Purchasing and sourcing of e-cigarettes among youth in Scotland and England following Scotland’s implementation of an e-cigarette retail register and prohibition of e-cigarette sales to under-18s
Bibliographic record
Abstract
BACKGROUND. Scotland implemented new e-cigarette regulations in April 2017 prohibiting sales to under-18s, requiring age verification, and requiring retailer registration. This study examined purchasing and sourcing of e-cigarettes among minors aged 16-17, and youth aged 18-19, in the short- (4 months) and longer-term (16 months) after regulations were implemented, compared with England. METHODS. Data were from the July/August 2017 and August/September 2018 cross-sectional online ITC Youth Tobacco and Vaping Surveys of 16- to 19-year-olds in Scotland (n2017/2018=434/377) and England (n2017/2018=3,791/3,743). Logistic regressions were used to examine differences in past-12-month purchasing, past-12-month sale refusal, and past-30-day sourcing of e-cigarettes between 2017 and 2018, by country and age group. RESULTS. Among vapers aged 16-17 in Scotland, from 4 to 16 months post-regulations, e-cigarette purchasing increased from 21% to 50% and sale refusal increased from 14% to 16%, but these changes were not significant and did not differ from changes observed in 18-19-year-olds or England (p>.05). Purchasing and sale refusal were most common in vape shops. Purchasing from a vape shop increased among vapers aged 16-17 in Scotland from 4 to 16 months post-regulations (17% to 85%, p=.003) but not among 18-19-year-olds or in England (p>.05). Among past-30-day vapers, social sources were most common. CONCLUSIONS. Youth vapers in Scotland showed no significant changes in overall purchasing, sale refusal, or sourcing of e-cigarettes, from 4 to 16 months post-regulations, and changes did not differ by age group or from England. Findings suggest low compliance with age-of-sale regulations in Scotland and England.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".