Healthcare Professionals’ Insights on the Integration of Kinesiologists into Ontario’s Health System
Bibliographic record
Abstract
ABSTRACT Introduction/Purpose Kinesiologists are well suited to work collaboratively or independently within the health system to improve patient/client care and well-being. This cross-sectional survey explored perceptions of the integration of registered kinesiologists (RKins) into the health system in Ontario. Methods RKins ( n = 202) and other health professionals (OHP; n = 337), including physicians, physiotherapists, nurse practitioners, etc., participated in an online survey. Results RKins reported working in diverse practice environments, and more than half reported receiving patients/clients through referrals. Of the OHP, 37.7% had ongoing professional interactions with RKins and 86.7% reported high satisfaction with these interactions; 32.6% of OHP reported referring patients/clients to RKins, primarily for exercise prescription (86.0%), treatment of clinical conditions (48.8%), and patient education (46.5%). Perceived barriers to referral included lack of awareness of the RKins’ scope of practice (81.0%), inadequate funding for services (67.1%), and low confidence in the clinical competency of RKins (61.8%). Conclusions RKins are experts in exercise-based interventions to prevent, treat, and manage many chronic lifestyle-related diseases. Initiatives to increase awareness of the RKins’ scope of practice, clinical competency, and standards of practice and to increase funding for RKin services are important next steps.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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 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".