Promotion of Testing for Celiac Disease and the Gluten-Free Diet Among Complementary and Alternative Medicine Practitioners
Bibliographic record
Abstract
INTRODUCTION: We identified the frequency and assessed the validity of marketing claims made by American chiropractors, naturopaths, homeopaths, acupuncturists, and integrative medicine practitioners relating to the diagnosis and treatment of celiac disease and nonceliac gluten sensitivity (NCGS), both of which have increased in prevalence in recent years. METHODS: We performed a cross-sectional study analyzing websites of practitioners from 10 cities in the United States and analyzed the websites for any mention of celiac or NCGS as well as specific claims of ability to diagnose, ability to treat, and treatment efficacy. We classified treatments promoted as true, false, or unproven, as assessed independently by 2 authors. RESULTS: Of 500 clinics identified, 178 (35.6%) made a claim regarding celiac disease, NCGS, or a gluten-free diet. Naturopath clinic websites have the highest rates of advertising at least one of diagnosis, treatment, or efficacy for celiac disease (40%), followed by integrative medicine clinics (36%), homeopaths (20%), acupuncturists (14%), and chiropractors (12%). Integrative medicine clinics have the highest rates of advertising at least one of diagnosis, treatment, or efficacy for NCGS (45%), followed by naturopaths (37%), homeopaths (14%), chiropractors (14%), and acupuncturists (10%). A geographic analysis yielded no significant variation in marketing rates among clinics from different cities. Of 232 marketing claims made by these complementary and alternative medicine (CAM) clinic websites, 138 (59.5%) were either false or unproven. DISCUSSION: A significant number of CAM clinics advertise diagnostic techniques or treatments for celiac disease or NCGS. Many claims are either false or unproven, thus warranting a need for increased regulation of CAM advertising to protect the public.
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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 | 0.003 | 0.015 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".