Use of Provider-Based Complementary and Alternative Medicine by Adult Smokers in the United States: Comparison from the 2002 and 2007 NHIS Survey
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
PURPOSE: To provide a snapshot of provider-based complementary and alternative medicine (pbCAM) use among adult smokers and assess the opportunity for these providers to deliver tobacco cessation interventions. DESIGN: Cross-sectional analysis of data from the 2002 and 2007 National Health Interview Surveys. SETTING: Nationally representative sample. SUBJECTS: A total of 54,437 (31,044 from 2002; 23,393 from 2007) adults 18 years and older. MEASURES: The analysis focuses on 10 types of pbCAM, including acupuncture, Ayurveda, biofeedback, chelation therapy, chiropractic care, energy therapy, folk medicine, hypnosis, massage, and naturopathy. ANALYSIS: The proportions of current smokers using any pbCAM as well as specific types of pbCAM in 2002 and 2007 are compared using SAS SURVEYLOGISTIC. RESULTS: Between 2002 and 2007, the percentage of recent users of any pbCAM therapy increased from 12.5% to 15.4% (p = .001). The largest increases occurred in massage, chiropractic, and acupuncture. Despite a decrease in the national average of current smokers (22.0% to 19.4%; p = .001), proportions of smokers within specific pbCAM disciplines remained consistent. CONCLUSION: Complementary and alternative medicine (CAM) practitioners, particularly those in chiropractic, acupuncture, and massage, represent new cohorts in the health care community to promote tobacco cessation. There is an opportunity to provide brief tobacco intervention training to CAM practitioners and engage them in public health efforts to reduce the burden of tobacco use in the United States.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it