The Effectiveness of an Interprofessional Education Course in Teaching the Importance of Choosing Wisely and Resource Stewardship: A Pilot Study
Bibliographic record
Abstract
Objectives Rising health care costs and an increase in unnecessary testing have sparked interest in resource stewardship (RS) and subsequently the Choosing Wisely Canada (CWC) campaign. Currently, all Canadian medical schools have student representatives for CWC; however, the same is not true in other health professions. Interprofessional care learned through interprofessional education (IPE) can lead to better patient outcomes. This study assessed whether an IPE course for health profession students was effective in teaching undergraduate students both interprofessional competencies and CWC principles. Methods An approximately seven-hour-long, four-session course was administered to Dalhousie University health profession students (N= 30). A validated survey for IPE competencies and a general survey about CWC principles were administered to assess the course. Descriptive statistics were used to assess the general CWC views, and paired samples t-tests were employed to compare pre- and post-IPE competencies. Results The full survey was completed by 25 (83%) students. Of these, 52% were female, within five health disciplines, and 13 (52%) had heard of CWC prior. Overall, the students agreed that CWC was important and relevant to their profession. They also reported significant improvements in multiple IPE competencies, including communication, collaboration, roles and responsibilities, patient-/family-centered care, conflict management/resolution, and team function. Conclusion Participants in our pilot Choosing Wisely IPE course valued the importance of the CWC campaign and reported improvement in multiple IPE competencies. This adaptable, simple, and low-cost course may be an effective way to integrate RS teaching across multiple health professions.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".