Characteristics of Homeopathy Users among Internal Medicine Patients in Germany
Bibliographic record
Abstract
BACKGROUND: Homeopathy use continues to grow in many European countries, and some studies have examined the characteristics of patients using homeopathy within the general population. The aim of this study was to identify predictors for homeopathy use among internal medicine patients. PATIENTS AND METHODS: A cross-sectional analysis was conducted among all patients being referred to the Department of Internal and Integrative Medicine at Essen, Germany, over a 3-year period. The analysis examined whether patients had used homeopathy for their primary medical complaint before, the perceived benefit, and the perceived harm of homeopathy use. Odds ratios with 95% confidence intervals were calculated using multiple logistic regression analysis. RESULTS: Of 2,045 respondents, 715 (35.0%) reported having used homeopathy for their primary medical complaint (diagnosis according to the International Statistical Classification of Diseases and Related Health Problems), with 359 (50.2%) reporting perceived benefits and 15 (2.1%) reporting harm. Homeopathy use was positively associated with female gender, high school level education, suffering from fibromyalgia or subthreshold depression, and being fast food abstinent, while patients with osteoarthritis, spinal or other pain, smokers, and patients with a high external-social health locus of control were less likely to use homeopathy. CONCLUSION: Personal characteristics and health status may impact on the use and the perceived helpfulness of homeopathy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".