Conhecimento e uso de cigarros eletrônicos e percepção de risco no Brasil: resultados de um país com requisitos regulatórios rígidos
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Given the uncertainties regarding electronic cigarettes' (e-cigs) impact on health, in 2009 Brazil prohibited sales, importation or advertisements of these products until manufacturers are able to show they are safe and/or effective in smoking cessation. This study sought to analyze: (1) awareness of electronic cigarettes, ever-use and recent use; (2) perception of harmfulness of electronic cigarettes when compared with conventional cigarettes; and (3) correlates of awareness and perception of harmfulness. This is a cross-sectional study among Brazilian smokers (≥ 18 years) using the Wave 2 replenishment sample of the Brazilian International Tobacco Control Policy Evaluation Survey. Participants were recruited in three cities through a random-digit dialing sampling frame between October 2012 and February 2012. Among the 721 respondents, 37.4% (n = 249) of current smokers were aware of e-cigs, 9.3% (n = 48) reported having ever tried or used e-cigs and 4.6% (n = 24) reported having used them in the previous six months. Among those who were aware of e-cigs, 44.4% (n = 103) believed they were less harmful than regular cigarettes (low perception of harmfulness). "Low perception of harmfulness" was associated with a higher educational level and with having recently tried/used e-cigs. Despite restrictions to e-cigs in Brazil, 4.6% of sample smokers reported having recently used them. Health surveillance programs in Brazil and other countries should include questions on use and perceptions of e-cigs considering their respective regulatory environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it