Alternative Medicine Use by Canadian Ambulatory Gastroenterology Patients: Secular Trend or Epidemic?
Bibliographic record
Abstract
OBJECTIVES: To assess the prevalence and determinants of alternative medicine (AM) use in gastroenterology outpatients and those with inflammatory bowel disease (IBD). METHODS: An 80-item questionnaire, addressing symptoms, general health, quality of life, and AM use, was administered and analyzed using logistic regression. RESULTS: 52.5% of 341 participants used AM in the previous year. Most commonly used were herbal medicine (45.2% of users; 95% CI 35.4-52.5%), chiropractor (40.7%; 95% Cl 31.4-48.0%), and massage therapy (22.9%; 95% CI 15.9-29.1%). Reasons prompting AM use were ineffective medical therapy (39.5%; 95% CI 30.4-46.8%), a greater sense of self-control (29.1%; 95% CI 21.2-35.7%), agreement with personal beliefs (19.5%; 95% CI 13.1-25.4%), and conventional drug adverse-effects (17.3%; 95% CI 11.2-22.9%). AM use was predicted as follows: (1) higher education (odds ratio (OR) 2.10; 95% CI 1.22-3.60), (2) comorbid medical conditions (OR 1.80; 95% CI 1.08-3.00), 3) poor mental component summary score of the SF-12 health survey (OR 1.04; 95% CI 1.01-1.07), and (4) higher annual income (OR 1.17; 95% CI 1.001-1.36), but was not related to response to conventional medical therapy. AM practitioners had instructed 8.6% to change prescription medications. AM usage for gastrointestinal disease was greater in patients with IBD (44.6% vs 10.0%; p < 0.05), who were more likely to cite adverse drug effects as a reason for AM use (28.9 vs 14.4%; p = 0.03). CONCLUSIONS: AM was used by 52.5% of gastroenterology outpatients and its use was greater in those with a higher level of education, comorbid conditions, poorer mental health-related quality of life, and higher income. Drug-related side effects also led to increased AM use.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".