Patient Perspectives on Discussions of Electronic Cigarettes in Primary Care
Bibliographic record
Abstract
PURPOSE: Patient preferences regarding the role of the primary care provider (PCP) in discussing electronic cigarette (e-cigarette) use are unknown. METHODS: < .05 to assess associations between e-cigarette use and these measures. RESULTS: The prevalence of e-cigarette use was 10% for recent (≤30 days) use and 29% for nonrecent (>30 days) use. Prevalence was significantly higher among those who were younger, less educated, or smoked cigarettes, but did not vary by sex or self-reported health status. Roughly one quarter of participants believed they were knowledgeable about the health effects of e-cigarettes, secondhand smoke, and quitting cigarettes. Sources of e-cigarette information included television advertisements (56.6%), friends and family (49.9%), or e-cigarette shops (25.5%), but included physician offices much less frequently (6.0%). Although 30.2% disagreed that their PCP knew a lot about e-cigarettes, 62.0% were comfortable discussing e-cigarettes with their PCP. However, only 25% of all patients wanted their PCP to discuss e-cigarettes with them, but 62.0% of recent e-cigarette users wanted such a discussion. Most preferred a brief discussion or handout to a lengthy discussion. CONCLUSION: PCPs were infrequent sources of information for patients regarding e-cigarette use. PCPs need evidence-based strategies to help them address e-cigarettes in primary care.
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.
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 | 0.001 |
| 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".