Concurrent E-Cigarette Use During Tobacco Dependence Treatment in Primary Care Settings: Association With Smoking Cessation at Three and Six Months
Bibliographic record
Abstract
INTRODUCTION: Electronic cigarettes (e-cigarettes) are being used as cessation aids by many smokers despite a lack of empirical evidence regarding their safety and efficacy. We analyzed the association of e-cigarette use and smoking abstinence in a population of smokers accessing standard smoking cessation treatment (nicotine replacement therapy [NRT] plus behavioral counseling) through primary care clinics in Ontario, Canada. METHODS: Participants were recruited through 187 primary care clinics across Ontario, Canada and were eligible for up to 26 weeks of brief behavioral counseling and individualized dosing of NRT at no cost. Adjusted logistic regression models were used to examine the association between concurrent e-cigarette use and smoking abstinence at 3- and 6-month follow-ups. RESULTS: Of the 6526 participants who completed a 3-month follow-up, 18.1% reported using an e-cigarette while in treatment. The majority of e-cigarette users (78.2%) reported using an e-cigarette for smoking cessation. At 3-month follow-up, e-cigarette use was negatively associated with abstinence after controlling for confounders (adjusted odds ratio [AOR] = 0.706, p < .001, 95% confidence interval [CI] = 0.607-0.820). E-cigarette use was also negatively associated with abstinence at 6-month follow-up (AOR = 0.502, p < .001, 95% CI = 0.393-0.640). CONCLUSION: E-cigarette use was negatively associated with successful quitting in this large community sample of smokers accessing standard evidence-based smoking cessation treatment through primary care clinics, even after adjusting for covariates such as severity of tobacco dependence, gender, and age. The findings suggest that concurrent use of e-cigarettes with NRT may harm cessation attempts. IMPLICATIONS: This study confirms previous findings from observational studies regarding the negative association between e-cigarette use and smoking cessation, but in a large cohort of smokers enrolled in an evidence-based treatment program. The implications of these findings are that concurrent use of e-cigarettes during a quit attempt utilizing cost-free evidence-based treatment (NRT plus behavioral counseling) does not confer any added benefit and may hamper successful quitting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".