The quality of information available about Ephedra sinica on online vendor websites: The Canadian consumer experience
Bibliographic record
Abstract
BACKGROUND: Ephedra sinica (ES) is a natural health product used to promote weight loss, enhance athletic performance, and treat common ailments such as the common cold or flu. Due to restrictions within Canada, Canadians interested in purchasing this product turn to online vendors for the ease and discrete nature of online transactions. However, the information available on these websites for consumers looking to purchase the substance is variable. This study investigated the quality of information about ES available to Canadian consumers on the websites of these online vendors. METHODS: Following searches on Google.ca, eligible websites were assessed using the DISCERN instrument, a tool consisting of 16 questions, each rated on a five-point Likert scale, to assess the quality of health information about a treatment choice. The data was used to determine the overall quality of information about ES available to consumers on these websites. RESULTS: A total of 660 webpages were identified, of which 28 websites were found to be eligible. It was determined that the overall quality of information of websites selling ES products online was poor, as 79 % of online vendors received an average score of 2 or below. CONCLUSION: Consumers looking to purchase ES online are lacking critical information about this herbal product that is necessary to make an informed decision about its use. This study's findings can be used by clinicians and researchers to inform patients about the poor quality of information about ES on these websites and help them identify quality sources of information.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".