Use of ‘Elf Bar’ among youth and young adults who currently vape in England: cross‐sectional associations with demographics, dependence indicators and reasons for use
Bibliographic record
Abstract
BACKGROUND AND AIMS: Elf Bar is currently the leading e-cigarette (vape) brand in Great Britain. This study examined youth and young adults' use of Elf Bar, socio-demographic characteristics and dependence indicators and reasons for use over other brands. DESIGN: Cross-sectional survey. SETTING AND PARTICIPANTS: Online 2022 International Tobacco Control Project Youth Tobacco and Vaping Survey (N = 1355 16-29-year-olds in England who had vaped in the past 30 days). MEASUREMENTS: Currently using Elf Bar most often (versus other brands) and associations with: socio-demographics, owning a vaping device, dependence indicators and reasons for brand choice. Logistic regressions were used. FINDINGS: Among 16-29-year-olds who vaped in the past 30 days, 48.4% (n = 732) reported Elf Bar as the brand they used most often. Among 16-17-year-olds, 40.7% used Elf Bar over other brands; this was lower than among 18-19-year-olds (60.1%) and 20-29-year-olds (47.4%) (P ≤ 0.002). Using Elf Bar over other brands was higher among those who were female (55.2 versus 41.5% male), identified as White (53.1 versus 30.9% other/mixed), a student (54.5 versus 44.3% not), did not own a vape (66.7 versus 44.4% who did) and typically vaped 5-8 hours after waking (62.7 versus 36.8% within 5 min) (P ≤ 0.044). Most who vaped but had never smoked used Elf Bar (64.3%), although use did not significantly differ from those who currently (45.4%), formerly (42.3%) or experimentally (48.7%) smoked (all P ≥ 0.060). Popular reasons for choosing Elf Bar over other brands were better flavour/taste (47.5%), less expensive (28.7%), easier to get (26.1%), smoother to inhale (24.0%) and popularity (23.1%). 'Better for quitting smoking' (10.1%) was least frequently selected reason for choosing Elf Bar over other brands. CONCLUSIONS: Elf Bar brand e-cigarettes were used by approximately half of 16-29-year-olds who vaped in England in 2022 and was mainly chosen over other brands for subjective responses (e.g. flavour/taste), rather than for quitting smoking.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".