Correlates of e-cigarette use among adults initiating smoking cessation treatment

A new statistical model for longitudinal ecological momentary assessment data on dual use of electronic and combustible cigarettes

Background: Existing studies of dual use of electronic and combustible cigarettes either collected longitudinal data with long gaps in between waves or conducted ecological momentary assessment (EMA) over a short period of time. In recent years, the measurement burst design that embeds an EMA protocol in each wave assessment of a traditional longitudinal study has become more popular and yet conventional generalized linear mixed models (GLMM) have important limitations for handling data from this design.Objectives: This study proposed a new statistical method to analyze data from the measurement burst design.Methods: This new statistical method was designed to model the short-term (within-wave) as well as long-term (between-wave) changes and was validated by a simulation study. Secondary analysis was conducted to analyze data from 205 dual users (52% male) and 146 exclusive smokers (50% male) who participated in a recent study using the measurement burst design.Results: The simulation study shows that the proposed method can handle the gap between waves well and is also robust to nonlinear changes across waves. Although no short-term change in smoking was found, dual users reported a long-term reduction in cigarette use that was more rapid compared to exclusive smokers (β ˆ = - 0.0127 , p = .0167 ). Vaping more was associated with smoking less (β ˆ = - 0.0058 , p = .0054 ).Conclusion: The proposed method is highly applicable as it can be easily implemented by substance use researchers and the results can be straightforwardly interpreted. The results suggest that e-cigarette use may play a role in promoting a long-term reduction in smoking among dual users.

Mobile contingency management for smoking cessation among socioeconomically disadvantaged adults: Protocol for a randomized trial

BACKGROUND

Smoking rates remain high among socioeconomically disadvantaged adults. Offering small escalating financial incentives for abstinence (i.e., contingency management [CM]), alongside clinic-based treatment dramatically increases cessation rates in this vulnerable population. However, innovative approaches are needed for those who are less able to attend office visits. The current study will evaluate an automated mobile phone-based CM approach that will allow socioeconomically disadvantaged individuals to remotely earn financial incentives for smoking cessation.

METHODS

The investigators have previously combined technologies, including 1) carbon monoxide monitors that connect with mobile phones to remotely verify abstinence, 2) facial recognition software to confirm identity during breath sample submissions, and 3) automated delivery of incentives triggered by biochemical abstinence confirmation. This automated CM approach will be evaluated in a randomized controlled trial of 532 low-income adults seeking cessation treatment. Participants will be randomly assigned to telephone counseling and nicotine replacement therapy (standard care [SC]) or SC plus mobile financial incentives (CM) for abstinence.

RESULTS

Biochemically-verified 7-day point prevalence abstinence at 26 weeks post-quit is the primary outcome. The cost-effectiveness of the interventions will be evaluated. Potential treatment mechanisms, including self-efficacy, motivation, and treatment engagement, will be explored to optimize future interventions.

DISCUSSION

Automated mobile CM may offer a low-cost approach to smoking cessation that can be combined with telephone counseling and pharmacological interventions. This approach represents a critical step toward the widespread dissemination of CM treatment to real-world settings, to reduce tobacco-related disease and disparities.

Incidence of Cigarette Smoking Relapse Among Individuals Who Switched to e-Cigarettes or Other Tobacco Products

IMPORTANCE

Although e-cigarettes are not approved as a cessation device, many who smoke believe that e-cigarettes will help them quit cigarette smoking successfully.

OBJECTIVE

To assess whether people who recently quit smoking and who had switched to e-cigarettes or another tobacco product were less likely to relapse to cigarette smoking compared with those who remained tobacco free.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study analyzed a nationally representative sample of US households that participated in 4 waves of the Population Assessment of Tobacco and Health Study (conducted 2013 through 2017), combining 2 independent cohorts each with 3 annual surveys. Eligible participants were individuals who smoked at baseline, had recently quit at the first follow-up, and completed the second follow-up survey.

EXPOSURES

Use of e-cigarettes or alternate tobacco products at follow-up 1 after recently quitting smoking.

MAIN OUTCOMES AND MEASURES

Weighted percentage of participants with over 12 months abstinence by follow-up 2.

RESULTS

Of a total of 13 604 participants who smoked cigarettes at baseline, 9.4% (95% CI, 8.7%-10.0%) recently had quit smoking (mean age, 41.9; 95% CI, 39.7-46.6 years; 641 [43.2%] women) Of these, 22.8% (95% CI, 19.7%-26.0%) had switched to e-cigarettes, with 17.6% (95% CI, 14.8%-20.5%) using them daily. A total of 37.1% (95% CI, 33.7%-40.4%) used a noncigarette tobacco product and 62.9% (95% CI, 59.6%-66.3%) were tobacco free. Rates of switching to e-cigarettes were highest for those who were in the top tertile of tobacco dependence (31.3%; 95% CI, 25.0%-37.7%), were non-Hispanic White (26.4%; 95% CI, 22.3%-30.4%), and had higher incomes (annual income ≥$35 000, 27.5%; 95% CI, 22.5%-32.4% vs <$35 000, 19.3%; 95% CI, 16.3%-22.3%). At follow-up 2, unadjusted relapse rates were similar among those who switched to different tobacco products (for any tobacco product: successfully quit, 41.5%; 95% CI, 36.2%-46.9%; relapsed with significant requit, 17.0%; 95% CI, 12.4%-21.6%; currently smoking, 36.2%; 95% CI, 30.9%-41.4%). Controlled for potential confounders, switching to any tobacco product was associated with higher relapse rate than being tobacco free (adjusted risk difference, 8.5%; 95% CI, 0.3%-16.6%). Estimates for those who switched to e-cigarettes, whether daily or not, were not significant. While individuals who switched from cigarettes to e-cigarettes were more likely to relapse, they appeared more likely to requit and be abstinent for 3 months at follow-up 2 (17.0%; 95% CI, 12.4%-21.6% vs 10.4%; 95% CI, 8.0%-12.9%).

CONCLUSIONS AND RELEVANCE

This large US nationally representative study does not support the hypothesis that switching to e-cigarettes will prevent relapse to cigarette smoking.