Electronic Cigarette Use among Irish Youth: A Cross Sectional Study of Prevalence and Associated Factors
Bibliographic record
Abstract
PURPOSE: To examine prevalence of, and factors associated with, e-cigarette use among young people aged 16-17 in Ireland. METHODS: In 2014, a representative sample of 821 young people aged 16-17 recruited from secondary schools completed a pen and paper survey on e-cigarette use, tobacco use, and socio-demographic items. FINDINGS: A total of 23.8% of respondents had used e-cigarettes at least once. Dual trial of tobacco and e-cigarettes was common with 69.5% of regular smokers and 30.4% of 'ever' smokers having tried e-cigarettes and 10.6% of current smokers using e-cigarettes regularly. 4.2% of never smokers have tried e-cigarettes. Overall, current e-cigarette use (once a month or more) was low (3.2%). Binary logistic regression conducted through generalized estimating equations (GEE) determined that controlling for other variables, current tobacco use and 'ever' tobacco use predicted ever e-cigarette use. Gender and school-level socioeconomic status were also independent predictors of ever e-cigarette use. Gender stood as the only predictor of on-going e-cigarette use, with males being more likely to regularly use e-cigarettes at least once a month. CONCLUSIONS: E-cigarette use among 16-17 year olds in Ireland is of note, with nearly a quarter of students having tried them. Concurrent or experimental use of e-cigarettes and tobacco is more common than sole use, while a small number have tried e-cigarettes without having tried tobacco.
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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 | 0.000 | 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".