Self‐reported use of natural health products among rheumatology patients: A cross‐sectional survey
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: To describe the self-reported use of natural health products (NHPs) and identify characteristics that predict selected NHP use in rheumatology patients. METHODS: We conducted a cross-sectional survey of consecutive rheumatology patients in two major clinics in Edmonton, Alberta. Survey items included demographic data, rheumatologic diagnoses, prescribed medications, NHPs, and information regarding patients' use of NHPs. Selected NHPs of interest - defined to include joint-specific products, oils with putative joint benefits, and other non-vitamin, non-mineral products - were classified by 2 reviewers. The characteristics of selected NHP users and non-users were compared using chi-squared and ANOVA tests, followed by multivariable-adjusted logistic regression. RESULTS: 1063 patients completed the survey (response rate = 36%, mean age 53 [sd 15], 70% female). 36% of respondents reported using one or more of a wide range of selected NHPs (mean 1.8, range 1-9). The most common source of NHP recommendations for selected NHP users were physicians (42%). Significant predictors of selected NHP use were: being female (aOR 1.41, 95%CI [1.05-1.90], p = 0.02), having a post-secondary degree (aOR 1.60 [1.15-2.22], p = 0.005), and the number of non-rheumatic medications (aOR 1.08 [ 1.00-1.15], p = 0.03) and NSAIDs (aOR 1.32 [1.06, 1.63], p = 0.01). Similar findings were observed among only inflammatory arthritis patients. CONCLUSIONS: Our study confirms the frequent use of selected NHPs, possibly to mitigate persistent symptoms of rheumatologic illness. Rheumatologists appear to be trusted sources of advice and recommendations on NHP use and should provide balanced counselling for their patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it