The Pain Interprofessional Curriculum Design Model
Bibliographic record
Abstract
Objective: Although the University of Toronto Centre for the Study of Pain has successfully implemented an Interfaculty Pain Curriculum since 2002, we have never formalized the process in a design model. Therefore, our primary aim was to develop a model that provided an overview of dynamic, interrelated elements that have been important in our experience. A secondary purpose was to use the model to frame an interactive workshop for attendees interested in developing their own pain curricula. Methods: The faculties from Dentistry, Medicine, Nursing, Occupational Therapy, Pharmacy, and Physical Therapy met to develop the model components. Discussion focused on patient-centered pain assessment and management in an interprofessional context, with pain content being based on the International Association for the Study of Pain-Interprofessional Pain Curriculum domains and related core pain competencies. Profession-specific requirements were also considered, including regulatory/course requirements, level of students involved, type of course delivery, and pedagogic strategies. Results: The resulting Pain Interprofessional Curriculum Design Model includes components that are dynamic, competency-based, collaborative, and interrelated. Key questions important to developing curricular components guide the process. The Model framed two design workshops with very positive responses from international and national attendees. Conclusions: The Pain Interprofessional Curriculum Design Model is based on established pain curricula and related competencies that are relevant to all health science students at the prelicensure (entry-to-practice) level. The model has been developed from our experience, and the components resonated with workshop attendees from other regions. This Model provides a basis for future interventions in curriculum design and evaluation.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".