Reaching and treating Spanish-speaking smokers through the National Cancer Institute's cancer information service
Bibliographic record
Abstract
Although the prevalence of smoking is lower among Hispanics than among the general population, smoking still levies a heavy public health burden on this underserved group. The current study, Adiós al Fumar (Goodbye to Smoking), was designed to increase the reach of the Spanish-language smoking cessation counseling service provided by the National Cancer Institute's Cancer Information Service (CIS) and to evaluate the efficacy of a culturally sensitive, proactive, behavioral treatment program among Spanish-speaking smokers. Adiós was a 2-group randomized clinical trial evaluating a telephone-based smoking cessation intervention. Spanish-speaking smokers (N = 297) were randomized to receive either standard counseling or enhanced counseling (EC). Paid media was used to increase the reach of the Spanish-language smoking cessation services offered by the CIS. The Adiós sample was of very low socioeconomic status (SES), and more than 90% were immigrants. Calls to the CIS requesting smoking cessation help in Spanish increased from 0.39 calls to 17.8 calls per month. The unadjusted effect of EC only approached significance (OR = 2.4, P = .077), but became significant after controlling for demographic and tobacco-related variables (OR = 3.8, P = .048). Adiós al Fumar demonstrated that it is possible to reach, retain, and deliver an adequate dose of treatment to a very low SES population that has traditionally been viewed as difficult to reach and hard to follow. Moreover, the findings suggest that a proactive, telephone-counseling program, based on the Treating Tobacco Use and Dependence Clinical Practice Guideline and adapted to be culturally appropriate for Hispanics, is effective. Cancer 2007. (c) 2006 American Cancer Society.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".