Physical activity counselling and exercise prescription practices of chiropractors in Canada and internationally: an exploratory survey.
Bibliographic record
Abstract
Background: Physical activity and exercise (PAE) counselling and exercise prescriptions increase patient physical activity. However, the perceptions/practices of chiropractors are poorly understood. Methods: We surveyed the practices among chiropractors working in Canada (n=50) and Internationally (n=37). Chiropractors completed self-reflection questionnaires regarding their current practices and perceptions towards providing PAE counselling to patients. Chiropractor responses were obtained via Canadian provincial survey and educational workshops. Results: Chiropractor respondents included PAE content and exercise prescriptions in most patient appointments (67±27% and 59±35%, respectively), but the largest barriers (2.5/4.0) and least confidence were in their patients to follow through (52±21%). Canadian respondents reported higher knowledge (~0.4/4.0 higher), greater self-confidence (10-20% higher), and provided more PAE recommendations (8%) and prescriptions (16%) than International respondents. Chiropractor respondents were least comfortable advising patients with cancer. Conclusion: Chiropractor respondents may serve as health promotors to address patient inactivity, and the challenges identified should be addressed through educational training.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".