Changes in electronic cigarette use and label awareness among smokers before and after the European Tobacco Products Directive implementation in six European countries: findings from the EUREST-PLUS ITC Europe Surveys
Bibliographic record
Abstract
BACKGROUND: Article 20 of the European Tobacco Product Directive (TPD), which went into effect in May 2016, regulates electronic cigarettes (e-cigarettes) in the European Union (EU). The aim of this study was to evaluate changes in e-cigarette use, design attributes of the products used and awareness of e-cigarette labelling and packaging among smokers from six EU Member States (MS) before and after TPD implementation. METHODS: Data come from Wave 1 (2016, pre-TPD) and Wave 2 (2018, post-TPD) of the ITC Six European Country Survey among a sample of smokers and recent quitters who use e-cigarettes from six EU MS. Weighted logistic generalized estimating equations regression models were estimated to test the change in binary outcomes between Waves 1 and 2 using SAS-callable SUDAAN. RESULTS: In 2018, current daily/weekly e-cigarette use among adult smokers was just over 2%, but this varied from the highest in Greece (4%) to lowest in Poland (1.2%). From Waves 1 to 2, there was a significant increase in respondents reporting noticing and reading health and product safety information on leaflets inside e-cigarette packaging (8.39-11.62%, P < 0.001). There were no significant changes between waves of respondents reporting noticing or reading warning labels on e-cigarette packages/vials. CONCLUSIONS: e-cigarette use among smokers in these six EU countries is low. Although reported noticing and reading leaflets included in the packaging of e-cigarettes increased significantly from before to after the TPD, there was no significant change in reported noticing and reading of warning labels. Findings indicate the importance of continued monitoring of TPD provisions around e-cigarettes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".