettes in nonsmoking situations.

METHODS

Adolescents (N = 1,799) from public high schools outside of Philadelphia, PA, completed in-classroom surveys at wave 1 (fall 2016, beginning of ninth grade) and at 6-month intervals for the following 36 months (fall 2019, beginning of 12th grade).

RESULTS

A parallel process latent growth curve model revealed that the pathway from baseline smoking to e-cigarette use trend through baseline e-cigarette substitution beliefs was significant (B = .02, z = 2.16, p = .03), indicating that the positive effect of greater baseline cigarette smoking on the rate of e-cigarette progression was channeled through e-cigarette substitution beliefs. The indirect effect from baseline smoking to e-cigarette use trend via e-cigarette substitution beliefs trend was also significant, albeit negative (B = -.05, z = -2.61, p = .009). The negative indirect effect suggested that the strong positive effect of baseline cigarette smoking on baseline substitution beliefs was followed by a slowing of the overall rate of change from baseline. Given that the total effect from baseline smoking to e-cigarette trend was not significant (p = .91), the results suggested complete mediation.

CONCLUSIONS

Among adolescents with greater use of combustible cigarettes, beliefs regarding the substitutability of e-cigarettes in nonsmoking situations appear to foster progression in e-cigarette use. Addressing these beliefs in the school setting and through media campaign messaging early in adolescence may help to prevent the use of e-cigarettes and combustible cigarettes.

Conjoint Developmental Trajectories of Adolescent E-cigarette and Combustible Cigarette Use

OBJECTIVES

In this study, we sought to identify which adolescents progress to regular electronic cigarette (e-cigarette) use (without cigarette smoking), which adolescents become dual users of both types of cigarettes, and how dual use develops across time.

METHODS

Adolescents (N = 1808) from public high schools outside Philadelphia, Pennsylvania, completed in-classroom surveys at wave 1 (fall 2016, beginning of ninth grade) and at 6-month intervals for the following 36 months (fall 2019, beginning of 12th grade).

RESULTS

A sequential processes growth mixture model identified 4 conjoint latent classes: later, rapid e-cigarette uptake (class 1: n = 230); no use of e-cigarettes or combustible cigarettes (class 2: n = 1141); earlier, steady e-cigarette uptake (class 3: n = 265); and dual use of e-cigarettes and combustible cigarettes (class 4: n = 204). Using a rich set of potential risk factors, multinomial logistic regression assessed the likelihood of belonging to each conjoint class compared with the comparison class (dual use). Adolescents in the dual use class were characterized by a greater number and severity of e-cigarette and combustible cigarette risk factors. Adolescents in the 2 e-cigarettes-only classes were characterized by either e-cigarette-specific risk factors (earlier onset) or no risk factors (later onset). The no use class had an absence of risk factors for e-cigarette and cigarette use.

CONCLUSIONS

This study provides new prospective evidence for distinct patterns and profiles of adolescents who progress to current e-cigarette use, including adolescents who were initially cigarette smokers. The findings have implications for prevention intervention timing, tobacco product focus, content, and the adolescent subgroups to target.

Adolescent depression symptoms and e-cigarette progression

BACKGROUND

Depression symptoms are associated with the initiation of cigarette smoking and progression to regular use. Whether similar relationships exist between depression symptoms and adolescent e-cigarette progression has not been firmly established.

METHODS

This prospective longitudinal survey study measured the relationship between depression symptoms and e-cigarette use among 1822 adolescents from four public high schools outside of Philadelphia, PA. Adolescents completed in-classroom surveys at wave 1 (fall 2016, 9th grade) and 6-month intervals for the following 36 months (fall 2019, 12th grade). E-cigarette use, depression symptoms, and potential covariates were measured at each wave. A latent growth curve model was used to assess the longitudinal relationship between e-cigarette use and depression symptoms.

RESULTS

Baseline depressive symptoms had a significant effect on e-cigarette use trend (b = 0.01, z = 4.29, p < 0.0001) while holding other variables constant. A standard deviation increase in depressive symptoms at baseline was associated with a 0.25 standard deviation increase in the rate of e-cigarette progression across the following 36 months. By contrast, the path from baseline e-cigarette use to depressive symptoms trend was not significant (p = 0.74).

CONCLUSIONS

The present study provides new evidence for the effects of depression symptoms on adolescent e-cigarette progression. Greater depressive symptoms at age 14 years old were associated with a faster rate of e-cigarette escalation. However, e-cigarette use was not related to the development of depression symptoms over time. It will be important to examine whether adolescents with elevated depression symptoms respond similarly to e-cigarette prevention campaigns as adolescents in general.

Machine Learning-Based Nicotine Addiction Prediction Models for Youth E-Cigarette and Waterpipe (Hookah) Users

Despite the harmful effect on health, e-cigarette and hookah smoking in youth in the U.S. has increased. Developing tailored e-cigarette and hookah cessation programs for youth is imperative. The aim of this study was to identify predictor variables such as social, mental, and environmental determinants that cause nicotine addiction in youth e-cigarette or hookah users and build nicotine addiction prediction models using machine learning algorithms. A total of 6511 participants were identified as ever having used e-cigarettes or hookah from the National Youth Tobacco Survey (2019) datasets. Prediction models were built by Random Forest with ReliefF and Least Absolute Shrinkage and Selection Operator (LASSO). ReliefF identified important predictor variables, and the Davies–Bouldin clustering evaluation index selected the optimal number of predictors for Random Forest. A total of 193 predictor variables were included in the final analysis. Performance of prediction models was measured by Root Mean Square Error (RMSE) and Confusion Matrix. The results suggested high performance of prediction. Identified predictor variables were aligned with previous research. The noble predictors found, such as ‘witnessed e-cigarette use in their household’ and ‘perception of their tobacco use’, could be used in public awareness or targeted e-cigarette and hookah youth education and for policymakers.