E-cigarette and tobacco product use among NYS youth before and after a state-wide vaping flavour restriction policy, 2020–2021
Bibliographic record
Abstract
SIGNIFICANCE: Reducing youth e-cigarette use is a New York State (NYS) public health priority. In May 2020, a state-wide restriction on flavoured e-cigarettes, except tobacco flavour, was passed. This study examines changes in nicotine product use behaviour among youth around the time of the state-wide vaping flavour restriction. METHODS: NYS data from the US International Tobacco Control Policy Evaluation Project Youth Tobacco and E-cigarette Tobacco and Vaping Survey were analysed cross-sectionally from February 2020 (n=955), August 2020 (n=946), February 2021 (n=1030) and August 2021 (n=753). Online surveys were conducted among youth 16-19 years. Weighted descriptive statistics and regression models were used to describe changes in nicotine product use behaviour. Models were adjusted for age, sex, race/ethnicity and perceived family socioeconomic status. RESULTS: Significant decreases in past 30-day e-cigarette use (20%-11%), cigarette (7%-4%), and dual use of e-cigarettes and cigarettes (5%-2%) were observed over the 2-year period in NYS. Over 95% of vapers still reported using a non-tobacco-flavoured e-cigarette following the restriction, with fruit-flavoured being the most popular at each time point. CONCLUSIONS: Nearly all NYS youth continued to vape flavours that were restricted in NYS. While youth past 30-day vaping prevalence decreased significantly from 2020 to 2021, increased flavour restriction compliance could result in an even greater decrease. Continuous monitoring is important to better understand perceptions, use patterns and access at the individual level, retail level and population level to inform future enforcement and restrictions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".