Examining Disparities in Current E-Cigarette Use among U.S. Adults before and after the WHO Declaration of the COVID-19 Pandemic in March 2020

Contextualizing Changes in e-Cigarette Use During the Early COVID-19 Pandemic and Accompanying Infodemic ("So Much Contradictory Evidence"): Qualitative Document Analysis of Reddit Forums

BACKGROUND

Understanding how social media platforms facilitate information exchange and influence behavior during health crises can enhance public health responses during times of uncertainty. While some risk factors for COVID-19 susceptibility and severity (eg, old age) were clear, whether e-cigarette use increased risk was not clear. People who used e-cigarettes had to navigate both the COVID-19 infodemic and a conflicting, politicized, and changing information environment about the interaction between COVID-19 and e-cigarette use.

OBJECTIVE

This study aims to characterize and contextualize e-cigarette-related behavior changes during the early COVID-19 pandemic and illuminate the role that social media played in decision-making.

METHODS

We conducted a qualitative analysis of COVID-19-related e-cigarette discussions on 3 Reddit forums about e-cigarettes. We collected 189 relevant discussion threads made in the first 6 months of the pandemic (collected from June 27, 2020, to July 3, 2020). Threads included 3155 total comments (mean 17 comments) from approximately 1200 unique Redditors. We developed and applied emergent codes related to e-cigarette perceptions and behaviors (eg, the role of nicotine in COVID-19 and do-it-yourself narratives) and web-based community interactions (eg, advice), identified thematic patterns across codes, and developed a model to synthesize the socioecological context of e-cigarette behaviors.

RESULTS

e-Cigarette subreddits provided a platform for Redditors to discuss perceptions and experiences with e-cigarettes, make sense of information, and provide emotional support. Discussions reflected an array of e-cigarette-related behavioral responses, including increases and decreases in use intensity, changes in purchasing practices (eg, stockpiling), and changes in vaping practices (eg, reusing disposable pods). This study presented a theoretically and empirically informed model of how circumstances created by the pandemic (eg, changes in activity space and product shortages) compelled behavior changes. Redditors drew from their existing perceptions, intentions, and experiences with nicotine and tobacco products; their personal pandemic experiences; and their participation on Reddit to decide whether and how to change their e-cigarette behaviors during the early pandemic. Forums reflected uncertainty, stress, and debate about the rapidly evolving and complicated public health information. Consumption and discussion of media (eg, news articles and peer-reviewed publications) on Reddit informed e-cigarette perceptions and behaviors. Decisions were complicated by distrust of the media.

CONCLUSIONS

Variations in individual traits and environmental circumstances during the early COVID-19 pandemic provide context for why there was no unified direction of e-cigarette behavior change during this period. Information and discussion on Reddit also informed risk perceptions and decisions during the pandemic. Social media is an effective and important place to communicate public health information, particularly during crisis or disaster situations. Moving forward, transparent, accurate, and specific message development should consider the stress, struggles, and stigma of people who use e-cigarettes and address the roles mistrust and misinformation play in decisions.

Differences in Provider Beliefs and Delivery of the 5As for Cigarette and Non-Cigarette Tobacco Use Between Two Types of Healthcare Centers Serving Rural and/or Medically Underserved Areas of Texas, US

BACKGROUND/OBJECTIVES

Rural populations in the US bear a disproportionate burden of cancer mortality, which may be partly due to their elevated tobacco use and the limited receipt of tobacco use interventions in rural healthcare settings. Here, we examine providers' use of the 5As (Ask, Advise, Assess, Assist, and Arrange), a brief tobacco cessation intervention, with their patients to assess intervention gaps.

METHODS

Provider practices in substance use treatment centers (SUTCs) and medical healthcare centers (MHCs), each serving rural and/or medically underserved areas (MUAs) of Texas, were compared. In total, 347 providers from 10 SUTCs (n = 174) and 9 MHCs (n = 173) responded to an anonymized survey about their cigarette and non-cigarette screening and intervention delivery, along with their perceived importance and workforce's preparedness to help patients stop using tobacco. Linear mixed and generalized linear mixed models were used to assess differences between practices at SUTCs and MHCs.

RESULTS

More MHC than SUTC providers reported that cigarette and non-cigarette tobacco use cessation intervention were (respectively) important parts of their job (p = 0.0009; p = 0.0023) and that their workforce was prepared to help their patients quit tobacco (p = 0.0275), although less than half of all respondents endorsed preparedness. Relative to those at SUTCs, MHC providers reported higher rates of asking (SUTCs = 59.57% and MHCs = 77.21%; p = 0.0182) and advising (SUTCs = 45.34% and MHCs = 72.35%; p = 0.0017) their patients to quit cigarette smoking and advising them to quit non-cigarette tobacco products (SUTCs = 43.94% and MHCs = 71.76%; p = 0.0016).

CONCLUSIONS

Overall, providers in both settings may benefit from greater preparation to deliver tobacco cessation care; needs were more prevalent within SUTCs than MHCs. Our findings can inform strategic planning to improve centers' capacity to comprehensively address their patients' tobacco use in rural/MUAs of Texas, US.

Feature Selection and Machine Learning Approaches in Prediction of Current E-Cigarette Use Among U.S. Adults in 2022

Feature selection is essentially the process of picking informative and relevant features from a larger collection of features. Few studies have focused on predictors for current e-cigarette use among U.S. adults using feature selection and machine learning (ML) approaches. This study aimed to perform feature selection and develop ML approaches in prediction of current e-cigarette use using the 2022 Health Information National Trends Survey (HINTS 6). The Boruta algorithm and the least absolute shrinkage and selection operator (LASSO) were used to perform feature selection of 71 variables. The random oversampling example (ROSE) method was utilized to deal with imbalance data. Five ML tools including support vector machines (SVMs), logistic regression (LR), random forest (RF), gradient boosting machine (GBM), and extreme gradient boosting (XGBoost) were applied to develop ML models. The overall prevalence of current e-cigarette use was 4.3%. Using the overlapped 15 variables selected by Boruta and LASSO, the RF algorithm provided the best classifier with an accuracy of 0.992, sensitivity of 0.985, F1 score of 0.991, and AUC of 0.999. Weighted logistic regression further confirmed that age, education level, smoking status, belief in the harm of e-cigarette use, binge drinking, belief in alcohol increasing cancer, and the Patient Health Questionnaire-4 (PHQ4) score were associated with e-cigarette use. This study confirmed the strength of ML techniques in survey data, and the findings will guide inquiry into behaviors and mentalities of substance users.

E-cigarette use or dual use of E-cigarette and combustible cigarette and mental health and cognitive impairment: Findings from the National Health Interview Survey, 2020-2021

BACKGROUND

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.

METHODS

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.

RESULTS

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).

CONCLUSIONS

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.

Knowledge, Attitude, and Practice of E-Cigarettes of Adolescents and Adults in Saudi Arabia: A Cross-Sectional Study

E-cigarettes have gained enormous popularity, and their use has increased drastically worldwide. However, little is known regarding adolescents' and adults' knowledge, attitudes, and practices in Saudi Arabia. We conducted a cross-sectional study using a self-administered online-modified WHO GATS questionnaire on a convenience sample approach. Data were collected between January and March 2021 after the alleviation of COVID-19 lockdown measures in Saudi Arabia. Univariate and multivariate regression models were developed to identify independent factors associated with knowledge, attitude, and practice. Our sample (1335) had a mean age of 26.45 ± 10.5 years; nearly half of the participants had poor knowledge about e-cigarettes. The usage and positive attitude were reported by 18.6% and 19.4%, respectively. Around 43.5% of e-cigarette users reported starting or increased use during the COVID-19 pandemic, while 9.5% of participants would recommend it to others. Logistic regressions showed that older participants were more likely to have poor knowledge (OR = 1.02, 95% C.I. = 1.01-1.03) and positive attitudes (OR = 0.98, 95% C.I. = 0.91-0.96). Male participants and smokers (OR = 3.0, 95% C.I. = 2.3-3.8) were more likely to have a positive attitude. However, younger participants were less likely to go for e-cigarettes (OR = 0.95, 95% C.I. = 0.93-0.97), while males (OR = 2.53, 95% C.I. = 1.65-3.86) and smokers (OR = 4.63, 95% C.I. = 3.47-6.18) were more likely to use them. This study indicated a high level of poor knowledge about e-cigarettes. A considerable proportion of participants reported usage and a positive attitude towards them. Older age, male gender, and being a smoker were the main elicited predictors for e-cigarette use.