Dietary supplement recommendations by Saskatchewan chiropractors: results of an online survey
Bibliographic record
Abstract
BACKGROUND: Chiropractors receive training in nutrition during their education, previous surveys have found that chiropractors frequently provide recommendations to patients relating to nutrition and dietary supplement intake. However, it has not been ascertained which specific supplements chiropractors recommend or the types of health conditions for which supplement recommendations are made. OBJECTIVE: The purpose of this study was to determine which dietary supplements are most commonly recommended by chiropractors in the province of Saskatchewan,Canada and the health conditions for which supplement recommendations are made. DESIGN: An online survey of licensed chiropractors practicing in the province of Saskatchewan, Canada was distributed three times following online and in-person notifications of the survey. STATISTICAL ANALYSES PERFORMED: Descriptive statistics were reported, predominantly in the form of means and proportions. RESULTS: A response rate of 45% was obtained. All of the respondents (100%) indicated providing nutritional advice or counselling to patients, while nearly all (99%) indicated providing dietary supplement recommendations to patients. Respondents estimated that they provide nutritional advice or counselling to 31% of their patients on average, and recommend dietary supplements to an average of 25% of their patients. The most commonly recommended supplements were glucosamine sulfate, multivitamins, vitamin C, vitamin D, calcium, omega-3 fatty acids, and probiotics. The most common reasons to recommend dietary supplements were for "general health and wellness" (82% of respondents), "bone health" (74%), "rheumatologic, arthritic, degenerative, or inflammatory conditions' (72%), and "acute and/or chronic musculoskeletal conditions" (65%). CONCLUSION: The majority of respondents indicated providing nutritional counselling and recommendations for dietary supplements to their patients. Respondents generally recommend a small number of dietary supplements and provide these recommendations and counselling to fewer than half of their patients on average, while tending to focus on conditions most closely related to the scope of practice of chiropractors. The findings of this study may have been limited by selection bias owing to the low response rate and as those who respond to surveys are often more likely to respond positively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".