Adult perceptions of the relative harm of tobacco products and subsequent T tobacco product use: Longitudinal findings from waves 1 and 2 of the population assessment of tobacco and health (PATH) study
Bibliographic record
Abstract
Objectives: To examine: (1) How perceptions of harm for seven non-cigarette tobacco products predict sub- sequent use; (2) How change in use is associated with changes in perceptions of product harm; (3) Whether sociodemographic variables moderate the association between perceptions and use. Methods: Data are from the adult sample (18+) of the Population Assessment of Tobacco and Health (PATH) Study, a nationally representative longitudinal cohort survey conducted September 2013-December 2014 (Wave 1 (W1) n = 32,320) and October 2014-October 2015 (Wave 2 (W2) n = 28,362). Results: Wave 1 users and non-users of e-cigarettes, filtered cigars, cigarillos, and pipes, who perceived these products as less harmful had greater odds of using the product at W2. For the other products, there was an interaction between W1 perceived harm and W1 use status in predicting W2 product use. At W2, a smaller percentage of U.S. adults rated e-cigarettes as less harmful than cigarettes compared to W1 (41.2% W1, 29.0% W2). Believing non-cigarette products to be less harmful than cigarettes was more strongly associated with subsequent product use in the oldest age group (55+ years) while weaker effects were observed in the youngest age group (18–24 years). This moderating effect of age was significant for e-cigarettes, hookah, traditional ci- gars, and cigarillos. Conclusions: Strategies to prevent initiation and promote cessation of these products may benefit from under- standing and addressing perceptions of these products.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".