Comparison of verbal claims for natural health products made by health food stores staff versus pharmacists in Ontario, Canada.
Bibliographic record
Abstract
BACKGROUND: This study tested the hypothesis that while there are no written medical claims existing for many NHP, such claims are made verbally, giving a false impression that these are proven medical products. OBJECTIVE: To compare the number and type of verbal claims for NHP made by pharmacists to those made by health food stores personnel. METHODS: Randomly selected Canadian pharmacies selling NHP and health food stores were visited and the staff was asked to recommend natural health products for the treatment of hypertension. RESULTS: All health food stores (n=20) but only 4 out of 38 pharmacies (p< 0.001) recommended NHP for the treatment of hypertension. A majority of health food store staff (70%) stated that NHP are superior or equal to medicinal drugs in treating hypertension based on efficacy. CONCLUSION: Unlike pharmacy practice, verbal claims are common practice in health food stores, despite the lack of either written claims and/or proof of efficacy for most of them. These may be a very effective approach given that 30-40% of North American adults are functionally illiterate. These verbal claims are often inappropriate and not evidence-based.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".