scholarly journals Compliance in Controlled E-cigarette Studies

Author(s):  
Meghan E Rebuli ◽  
Feifei Liu ◽  
Robert Urman ◽  
Jessica L Barrington-Trimis ◽  
Sandrah P Eckel ◽  
...  

Abstract Introduction E-cigarette studies have found that the use of a variety of flavors and customizable devices results in greater use frequency and user satisfaction. However, standardized research e-cigarettes are being developed as closed systems with limited flavor options, potentially limiting user satisfaction. In this study, we explore protocol compliance in an e-cigarette study using a standardized, assigned device with puff time and duration tracking (controlled e-cigarette) and potential limitations that controlled devices and e-liquids can introduce. Methods In a crossover study, 49 young adult e-cigarette users were recruited using convenience sampling and assigned a controlled e-cigarette device and flavored or unflavored e-liquids on standardized protocols. E-cigarette use frequency (number of puffs per day, collected from the device) and serum cotinine levels were obtained at each of three study visits over 3 weeks. The correlation of cotinine and e-cigarette use over the preceding week was calculated at each study visit. Results Correlation of nicotine intake, as measured by serum cotinine, and puff time, as measured by puffs count and duration from the e-cigarette device, as an indicator of study protocol compliance, substantially declined after the first week of the study and were no longer correlated in the remaining study weeks (R2 = 0.53 and p ≤ .01 in week 1, R2 < 0.5 and p > .05 for remaining weeks). Conclusions There is an emerging need for controlled e-cigarette exposures studies, but low compliance in the use of assigned devices and e-liquids may be a limitation that needs to be mitigated in future studies. Implications This study is the first to analyze compliance with instructions to use a standardized e-cigarette device with puff time and duration tracking (controlled e-cigarette) across all subjects and an assigned e-liquid flavor over a 3-week period. We find that protocol compliance, as measured by correlations between e-cigarette use measures and cotinine levels, was only achieved in the first week of the study and declined thereafter. These findings indicate that the assignment of a study device and instruction to only use the study device with assigned e-liquid flavor may not be sufficient to ensure participant compliance with the study protocol. We suggest that additional measures, including behavioral and biological markers, are needed to ensure sole use of the study e-cigarette and e-liquid and to be able to interpret results from controlled e-cigarette studies.

Author(s):  
Carla J Berg ◽  
Xuejing Duan ◽  
Katelyn Romm ◽  
Kim Pulvers ◽  
Daisy Le ◽  
...  

Abstract Introduction E-cigarette cessation intervention research is limited. Young adult e-cigarette use and cessation is particularly nuanced, given various user profiles (i.e., polytobacco use, co-use with marijuana) warranting different intervention approaches. Methods The current study is an analysis of baseline survey data (collected September-December, 2018) among 1,133 young adult (ages 18-34) e-cigarette users in a 2-year longitudinal study. We examined: 1) e-cigarette user profiles (i.e., e-cigarette only; e-cigarette/other tobacco; e-cigarette/marijuana; e-cigarette/other tobacco/marijuana); and 2) correlates of readiness to quit e-cigarette use in the next 6 months and past-year e-cigarette quit attempts. Results In this sample (Mage=23.91, 47.3% male, 35.5% sexual minority, 75.2% White, 13.7% Hispanic), e-cigarette user profiles were: 16.8% e-cigarettes-only, 23.4% e-cigarette/other tobacco, 18.0% e-cigarette/marijuana, and 41.8% e-cigarette/other tobacco/marijuana. Multinomial logistic regression (referent: e-cigarette-only use) indicated that all polyuse groups were more likely to use high-nicotine e-liquids (containing ≥9 mg of nicotine). Other predictors included: e-cigarettes/other tobacco users being older and male; e-cigarettes/marijuana users using closed systems; and e-cigarettes/other tobacco/marijuana users being sexual minority (p’s<.01). Readiness to quit e-cigarettes and past-year quit attempts were reported by 20.8% and 32.3%, respectively. Per multilevel regression, readiness to quit and quit attempts correlated with using fewer days, high-nicotine e-liquids, and closed systems, but not marijuana, as well as being heterosexual and Black (vs. White); readiness to quit also correlated with being single; past-year quit attempts correlated with other tobacco use and being Hispanic. Conclusions Young adult e-cigarette users demonstrate distinct user profiles and cessation-related experiences that should be considered in developing cessation interventions. Implications The vast majority of young adult e-cigarette users use other tobacco products and marijuana. Unfortunately, few reported readiness to quit or attempting quit. Moreover, certain subgroups (e.g., sexual/racial/ethnic minorities) are more likely to be ready or attempt to quit, but may not be successful. Vaping cessation interventions must attend to these nuances.


JAMA Oncology ◽  
2020 ◽  
Vol 6 (6) ◽  
pp. 923 ◽  
Author(s):  
Helen M. Parsons ◽  
Patricia I. Jewett ◽  
Karim Sadak ◽  
Lucie M. Turcotte ◽  
Rachel I. Vogel ◽  
...  

Author(s):  
Nkiruka C. Atuegwu ◽  
Cheryl Oncken ◽  
Reinhard C. Laubenbacher ◽  
Mario F. Perez ◽  
Eric M. Mortensen

E-cigarette use is increasing among young adult never smokers of conventional cigarettes, but the awareness of the factors associated with e-cigarette use in this population is limited. The goal of this work was to use machine learning (ML) algorithms to determine the factors associated with current e-cigarette use among US young adult never cigarette smokers. Young adult (18–34 years) never cigarette smokers from the 2016 and 2017 Behavioral Risk Factor Surveillance System (BRFSS) who reported current or never e-cigarette use were used for the analysis (n = 79,539). Variables associated with current e-cigarette use were selected by two ML algorithms (Boruta and Least absolute shrinkage and selection operator (LASSO)). Odds ratios were calculated to determine the association between e-cigarette use and the variables selected by the ML algorithms, after adjusting for age, gender and race/ethnicity and incorporating the BRFSS complex design. The prevalence of e-cigarette use varied across states. Factors previously reported in the literature, such as age, race/ethnicity, alcohol use, depression, as well as novel factors associated with e-cigarette use, such as disabilities, obesity, history of diabetes and history of arthritis were identified. These results can be used to generate further hypotheses for research, increase public awareness and help provide targeted e-cigarette education.


Author(s):  
Grace C. Hillyer ◽  
Meaghan Nazareth ◽  
Sarah Lima ◽  
Karen M. Schmitt ◽  
Andria Reyes ◽  
...  

2008 ◽  
Vol 33 (5) ◽  
pp. 668-674 ◽  
Author(s):  
Emily L.R. Harrison ◽  
Sherry A. McKee
Keyword(s):  

2018 ◽  
Vol 21 (5) ◽  
pp. 691-694 ◽  
Author(s):  
Mary F Brunette ◽  
Joelle C Ferron ◽  
Pamela Geiger ◽  
Andrea C Villanti

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