Awareness and use of short-fill e-liquids by youth in England in 2021: findings from the ITC Youth Tobacco and Vaping Survey
Bibliographic record
Abstract
BACKGROUND: Refillable e-cigarettes were popular among youth in England in 2021. The UK Tobacco and Related Products Regulations (TRPR) limits e-liquids to 20 mg/mL of nicotine in a 10 mL bottle. Short-fill e-liquids, which are not covered by TRPR regulations, are typically nicotine-free and come in larger, underfilled bottles allowing customisation with the addition of 'nicotine shots'. This paper investigates awareness, use, and reasons for use of short-fill e-liquids among youth in England. METHODS: Data are from the online 2021 International Tobacco Control Youth Survey, comprising 4224 youth (aged 16-19 years) in England. Weighted logistic regression models investigated associations between awareness and past 30-day use of short-fills by smoking status, vaping status, nicotine strength vaped and participant demographics. Reasons for use were also reported. RESULTS: Approximately one-quarter (23.0%) of youth in England reported awareness of short-fill e-liquids. Among youth who had vaped in the past 30 days, 22.1% had used short-fills in the past 30 days; use was most prevalent among those who were also smoking (43.2%) and those who reported usually vaping nicotine concentrations of 2.1% (21 mg/mL) or more (40.8%). 'Convenience of a bigger bottle' was the most selected reason for use (45.0%), followed by 'less expensive than regular e-liquids' (37.6%). CONCLUSIONS: Awareness of short-fills was common among youth in 2021, including among those who had never vaped or smoked. Among youth who vaped in the past 30 days, short-fill use was more prevalent among those who also smoked and those who vaped nicotine-containing e-liquids. Integration of short-fill products into existing e-cigarette regulations should be considered.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".