Ten years of interfaculty pain curriculum at the University of Toronto: impact on student learning
Bibliographic record
Abstract
INTRODUCTION: Delivery of interprofessional pain education for prelicensure healthcare professionals is strongly recommended to advance a workforce ready for collaborative practice and to improve the quality and outcomes of pain care. OBJECTIVES: We report a 10-year (2009-2019) longitudinal evaluation of a 20-hour undergraduate Interfaculty Pain Curriculum (IPC) delivered to students in the Faculties of Dentistry, Nursing, Pharmacy, and Medicine (also including the Departments of Physical Therapy, Occupational Therapy and Physician Assistant) at the University of Toronto, Canada. The IPC follows a constructivist approach to facilitate interactive and multifaceted learning. METHODS: Evaluation methods based on the Kirkpatrick model were used to appraise changes in participating students' pain knowledge and beliefs and their ability to collaboratively develop an interprofessional pain management plan. RESULTS: A total of 10,693 students participated over the 10-year study period. The mean annual attendance was 972 students and participation to the program increased significantly over the years. Overall, the IPC was effective in improving students' mean pain knowledge and beliefs scores; however, the mean knowledge score gains were negatively correlated with time, likely related to increased uniprofessional pain education. Although an increasing trend in mean interprofessional pain management plan scores was observed, the scores were not significantly correlated with time. CONCLUSIONS: The interactive and multifaceted IPC is consistently effective in improving knowledge and beliefs and interprofessional pain management care plan development among participating student cohorts. Future inquiry is required to better understand the mechanisms behind student learning in interprofessional pain education to enhance pain curriculum development and delivery.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".