Physical Activity Counselling and Exercise Prescription Practices among Dietitians Across Nova Scotia
Bibliographic record
Abstract
The purpose of this study was to assess the perceptions and practices around physical activity counselling and exercise prescription of dietitians in Nova Scotia. Dietitians (n = 95) across Nova Scotia completed an online self-reflection survey regarding their current physical activity and exercise (PAE) practices. Most (51%; n = 48) reported no previous PAE educational training. Dietitians infrequently prescribed exercise to their patients (16% ± 26% of appointments) or provided PAE referrals (17% ± 24%). Dietitians reported moderate confidence (57% ± 21%) performing PAE counselling and included PAE-related content in half of patient appointments (52% ± 31%). Almost all respondents (95%) identified interest in further PAE education or training. Open-ended responses also demonstrated the need for community-based exercise programs (28% of providers) and qualified exercise professionals to refer to (25%). Overall, dietitians report rarely providing patients with written exercise prescriptions or referrals to other professionals for PAE content but do frequently include PAE in patient appointments. Dietitians in Nova Scotia are well positioned to promote PAE, but more educational training and improved referral systems to qualified exercise professionals or community exercise programs is strongly desired. Exercise professionals and dietitians should concurrently advocate for these changes and collaborate to help more patients lead physically active lifestyles.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".