Assessing Interprofessional Learning during a Student Placement in an Interprofessional Rehabilitation University Clinic in Primary Healthcare in a Canadian Francophone Minority Context
Bibliographic record
Abstract
Background: Interprofessional collaboration is deemed the key to quality patient care and the future for healthcare delivery models. Such a complex competency needs to be learned; as such, interprofessional education should be a key component of health professional programs. An Interprofessional Rehabilitation University Clinic was created to promote interprofessional education at the pre-licensure level. However, few resources are currently available to assess interprofessional learning; no tool (English or French) that specifically assesses interprofessional learning could be identified.Methods and Findings: A self-administered questionnaire was developed to assess interprofessional learning during a clinical placement. Using a single-group posttest-only design, this descriptive pilot project reports the results obtained with this tool for the first 15 students on placement at the Clinic. Preliminary findings suggest this tool helped demonstrate that, during placements in an interprofessional clinic, students developed some understanding of their own profession as well as of other professions. Responses showed that participants believe that interprofessional interventions are more efficient, save time, and facilitate sharing of information leading to a better comprehension of the clients’ situations. The tool suggests that students feel that an interprofessional educational experience is beneficial for clients and for themselves.Conclusions: Assessing interprofessional learning is challenging. Although the tool developed during this project is most promising, further research is warranted to increase its usefulness in assessing interprofessional learning.
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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 | 0.016 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.010 |
| Insufficient payload (model declined to judge) | 0.001 | 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".