Attitudes towards complementary and alternative medicine among medical and psychology students
Bibliographic record
Abstract
The use of complementary and alternative medicine (CAM) is increasing in Europe as well as in the USA, but CAM courses are infrequently integrated into medical curricula. In Europe, but also especially in the USA and in Canada, the attitudes of medical students and health science professionals in various disciplines towards CAM have been the subject of investigation. Most studies report positive attitudes. The main aim of this study was to compare the attitudes towards CAM of medical and psychology students in Germany. An additional set of questions concerned how CAM utilisation and emotional and physical condition affect CAM-related attitudes. Two hundred thirty-three medical students and 55 psychology students were questioned concerning their attitudes towards CAM using the Questionnaire on Attitudes Towards Complementary Medical Treatment (QACAM). Both medical students and psychology students were sceptical about the diagnostic and the therapeutic proficiency of doctors and practitioners of CAM. Students' attitudes towards CAM correlated neither with their experiences as CAM patients nor with their emotional and physical condition. It can be assumed that German medical and psychology students will be reluctant to use or recommend CAM in their professional careers. Further studies should examine more closely the correlation between attitudes towards CAM and the students' worldview as well as their existing knowledge of the effectiveness of CAM.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".