Examining E-Cigarette Purchases and Cessation in a Consumer Panel of Smokers
Bibliographic record
Abstract
OBJECTIVES: Examine correlates of initiation of e-cigarette use among smokers and determine the impact of e-cigarette use on cessation among smokers in a national U.S. consumer panel. METHODS: This study used the Nielsen Homescan Panel data from 2011 to 2013, augmented with state-specific measures of tobacco control activities, to examine 1) correlates of single and repeat e-cigarette purchasing among panelists currently purchasing cigarettes; and 2) correlates of "cessation". Participating panelists scanned all retail purchases, and Nielsen recorded over 3 million product types. The key explanatory variable for cessation was e-cigarette purchase. Parallel analysis was conducted for conventional nicotine replacement therapy (NRT) purchase. Cessation was defined as no purchases for at least 6 months and no subsequent purchases until the end of 2013. Analysis was conducted in 2015. E-cigarettes tracked by Nielsen during this period were cig-a-like products resembling tobacco cigarettes in appearance. RESULTS: Single e-cigarette purchase was associated with whether the panelist resided in a single person male household and bought a higher volume of cigarettes. Repeat purchase was associated with higher state cigarette taxes, less stringent state public smoke-free policies, lower cigarette prices, and more frequent cigarette purchasing. Cessation was associated with repeat e-cigarette purchasing, repeat NRT purchasing, younger age, lower monthly cigarette volume, less frequent purchasing of cigarettes, less recent cigarette purchase at baseline, and single e-cigarette purchase before baseline. CONCLUSIONS: Both individual and policy variables were associated with e-cigarette use. Repeat e-cigarette purchase was associated with cigarette purchase discontinuation, as were various smoking intensity measures.
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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 | 0.002 | 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".