U.S. Youth Use of the BIDI ® Stick Disposable E-Cigarette: The Importance of Establishing Device Specific Prevalence Data in Regulating Electronic Nicotine Delivery Systems (ENDS)
Bibliographic record
Abstract
Abstract Background In the light of the finding from the 2022 U.S. National Youth Tobacco Survey that disposable e-cigarette devices are the most widely used e-cigarette devices amongst U.S. youth use there is an important need to identify which disposable devices may be driving that increase. In this paper we report the results of research designed to estimate the prevalence of youth and underage young adult use of one of the leading disposable e-cigarette brands currently on sale within the U.S. Methods Crosssectional online survey of a nationally representative sample of 1,215 youth (1317 years) recruited via the IPSOS probability-based KnowledgePanel and 3,370 young adults aged 18 to 24 - amongst whom 1,125 were aged 18 to 20. Results Amongst youth aged 13 to 17, 0.91% [95% CI: 0.44–1.68] reported having ever used a BIDI® Stick branded product and 0.04% [95% CI: 0.00-0.38] reported currently using a BIDI® Stick branded product. Amongst those young adults aged 18 to 20, 3.90% [95% CI: 2.49–5.81] reported having ever used a BIDI® Stick product whilst 0.60% [95% CI: 0.17–1.55] reported they now use a BIDI® Stick product “every day” or “some days”. Conclusions The low prevalence of youth and underage adult current use of the BIDI® Stick ecigarette suggests that this product is not responsible for the recent growth in the use of disposable e-cigarettes by youth within the U.S. as demonstrated by the 2022 National Youth Tobacco Survey.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".