An Interfaculty Pain Curriculum: Lessons learned from six years experience
Bibliographic record
Abstract
Minimal pain content has been documented in pre-licensure curricula and students lack important pain knowledge at graduation. To address this problem, we have implemented and evaluated a mandatory Interfaculty Pain Curriculum (IPC) yearly since 2002 for students (N=817 in 2007) from six Health Science Faculties/Departments. The 20-h pain curriculum continues to involve students from Dentistry, Medicine, Nursing, Pharmacy, Physical Therapy, and Occupational Therapy as part of their 2nd or 3rd year program. Evaluation methods based on Kirkpatrick's model now include evaluation of a Comprehensive Pain Management Plan along with the previously used Pain Knowledge and Beliefs Questionnaire (PKPQ) and Daily Content and Process Questionnaires (DCPQ). Important lessons have been learned and subsequent changes made in this iterative curriculum design based on extensive evaluation over the 6-year period. Modifications have included case development more relevant to the diverse student groups, learning contexts that are uni-, inter-, and multi-professional, and facilitator development in working with interprofessional student groups. PKBQ scores have improved in all years with a statistically significant average change on correct responses from 14% to 17%. The DCPQ responses have also indicated consistently that most students (85-95%) rated highly the patient panel, expert-lead clinically focused sessions, and small interprofessional groups. Relevancy and organization of the information presented have been generally rated highly from 80.3% to 91.2%. This curriculum continues to be a unique and valuable learning opportunity as we utilize lessons learned from extensive evaluation to move the pain agenda forward with pre-licensure health science students.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".