Dataset Information

An electronic, smart lighter to measure cigarette smoking: A pilot study to assess feasibility and initial validity.

ABSTRACT: Understanding variability in smoking patterns may inform smoking cessation interventions. Retrospective reports of cigarettes smoked per day may be biased and typically do not provide temporal precision regarding when cigarettes are smoked. However, real-time, user-initiated tracking, such as logging each time a cigarette is smoked, can be burdensome over long time frames. In this study, adult, non-treatment seeking daily smokers (N?=?22) used an electronic, smart lighter to light and timestamp cigarettes for 14?days. Participants reported number of cigarettes smoked per day (CPD) via a mobile device (daily diary) and retrospectively reported CPD at the end of the study using the Timeline Followback (TLFB). Self-reported lighter satisfaction and adherence varied with 68% of participants reporting that they liked using the lighter and participants reporting using the lighter for 92% of cigarettes smoked, on average. Lighter-estimated CPD did not differ from daily diary-estimated CPD, but was significantly lower than TLFB estimates. The lighter resulted in greater day-to-day variability relative to other methods and fewer rounded cigarette counts (digit bias) relative to the TLFB. The lighter appears to be feasible for capturing data on smoking patterns in daily smokers. Though false positive cigarettes are likely low, additional technologies that augment data captured from the lighter may be necessary to reduce false negatives (missed cigarettes) and alternative lighter designs may appeal more to certain smokers.

SUBMITTER: Tomko RL

PROVIDER: S-EPMC6708757 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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An electronic, smart lighter to measure cigarette smoking: A pilot study to assess feasibility and initial validity.

Tomko Rachel L RL McClure Erin A EA Cato Patrick A PA Wang Julie B JB Carpenter Matthew J MJ Karelitz Joshua L JL Froeliger Brett B Saladin Michael E ME Gray Kevin M KM

Addictive behaviors 20190715

Understanding variability in smoking patterns may inform smoking cessation interventions. Retrospective reports of cigarettes smoked per day may be biased and typically do not provide temporal precision regarding when cigarettes are smoked. However, real-time, user-initiated tracking, such as logging each time a cigarette is smoked, can be burdensome over long time frames. In this study, adult, non-treatment seeking daily smokers (N = 22) used an electronic, smart lighter to light and timestamp ...[more]

PMID: 31415971

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Project description:BackgroundElectronic 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.MethodsA 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 14-17 years 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.ResultsExploratory 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.ConclusionsA 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.

Project description:Background: The microbiome is increasingly being linked to cancer risk. Little is known about the lung and oral cavity microbiomes in healthy smokers (SM), and even less for electronic cigarette (EC) users, compared healthy never-smokers (NS). Methods: In a cross-sectional pilot study of SM (N=8), EC users (N=10) and NS (N=10) saliva and bronchoscopy-collected bronchoalveolar lavage samples were collected. Bacteria species were identified through metatranscriptome profiling by RNA-sequencing to study associations with the lung and oral microbiome. Pairwise comparisons and linear modeling was assessed with false discovery rates <0.1. Results: Total bacterial load was similar for the SM, EC users and NS, and there was no differences in the bacterial diversity across groups. In the lung, there were 44 bacterial species that were statistically significantly different for SM/NS, 80% of which were decreased in the SM. There were 12 bacterial species that were different for SM/EC users, all of which were decreased, 10 of which were also identified in the SM/NS comparison. The 2 bacterial species unique to SM/EC comparison were Neisseria sp. KEM232 and Curvibacter sp. AEP1-3. From the top 5 decreased species in SM/EC, 3 were also identified in the SM/NS comparison (Neisseria elongata, Neisseria sicca, and Haemophilus parainfluenzae) and 2 of these were unique to the SM/EC comparison (Neisseria zoodegmatis and Ottowia sp. oral taxon 894). There were 8 species increased in SM compared to NS, none of which are known to be clinically significant. In the oral microbiome, 152 bacteria species were differentially abundant for the SM/NS analysis, and only 17 for the EC/NS comparison, all which were also present in SM/NS comparisons. There were 21 bacteria that were differentially abundant in both the lung and oral cavity for SM and NS, 95% also were decreased in the SM. Conclusion: Smoking and EC use do not appear to materially affect the lung microbiome, although differences are noted of unclear clinical significance. Most differentially abundant bacteria decreased, which may be due to a toxic effect of cigarette smoke, including a change in humidity or heating. Given the low number of overlapping oral and lung microbes, the oral microbiome does not appear to be a good surrogate for smoking-related effects in the lung.

Project description:ImportanceMany studies have reported a positive association of youth electronic cigarette (e-cigarette) use with subsequent cigarette smoking initiation, but it remains unclear whether e-cigarette use is associated with continued cigarette smoking after initiation.ObjectiveTo assess the association of youth baseline e-cigarette use with their continued cigarette smoking 2 years after initiation.Design, setting, and participantsThe Population Assessment of Tobacco and Health (PATH) Study is a national longitudinal cohort study. This sample consisted of youth who participated in waves 3, 4, and 5 of the study (wave 3 was from October 2015 to October 2016, wave 4 was from December 2016 to January 2018, and wave 5 was from December 2018 to November 2019) and had never used cigarettes (cigarette-naive) by wave 3. The current analysis used multivariable logistic regressions in August 2022 to assess the association between e-cigarette use among cigarette-naive adolescents aged 12 to 17 years in 2015 and 2016 and subsequent continued cigarette smoking. PATH uses audio computer-assisted self-interviewing and computer-assisted personal interviewing to collect data.ExposuresEver and current (past 30-day) use of e-cigarettes in wave 3.Main outcomes and measuresContinued cigarette smoking in wave 5 after initiating smoking in wave 4.ResultsThe current sample included 8671 adolescents who were cigarette naive in wave 3 and also participated in waves 4 and 5; 4823 of the participants (55.4%) were aged 12 to 14 years, 4454 (51.1%) were male, and 3763 (51.0%) were non-Hispanic White. Overall, regardless of e-cigarette use, few adolescents (362 adolescents [4.1%]) initiated cigarette smoking at wave 4, and even fewer (218 participants [2.5%]) continued smoking at wave 5. Controlling for multiple covariates, the adjusted odds ratio of baseline ever e-cigarette use, compared with never e-cigarette use, was 1.81 (95% CI, 1.03 to 3.18) for continued smoking measured as past 30-day smoking at wave 5. However, the adjusted risk difference (aRD) was small and not significant. The aRD was 0.88 percentage point (95% CI, -0.13 to 1.89 percentage points) for continued smoking, with the absolute risk being 1.19% (95% CI, 0.79% to 1.59%) for never e-cigarette users and 2.07% (95% CI, 1.01% to 3.13%) for ever e-cigarette users. Similar results were found using an alternative measure of continued smoking (lifetime ≥100 cigarettes and current smoking at wave 5) and using baseline current e-cigarette use as the exposure measure.Conclusions and relevanceIn this cohort study, absolute and relative measures of risks yielded findings suggesting very different interpretations of the association. Although there were statistically significant odds ratios of continued smoking comparing baseline e-cigarette users with nonusers, the minor risk differences between them, along with the small absolute risks, suggest that few adolescents are likely to continue smoking after initiation regardless of baseline e-cigarette use.

Project description:ImportanceThe electronic cigarette (EC) has become popular among smokers who wish to reduce their tobacco use levels or quit smoking, but its effectiveness as a cessation aid is uncertain.ObjectiveTo examine the association of regular EC use with the number of cigarettes smoked per day, smoking cessation among current smokers, and smoking relapse among former smokers.Design, setting, and participantsThe CONSTANCES (Consultants des Centres d'Examens de Santé) cohort study, based in France, began recruiting participants January 6, 2012, and is currently ongoing. Participants were enrolled in CONSTANCES through 2015, and included 5400 smokers (mean [SD] follow-up of 23.4 [9.3] months) and 2025 former smokers (mean [SD] follow-up of 22.1 [8.6] months) at baseline who quit smoking in 2010, the year in which ECs were introduced in France, or afterward. Analyses were performed from February 8, 2017, to October 15, 2018.Main outcomes and measuresThe association between EC use and the number of cigarettes smoked during follow-up was studied using mixed regression models. The likelihood of smoking cessation was studied using Poisson regression models with robust sandwich variance estimators. The association between EC use and smoking relapse among former smokers was studied using Cox proportional hazards regression models. All statistical analyses were adjusted for sociodemographic characteristics, duration of follow-up, and smoking characteristics.ResultsAmong the 5400 daily smokers (2906 women and 2494 men; mean [SD] age, 44.9 [12.4] years), regular EC use was associated with a significantly higher decrease in the number of cigarettes smoked per day compared with daily smokers who did not use ECs (-4.4 [95% CI, -4.8 to -3.9] vs -2.7 [95% CI, -3.1 to -2.4]), as well as a higher adjusted relative risk of smoking cessation (1.67; 95% CI, 1.51-1.84]). At the same time, among the 2025 former smokers (1004 women and 1021 men; mean [SD] age, 43.6 [12.1] years), EC use was associated with an increase in the rate of smoking relapse among former smokers (adjusted hazard ratio, 1.70; 95% CI, 1.25-2.30).Conclusions and relevanceThis study's findings suggest that, among adult smokers, EC use appears to be associated with a decrease in smoking level and an increase in smoking cessation attempts but also with an increase in the level of smoking relapse in the general population after approximately 2 years of follow-up.

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An electronic, smart lighter to measure cigarette smoking: A pilot study to assess feasibility and initial validity.

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An electronic, smart lighter to measure cigarette smoking: A pilot study to assess feasibility and initial validity.

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