Effects of a Social Media Intervention on Vaping Intentions: Randomized Dose-Response Experiment.

BACKGROUND: e-Cigarette use, especially by young adults, is at unacceptably high levels and represents a public health risk factor. Digital media are increasingly being used to deliver antivaping campaigns, but little is known about their effectiveness or the dose-response effects of content delivery. OBJECTIVE: The objectives of this study were to evaluate (1) the effectiveness of a 60-day antivaping social media intervention in changing vaping use intentions and beliefs related to the stimulus content and (2) the dose-response effects of varying levels of exposure to the intervention on vaping outcomes, including anti-industry beliefs, vaping intentions, and other attitudes and beliefs related to vaping. METHODS: Participants were adults aged 18 to 24 years in the United States. They were recruited into the study through Facebook (Meta Platforms) and Instagram (Meta Platforms), completed a baseline survey, and then randomized to 1 of the 5 conditions: 0 (control), 4, 8, 16, and 32 exposures over a 15-day period between each survey wave. Follow-up data were collected 30 and 60 days after randomization. We conducted stratified analyses of the full sample and in subsamples defined by the baseline vaping status (never, former, and current). Stimulus was delivered through Facebook and Instagram in four 15-second social media videos focused on anti-industry beliefs about vaping. The main outcome measures reported in this study were self-reported exposure to social media intervention content, attitudes and beliefs about vaping, and vaping intentions. We estimated a series of multivariate linear regressions in Stata 17 (StataCorp). To capture the dose-response effect, we assigned each study arm a numerical value corresponding to the number of advertisements (exposures) delivered to participants in each arm and used this number as our focal independent variable. In each model, the predictor was the treatment arm to which each participant was assigned. RESULTS: The baseline sample consisted of 1491 participants, and the final analysis sample consisted of 57.28% (854/1491) of the participants retained at the 60-day follow-up. We compared the retained participants with those lost to follow-up and found no statistically significant differences across demographic variables. We found a significant effect of the social media treatment on vaping intentions (ß=-0.138, 95% CI -0.266 to -0.010; P=.04) and anti-industry beliefs (ß=-0.122, 95% CI 0.008-0.237; P=.04) targeted by the intervention content among current vapers but not among the full sample or other strata. We found no significant effects of self-reported exposure to the stimulus. CONCLUSIONS: Social media interventions are a promising approach to preventing vaping among young adults. More research is needed on how to optimize the dosage of such interventions and the extent to which long-term exposure may affect vaping use over time. TRIAL REGISTRATION: ClinicalTrials.gov NCT04867668; https://clinicaltrials.gov/study/NCT04867668.

Longitudinal association between e-cigarette use and respiratory symptoms among US adults: Findings from the Population Assessment of Tobacco and Health Study Waves 4-5.

BACKGROUND: We assessed longitudinal effects of e-cigarette use on respiratory symptoms in a nationally representative sample of US adults by combustible tobacco smoking status. METHODS: We analyzed Waves 4-5 public-use data from the Population Assessment of Tobacco and Health Study. Study sample included adult respondents who reported no diagnosis of respiratory diseases at Wave 4, and completed Waves 4-5 surveys with no missing data on analytic variables (N = 15,291). Outcome was a validated index of functionally important respiratory symptoms based on 7 wheezing/cough questions (range 0-9). An index score of ≥2 was defined as having important respiratory symptoms. Weighted lagged logistic regression models were performed to examine the association between e-cigarette use status at Wave 4 (former/current vs. never use) and important respiratory symptoms at Wave 5 by combustible tobacco smoking status (i.e., never/former/current smokers), adjusting for Wave 4 respiratory symptom index, sociodemographic characteristics, secondhand smoke exposure, body mass index, and chronic disease. RESULTS: Among current combustible tobacco smokers, e-cigarette use was associated with increased odds of reporting important respiratory symptoms (former e-cigarette use: adjusted odds ratio [AOR] = 1.39, 95% confidence interval [CI]: 1.07-1.81; current e-cigarette use: AOR = 1.55, 95% CI: 1.17-2.06). Among former combustible tobacco smokers, former e-cigarette use (AOR = 1.51, 95% CI: 1.06-2.15)-but not current e-cigarette use (AOR = 1.59, 95% CI: 0.91-2.78)-was associated with increased odds of important respiratory symptoms. Among never combustible tobacco smokers, no significant association was detected between e-cigarette use and important respiratory symptoms (former e-cigarette use: AOR = 1.62, 95% CI: 0.76-3.46; current e-cigarette use: AOR = 0.82, 95% CI: 0.27-2.56). CONCLUSIONS: The association between e-cigarette use and respiratory symptoms varied by combustible tobacco smoking status. Current combustible tobacco smokers who use e-cigarettes have an elevated risk of respiratory impairments.

Evaluation of response to incentive recruitment strategies in a social media-based survey.

Objective: This study aimed to examine varying incentives on acceptance to participate in an online survey on social media and to identify related demographic factors. Methods: The study used Facebook and targeted its users aged 18 to 24 years in the United States. During recruitment, participants were randomized to one of the three types of incentives for survey completion, (1) a $5 gift card, (2) a lottery for a $200 gift card, and (3) a $5 gift card plus a lottery for a $200 gift card. Acceptance rates for survey participation were compared across three incentives using percentages, 95% logit-transformed confidence intervals, and Pearson's chi-squared tests. The survey asked about cognition and behaviors around smoking and vaping. Results: The ads had 1,782,931 impressions, 1,104,139 reaches, and 11,878 clicks. The average ad frequency was 1.615, and the click-through rate was 0.67%. Males clicked less than females when seeing the ads. The acceptance rates for the three incentives were 63.7%, 37.2%, and 64.6%, respectively. A Chi-square test confirmed that the lottery-only group had a lower acceptance rate compared to those guaranteed an incentive, including the gift card group and the gift card and lottery group. Further analyses indicated that males did not opt into the survey as often as females when given the lottery-only incentive option, and those who did not meet their financial expenses opted into the survey more often than those who had more money than their expenses when given the lottery-only incentive option. Conclusions: This study suggests that incentives guaranteed to all participants, even if the incentive's value is small, may lead to higher acceptance rates compared to a lottery for a greater incentive in social media-based surveys.

Perceptions of and Experiences With Cigarette and E-Cigarette Use Among a Diverse Population of US Latino Adolescents and Young Adults.

PURPOSE: To determine potential unique factors influencing cigarette and e-cigarette use in US Latino youth. APPROACH: We conducted a qualitative study assessing cigarette and e-cigarette perceptions and experiences, including experiences with/perceptions of the products, cultural influences and influences of friends and family. SETTING: Four online discussion boards, conducted in October 2020. PARTICIPANTS: 92 Latino youth aged 15-21 years living in the US. METHOD: Data from the discussion groups were coded and analyzed by three trained coders using a thematic analysis approach. RESULTS: Stress relief emerged as the dominant theme connected with both cigarettes and e-cigarettes. Apart from stress, perceptions of and experiences with the products differed. E-cigarettes were commonly viewed as trendy and cool and participants often reported using them due to curiosity and popularity. Participants commonly compared e-cigarettes to cigarettes, noting benefits of e-cigarettes. Participants also noted more negative short and long-term health effects of cigarette use, and discussed generational differences between the two products. CONCLUSION: Findings from this study help address a dearth of research examining tobacco use among diverse groups of Latino youth. Findings indicate that despite differences in country of heritage, Latino youth are united by similar opinions about cigarettes and e-cigarettes. Additionally, they share cultural values and experiences which could be leveraged for tobacco control communications that cut across populations of Latino youth.

The Measurement of Dose and Response for Smoking Behavior Change Interventions in the Digital Age: Systematic Review.

BACKGROUND: There is little consensus regarding effective digital health interventions for diverse populations, which is due in part to the difficulty of quantifying the impact of various media and content and the lack of consensus on evaluating dosage and outcomes. In particular, digital smoking behavior change intervention is an area where consistency of measurement has been a challenge because of emerging products and rapid policy changes. This study reviewed the contents and outcomes of digital smoking interventions and the consistency of reporting to inform future research. OBJECTIVE: This study aims to systematically review digital smoking behavior change interventions and evaluate the consistency in measuring and reporting intervention contents, channels, and dose and response outcomes. METHODS: PubMed, Embase, Scopus, PsycINFO, and PAIS databases were used to search the literature between January and May 2021. General and journal-based searches were combined. All records were imported into Covidence systematic review software (Veritas Health Innovation) and duplicates were removed. Titles and abstracts were screened by 4 trained reviewers to identify eligible full-text literature. The data synthesis scheme was designed based on the concept that exposure to digital interventions can be divided into intended doses that were planned by the intervention and enacted doses that were completed by participants. The intended dose comprised the frequency and length of the interventions, and the enacted dose was assessed as the engagement. Response measures were assessed for behaviors, intentions, and psychosocial outcomes. Measurements of the dose-response relationship were reviewed for all studies. RESULTS: A total of 2916 articles were identified through a database search. Of these 2916 articles, the title and abstract review yielded 324 (11.11%) articles for possible eligibility, and 19 (0.65%) articles on digital smoking behavior change interventions were ultimately included for data extraction and synthesis. The analysis revealed a lack of prevention studies (0/19, 0%) and dose-response studies (3/19, 16%). Of the 19 studies, 6 (32%) reported multiple behavioral measures, and 5 (23%) reported multiple psychosocial measures as outcomes. For dosage measures, 37% (7/19) of studies used frequency of exposure, and 21% (4/19) of studies mentioned the length of exposure. The assessment of clarity of reporting revealed that the duration of intervention and data collection tended to be reported vaguely in the literature. CONCLUSIONS: This review revealed a lack of studies assessing the effects of digital media interventions on smoking outcomes. Data synthesis showed that measurement and reporting were inconsistent across studies, illustrating current challenges in this field. Although most studies focused on reporting outcomes, the measurement of exposure, including intended and enacted doses, was unclear in a large proportion of studies. Clear and consistent reporting of both outcomes and exposures is needed to develop further evidence in intervention research on digital smoking behavior change.

Assessing digital advertising exposure using a virtual experimental protocol.

Introduction: The rapid increase in online public education campaigns underscores the need for a better understanding of the effects of exposure to digital advertising and targeted individual-level outcomes. The goal of this study is to develop a virtual experimental protocol to evaluate the dose-response effects of individual-level exposure to digital video ads on campaign outcomes in a naturalistic online browsing context. Methods: Young adults aged 18-24 years (n = 221) completed three 5 min viewing sessions on a realistic mock-up of the YouTube mobile app over a period of 2 weeks, followed by a 10-min survey after the third session. Participants were randomized to view between 0 and 6 exposures of ads from an e-cigarette prevention campaign; respondents viewed a total of 2 ads per session, with 0 to 2 of those ads being non-skippable digital video ads from the campaign and/or a dummy ad. The video ads played prior to short YouTube videos. Outcomes measured were self-reported ad recognition, frequency of ad exposure, and main message knowledge. Results: This study demonstrates a rapidly accessible virtual experimental protocol for evaluating the dose-response effects of digital advertising and individual-level outcomes. Five digital exposures of non-skippable video ads delivered via this platform over a 2-week period generated the highest ad recognition when there were up to six exposures. Higher exposure levels may be needed for message knowledge and ad-content-related effects. Conclusion: This protocol can be extended to investigate dose-response effects and mechanisms of action of individual-level exposure to digital advertising for multiple campaign outcomes, including changes in knowledge, attitudes, and beliefs. Findings can inform evidence for adequate levels of digital exposure in public education campaigns.

Machine learning to design antimicrobial combination therapies: Promises and pitfalls.

Combination therapies can overcome antimicrobial resistance (AMR) and repurpose existing drugs. However, the large combinatorial space to explore presents a daunting challenge. In response, machine learning (ML) algorithms are being applied to identify novel synergistic drug interactions from millions of potential combinations. Here, we compare ML-based approaches for combination therapy design based on the type of input information used, specifically: drug properties, microbial response and infection microenvironment. We also provide a compilation of publicly available drug interaction datasets relevant to AMR. Finally, we discuss limitations of current ML-based methods and propose new strategies for designing efficacious combination therapies. These include consideration of in vivo conditions, design of sequential combinations, enhancement of model interpretability and application of deep learning algorithms.

Cigar Use Progression Among New Cigar Initiators: A Two-Part Growth Curve Analysis Among a Youth and Young Adult Cohort.

INTRODUCTION: Youth and young adults (YYAs) are at high risk of cigar use. This study's objective was to examine progression and sociodemographic differences in current cigar use and frequency among new cigar initiators. AIMS AND METHODS: We conducted a two-part latent growth model among a nationally representative cohort of cigar initiators (aged 15-25) to examine 24-month trajectories of current cigar use and frequency (n = 1483). The cohort was recruited via address-based sampling with online data collection from 2014 to 2019 and surveyed approximately every 6 months. RESULTS: The unconditional odds of current cigar use (ie, past 30-day use) within 6 months of initiation was 0.72 (95% confidence interval: 0.63, 0.82), corresponding to a probability of 42%. The odds of current use among recent cigar initiates declined 6 months after initiation and was followed by a stabilization in use over time. Among continued users, frequency (# days used in past 30 days) increased linearly over time but remained low (3.47 days/months at 24 months). Younger individuals, non-Hispanic African Americans, those with lower subjective financial status, and current users of cigarettes, other tobacco products and/or marijuana were at highest risk within 6 months of initiation. Males, younger users, and current cigarette smokers had the highest risk for cigar progression over time. CONCLUSIONS: This study is the first to examine longitudinal cigar use patterns among YYA cigar initiators. Findings emphasize the need for research across the cigar use spectrum and the importance of interventions targeted by age, stage of use, cigarette, other tobacco, and marijuana use and key sociodemographics to interrupt use pathways. IMPLICATIONS: This study is the first to examine progression of cigar use among YYAs who have newly initiated cigars. Results show a high probability of current cigar use within 6 months of initiation followed by a rapid decline and stabilization over time. Frequency increases among those who continue using cigars. Males, younger users, and current cigarette smokers had the highest risk for cigar progression over time. Findings emphasize the need for targeting interventions by age, stage of use, cigarette, other tobacco, and marijuana use and key sociodemographics to interrupt use pathways.

Assessing the Health and Economic Impact of a Potential Menthol Cigarette Ban in New York City: a Modeling Study.

Menthol in cigarettes increases nicotine dependence and decreases the chances of successful smoking cessation. In New York City (NYC), nearly half of current smokers usually smoke menthol cigarettes. Female and non-Latino Black individuals were more likely to smoke menthol-flavored cigarettes compared to males and other races and ethnicities. Although the US Food and Drug Administration recently announced that it will ban menthol cigarettes, it is unclear how the policy would affect population health and health disparities in NYC. To inform potential policymaking, we used a microsimulation model of cardiovascular disease (CVD) to project the long-term health and economic impact of a potential menthol ban in NYC. Our model projected that there could be 57,232 (95% CI: 51,967-62,497) myocardial infarction (MI) cases and 52,195 (95% CI: 47,446-56,945) stroke cases per 1 million adult smokers in NYC over a 20-year period without the menthol ban policy. With the menthol ban policy, 2,862 MI cases and 1,983 stroke cases per 1 million adults could be averted over a 20-year period. The model also projected that an average of $1,836 in healthcare costs per person, or $1.62 billion among all adult smokers, could be saved over a 20-year period due to the implementation of a menthol ban policy. Results from subgroup analyses showed that women, particularly Black women, would have more reductions in adverse CVD outcomes from the potential implementation of the menthol ban policy compared to males and other racial and ethnic subgroups, which implies that the policy could reduce sex and racial and ethnic CVD disparities. Findings from our study provide policymakers with evidence to support policies that limit access to menthol cigarettes and potentially address racial and ethnic disparities in smoking-related disease burden.

Patterns of E-cigarette Use and Subsequent Cigarette Smoking Cessation Over 2 Years (2013/2014-2015/2016) in the Population Assessment of Tobacco and Health Study.

INTRODUCTION: Understanding the population impact of e-cigarettes requires determining their effect on cigarette smoking cessation. METHODS: Using the US Population Assessment of Tobacco and Health cohort, we examined smoking cessation among adult current cigarette smokers at Wave 1 with follow-up data at Waves 2 and 3 (n = 9724). RESULTS: By Wave 3 (2015/2016), 17.3% of smokers had quit smoking. Smokers using e-cigarettes daily or who increased to daily use over the three waves were two to four times more likely to have quit in the short term (<1 year) and long term (1+ years) compared with never e-cigarette users (p < .001). E-cigarette use in the last quit attempt was associated with a higher likelihood of short-term (<1 year) quitting at Wave 3 (adjusted relative risk ratio: 1.33; 95% confidence interval: 1.04, 1.71) compared with smokers who did not use an e-cigarette in their last quit attempt. Noncurrent (no use in any wave) e-cigarette users and users who were unstable in use frequency were 33% and 47% less likely to quit in the short-term, respectively (p < .001). Flavored (vs nonflavored) and using a rechargeable (vs disposable) e-cigarette device was associated with an increased likelihood of both short- and long-term quitting. CONCLUSION: Smoking cessation was more likely among frequent e-cigarette users, users of e-cigarettes in last quit attempt, and users of flavored and rechargeable devices. Less frequent, unstable, past, or never e-cigarette users were less likely to quit smoking. Monitoring the relationship between patterns of e-cigarette and cigarette use is complex but critical for gauging the potential of e-cigarettes as a harm reduction tool. IMPLICATIONS: This study suggests that consistent and frequent e-cigarette use over time is associated with cigarette smoking cessation among adults in the United States. In addition, findings suggest that flavored e-cigarette use and use of rechargeable e-cigarette devices can facilitate smoking cessation. These results underscore the importance of carefully defining and characterizing e-cigarette exposure patterns, potential confounders, and use of e-cigarettes to quit smoking, as well as variations in length of the smoking cessation.

The Effectiveness of Online Messages for Promoting Smoking Cessation Resources: Predicting Nationwide Campaign Effects From Neural Responses in the EX Campaign.

What are the key ingredients that make some persuasive messages resonate with audiences and elicit action, while others fail? Billions of dollars per year are put towards changing human behavior, but it is difficult to know which messages will be the most persuasive in the field. By combining novel neuroimaging techniques and large-scale online data, we examine the role of key health communication variables relevant to motivating action at scale. We exposed a sample of smokers to anti-smoking web-banner messages from a real-world campaign while measuring message-evoked brain response patterns via fMRI, and we also obtained subjective evaluations of each banner. Neural indices were derived based on: (i) message-evoked activity in specific brain regions; and (ii) spatially distributed response patterns, both selected based on prior research and theoretical considerations. Next, we connected the neural and subjective data with an independent, objective outcome of message success, which is the per-banner click-through rate in the real-world campaign. Results show that messages evoking brain responses more similar to signatures of negative emotion and vividness had lower online click-through-rates. This strategy helps to connect and integrate the rapidly growing body of knowledge about brain function with formative research and outcome evaluation of health campaigns, and could ultimately further disease prevention efforts.

Sociodemographic Disparities in the Tobacco Retail Environment in Washington, DC: A Spatial Perspective.

Objective: Studies assessing sociodemographic disparities in the tobacco retail environment have relied heavily on non-spatial analytical techniques, resulting in potentially misleading conclusions. We utilized a spatial analytical framework to evaluate neighborhood sociodemographic disparities in the tobacco retail environment in Washington, DC (DC) and the DC metropolitan statistical area (DC MSA). Methods: Retail tobacco availability for DC (n=177) and DC MSA (n=1,428) census tract was assessed using adaptive-bandwidth kernel density estimation. Density surfaces were constructed from DC (n=743) and DC MSA (n=4,539) geocoded tobacco retailers. Sociodemographics were obtained from the 2011-2015 American Community Survey. Spearman's correlations between sociodemographics and retail density were computed to account for spatial autocorrelation. Bivariate and multivariate spatial lag models were fit to predict retail density. Results: DC and DC MSA neighborhoods with a higher percentage of Hispanics were positively correlated with retail density (rho = .3392, P = .0001 and rho = .1191, P = .0000, respectively). DC neighborhoods with a higher percentage of African Americans were negatively correlated with retail density (rho = -.3774, P = .0000). This pattern was not significant in DC MSA neighborhoods. Bivariate and multivariate spatial lag models found a significant inverse relationship between the percentage of African Americans and retail density (Beta = -.0133, P = .0181 and Beta = -.0165, P = .0307, respectively). Conclusions: Associations between neighborhood sociodemographics and retail density were significant, although findings regarding African Americans are inconsistent with previous findings. Future studies should analyze other geographic areas, and account for spatial autocorrelation within their analytic framework.

Impact of e-cigarette and cigarette prices on youth and young adult e-cigarette and cigarette behaviour: evidence from a national longitudinal cohort.

INTRODUCTION: Understanding the impact of prices for tobacco and nicotine products is critical for creating policies to prevent use among young people. This study examines the impact of electronic cigarette (e-cigarette) and cigarette prices on current e-cigarette and cigarette use among youth and young adults. METHODS: Data were from a national probability-based sample aged 15-21 collected in 2014 and followed every 6 months for 2.5 years through 2016. We conducted separate conditional likelihood logistic regression models with past 30-day e-cigarette use and past 30-day cigarette use outcomes on the sample of individuals who participated in at least two survey waves (n=11 578) with linked Nielsen market-level price data for rechargeable e-cigarettes and cigarettes. Models controlled for time-varying variables at the individual and state policy levels, and fixed effects at the individual, wave and market levels. RESULTS: Higher cigarette prices were associated with increased past 30-day e-cigarette use, indicating e-cigarettes may serve as a substitute for cigarettes. We did not find a statistically significant relationship between rechargeable e-cigarette prices and past 30-day e-cigarette use; neither did we find a significant relationship between rechargeable e-cigarette prices and past 30-day cigarette smoking. CONCLUSION: This is the first study to examine e-cigarette and cigarette prices on e-cigarette and cigarette behaviour longitudinally among young people. Findings suggest the need for better measuring the costs associated with e-cigarette use among this population, as well as a careful assessment of price and tax policies that takes into account cross-product impact to sufficiently discourage e-cigarette and cigarette use among young people.

History and Current Trends in the Electronic Cigarette Retail Marketplace in the United States: 2010-2016.

INTRODUCTION: The US market for electronic nicotine delivery systems (ENDS) has grown rapidly in the last decade. There is limited published evidence examining changes in the ENDS marketplace prior to the US Food and Drug Administration's (FDA) deeming rule in 2016. This study describes US ENDS retail market trends from 2010 to 2016. METHODS: National data were obtained from Nielsen retail scanners for five product types: (1) disposables, (2) rechargeables, (3) cartridge replacements, (4) e-liquid bottle refills, and (5) specialty vapor products. We examined dollar sales, volume, price, brand, and flavor. RESULTS: Adjusted national sales increased from $11.6 million in 2010 to $751.2 million in 2016. The annual rate of sales growth rapidly increased before slowing through 2015. The rate of growth spiked in 2016. Market share for menthol products and other assorted flavors increased from 20% in 2010 to 52.1% by 2016. NJOY's early market dominance shifted as tobacco industry brands entered the market and eventually captured 87.8% of share by 2016. Rechargeables and accompanying products comprised an increased proportion of total volume sold over time while disposable volume declined. Specialty vapor products appeared at retail in 2015. CONCLUSIONS: Findings show strong early growth in the ENDS retail market followed by considerable slowing over time, despite a slight uptick in 2016. Trends reflect shifts to flavored products, newer generation "open-system" devices, lower prices, and tobacco industry brands. This study provides a baseline against which to compare the impact of FDA's 2016 deeming rule and future actions on the ENDS marketplace. IMPLICATIONS: This study uses market scanner data from US retail outlets to describe trends in the ENDS retail market from 2010 to 2016, providing a baseline against which to compare the impact of FDA's 2016 deeming rule and future actions on the ENDS marketplace. Understanding historical market trends is valuable in assessing how future regulatory efforts and advances in ENDS technology may impact industry response and consumer uptake and use.

Examining differences in cigarette smoking prevalence among young adults across national surveillance surveys.

Accurate smoking prevalence data is critical for monitoring, surveillance, and evaluation. However, estimates of prevalence vary across surveys due to various factors. This study examines smoking prevalence estimates for 18-21 year olds across six U.S. national telephone, online and in-person surveys for the years 2013 and 2014. Estimates of ever smoking ranged from 35% to 55%. Current smoking ranged from 16% to 30%. Across the three modalities, household surveys were found to yield the highest estimates of smoking prevalence among 18 to 21 year olds while online surveys yielded the lowest estimates, and this was consistent when stratifying by gender and race/ethnicity. Assessments of the joint effect of gender, race/ethnicity, educational attainment and survey mode indicated that the relative differences in the likelihood of smoking were consistent across modes for gender and education groups. However, the relative likelihood of smoking among minority groups compared with non-Hispanic Whites varied across modes. Gender and racial/ethnic distributions for most surveys significantly differed from the U.S. Census. Over and underrepresentation of certain demographic subpopulations, variations in survey question wording, and social desirability effects may explain modality differences in smoking estimates observed in this study. Further research is needed to evaluate the effect of survey mode on variation in smoking prevalence estimates across national surveys, particularly for young adult populations.

Patterns of E-Cigarette Use Among Youth and Young Adults: Review of the Impact of E-Cigarettes on Cigarette Smoking.

There is concern that e-cigarette use among youth and young adults (YAs) may lead to future cigarette or other combustible tobacco product use. A synthesis of the literature on this topic is needed because existing longitudinal studies are limited in number and not consistent in their conclusions. We conducted a search in PubMed through December 31, 2017 for peer-reviewed studies related to e-cigarette patterns of use. Of 588 relevant studies, 26 had a youth or YA sample, were longitudinal in design, and assessed e-cigarette use at baseline and cigarette smoking at follow-up. Most studies followed a sample over time and compared cigarette smoking at follow-up between baseline e-cigarette users and nonusers. Other studies examined the difference at follow-up in cigarette smoking status among smokers according to e-cigarette use at baseline. Results suggest that, among never smokers, e-cigarette use is associated with the future (6 months to 2.5 years) cigarette trial; however, firm conclusions cannot be drawn because of limitations including small sample size, measurement of experimental use (ie, ever use, past 30-day use) rather than established use, and inadequate controls for potentially confounding variables. Conclusions also cannot be drawn from studies examining the impact of e-cigarette use among smokers due to the limited number of studies and additional limitations. A comprehensive understanding of this literature is needed to inform policy makers and consumers for evidence-based decision-making and to guide future research on e-cigarette use among youth and young adults. IMPLICATIONS: The present article provides a review of the impact of e-cigarette use on subsequent cigarette smoking among youth and YAs. Studies presented here suggest that e-cigarette use among nonsmokers is associated with subsequent cigarette smoking, but study designs are subject to numerous limitations. Future research should focus on addressing the characteristics that put youth and YAs at the risk of using either product and how appeal and accessibility of these products are related to product use in order to inform future policy-making.

A multidisciplinary approach to health campaign effectiveness.

Campaign costs are rising, making ad execution testing more critical to determine effectiveness prior to media spending. Premarket testing occurs prior to messages' airing while in-market testing examines message attributes when messages are aired within a real-world setting, where context plays an important role in determining audience response. These types of ad testing provide critical feedback to help develop and deploy campaigns. Due to recent changes in media delivery platforms and audience tobacco use behavior, this study analyzes two nationally representative youth samples, aged 15-21, to examine if pre-market ad testing is an indicator of in-market ad performance for public health campaigns, which rely on persuasive messages to promote or reduce health behaviors rather than selling a product. Using data from the Truth® campaign, a national tobacco use prevention campaign targeted to youth and young adults, findings indicate strong associations between pre-market scores and in-market ad performance metrics.