Marketing claims on the websites of leading e-cigarette brands in England
Bibliographic record
Abstract
INTRODUCTION: Exposure to electronic cigarette (EC) marketing is associated with EC use, particularly among youth. In England, the Tobacco and Related Products Regulations and Committee of Advertising Practice (CAP) regulate EC marketing to reduce appeal to youth; however, there are little published data on EC marketing claims used online. This study therefore provides an overview of marketing claims present on the websites of EC brands popular in England. METHODS: From January to February 2022, a content analysis of 10 of England's most popular EC brand websites was conducted, including violation of CAP codes. RESULTS: Of the 10 websites, all presented ECs as an alternative to smoking, 8 as a smoking cessation aid and 6 as less harmful than smoking. Four websites presented ECs as risk-free. All mentioned product quality, modernity, convenience, sensory experiences and vendor promotions. Nine featured claims about flavours, colours, customisability and nicotine salts. Seven featured claims concerning social benefits, personal identity, sustainability, secondhand smoke and nicotine strength. Six featured claims about fire safety. Some claimed ECs are cheaper than tobacco (n=5), cited health professionals (n=4) or featured collaborations with brands/icons (n=4). All were assessed by the research team to violate one or more CAP code(s) by featuring medicinal claims (n=8), contents which may appeal to non-smokers (n=7), associations with youth culture (n=6), depictions of youth using ECs (n=6) or media targeting youth (n=5). CONCLUSION: Among 10 top EC brand websites in England, marketing elements that might appeal to youth were commonly identified and CAP code compliance was low.
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 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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".