A physician-physiotherapist collaborative model in a family medicine teaching clinic
Bibliographic record
Abstract
Persons with musculoskeletal disorders frequently seek care in family medicine clinics. However, musculoskeletal education provided in medical schools is often considered insufficient. The implementation of a collaborative model that integrates physiotherapists into teaching clinics may benefit the musculoskeletal training of medical residents. This paper describes a model developed in a family medicine teaching clinic by examining the interprofessional educational and collaborative activities implemented in this model. The model allowed to provide physiotherapy services, involve the physiotherapist in the training of family medicine residents and enhance interprofessional collaboration, particularly for the management of persons with musculoskeletal disorders._____Les personnes ayant des troubles musculosquelettiques consultent fréquemment en cliniques de médecine de famille. Cependant, l’enseignement musculosquelettique dispensé dans les programmes de médecine est souvent considéré comme insuffisant. L’implantation d’un modèle de collaboration qui intègre les physiothérapeutes aux cliniques d’enseignement pourrait améliorer la formation des médecins résidents. Cet article décrit un modèle développé dans une clinique d’enseignement en médecine familiale en examinant les activités interprofessionnelles d’éducation et de collaboration implantées dans ce modèle. Le modèle a permis d’offrir des services de physiothérapie, d’impliquer le physiothérapeute dans la formation des médecins résidents et d’améliorer la collaboration interprofessionnelle, particulièrement pour la prise en charge des personnes ayant des troubles musculosquelettiques.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".