A Literature Review of Health Care Professional Attitudes Toward Complementary and Alternative Medicine
Bibliographic record
Abstract
Objective. To summarize health care professionals' attitudes toward complementary and alternative medicine (CAM). Methods. In October 2006, we searched Allied and Complementary Medicine Database (AMED; 1985—2006), Excerpta Medica Database (EMBASE; 1980—2006), and MED-LINE (1960—2006) for Canadian or US studies of health care professionals' attitudes toward CAM, published in English or French. Results. A total of 21 surveys of physicians, nurses, public health professionals, dietitians, social workers, medical/nursing school faculty, and pharmacists were included that focused on beliefs about CAM efficacy, personal use, clinical practice use and referrals, communication with patients about CAM, level of knowledge, and the need for information regarding various CAM therapies. Physicians were more negative compared to other health care professionals. Positive attitudes toward CAM did not correlate with CAM referral or prescription patterns. Health care professionals of all disciplines wanted more information about CAM. Conclusions. Heterogeneity in the CAM definition and questionnaire items precluded summarizing health care professionals' attitudes toward CAM. Providing CAM education to health care professionals may help to integrate CAM into mainstream medical care.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".