Trends in Social Norms Toward Cigarette Smoking and E-cigarette Use Among U.S. Youth Between 2015 and 2021
Bibliographic record
Abstract
INTRODUCTION: This study examines trends in social norms toward cigarette smoking and e-cigarette use among US youth during 2015-2021, focusing on descriptive interpersonal norms (friends' behavior) and injunctive norms at interpersonal (perceived important others' negative view) and societal level (perceived public disapproval). METHODS: Respondents were youth aged 12 to 17 from the Population Assessment of Tobacco and Health Study of the United States, Wave 3 (2015-2016) to Wave 6 (2021). Logistic regression models that adjusted for demographics and participation effects assessed norm changes over time and their association with use status in Wave 6. RESULTS: Between 2015 and 2021, the probability of having friends who smoked cigarettes decreased (26.1% vs. 7.9%, adjusted odds ratio [aOR] = 0.81 [95% confidence interval = 0.72 to 0.91]), while having friends who use e-cigarettes generally decreased (31.6% vs. 22.3%, aOR = 0.46, [0.37-0.58]) despite an increase in 2018-2019. Perceived negative views from important others remained stable for both products during 2015-2019, peaked in 2020 (85.2% and 86.2%) before declining slightly in 2021. Perceived public disapproval increased to a peak in 2020 for both products (73.3% to 84.2% for cigarettes and 55.4% to 77.5% for e-cigarettes). In 2021, having friends who used e-cigarettes was associated with current e-cigarette use (relative risk ratio [RRR] = 15.07 [9.94-22.85]) and current dual use (RRR = 3.38 [1.41-8.13]), while important others' negative view toward e-cigarette use reduced the likelihood of current e-cigarette use (RRR = 0.3 [0.2-0.44]). CONCLUSIONS: Among US youth during 2015-2021, norms consistently indicated denormalization of cigarette smoking. e-cigarette norms showed greater variability, particularly during the coronavirus disease 2019 (COVID-19) pandemic.
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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 | 0.000 |
| 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) | 0.001 | 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".