Bibliographic record
Abstract
BACKGROUND: Despite a lack of good scientific evidence for their benefit, Canadians take a lot of natural health products (NHPs). The objectives of this study were to determine patients' perception of the efficacy, safety and quality of NHPs and to characterize NHP use. METHODS: A standardized, 18-question survey was distributed to the general public through a variety of methods. RESULTS: A total of 326 individuals completed the survey. Eighty-five percent of respondents take 1 or more NHPs. Forty-seven percent agreed/strongly agreed that NHPs are safer than prescription medications and 24% disagreed/strongly disagreed that prescription medications are more effective than NHPs. Three-quarters of respondents agreed/strongly agreed that health care providers should recommend NHPs more often, as most stated they preferred to take an NHP for both a minor ailment (82%) and chronic medical condition (60%). Respondents used 124 different NHPs, most commonly vitamin D, vitamin B and magnesium. Respondents purchased NHPs primarily from health/vitamin stores (66%) and accessed the Internet for information about them (64%). Younger, female respondents were more likely to take NHPs. DISCUSSION: Patients appear to be comfortable foregoing education from health care professionals about the benefits and risks of NHPs. Patients' comfort with self-prescribing NHPs seems to stem from a perception of general efficacy and quality with little to no concern about harm and appears to be strongly influenced by lay sources of information. CONCLUSION: Most respondents take 1 or more NHPs, preferring to use NHPs over prescription medications for minor and chronic health concerns seemingly based on a perception of safety and quality.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".