Understanding how perceptions of tobacco constituents and the FDA relate to effective and credible tobacco risk messaging: A national phone survey of U.S. adults, 2014–2015
Bibliographic record
Abstract
Abstract Background The passage of the 2009 Family Smoking Prevention and Tobacco Control Act has necessitated the execution of timely, innovative, and policy-relevant tobacco control research to inform Food and Drug Administration (FDA) regulatory and messaging efforts. With recent dramatic changes to tobacco product availability and patterns of use, nationally representative data on tobacco-related perceptions and behaviors are vital, especially for vulnerable populations. Methods The UNC Center for Regulatory Research on Tobacco Communication conducted a telephone survey with a national sample of adults ages 18 and older living in the United States (U.S.). The survey assessed regulatory relevant factors such as tobacco product use, tobacco constituent perceptions, and tobacco regulatory agency credibility. The study oversampled high smoking/low income areas as well as cell phone numbers to ensure adequate representation among smokers and young adults, respectively. Coverage extended to approximately 98 % of U.S. households. Results The final dataset (N = 5,014) generated weighted estimates that were largely comparable to other national demographic and tobacco use estimates. Results revealed that over one quarter of U.S. adults, and over one third of smokers, reported having looked for information about tobacco constituents in cigarette smoke; however, the vast majority was unaware of what constituents might actually be present. Although only a minority of people reported trust in the federal government, two thirds felt that the FDA can effectively regulate tobacco products. Conclusions As the FDA continues their regulatory and messaging activities, they should expand both the breadth and availability of constituent-related information, targeting these efforts to reach all segments of the U.S. population, especially those disproportionately vulnerable to tobacco product use and its associated negative health outcomes.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".