Complementary Practitioners’ View of Treatment for Inflammatory Bowel Disease
Bibliographic record
Abstract
A substantial number of patients with inflammatory bowel disease use complementary therapies to manage their disease, including chiropractic and herbal therapies. The objective of this study was to explore whether providers of these therapies see patients with inflammatory bowel disease and recommend therapies, and to determine their opinions about the treatments that they recommend. The study sample comprised 66 chiropractors, 19 pharmacists, 16 herbalists and 15 health food store employees in Calgary, Alberta. A structured questionnaire containing two patient scenarios (a patient with active ulcerative colitis and a patient with inactive Crohn's disease) was completed either by an in-person interview or by a mailed questionnaire. Most respondents had seen patients with ulcerative colitis, and at least 80% of each group except pharmacists (only 10%) would treat these patients or recommend treatment. Almost all chiropractors used spinal manipulation, whereas herbalists and health food store employees suggested a wide range of different treatments. Chiropractors rated their treatment as moderately effective; herbalists and health food store employees viewed their recommendations as very effective. The results with respect to the second scenario were very similar. The wide range of treatment recommendations by practitioners, who differ greatly in terms of skills, knowledge and experience, has important implications for physician-patient communication, information provision and education regarding complementary and alternative therapies.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".