Healthcare Students’ Abilities To Translate Interprofessional Education To Collaborative Practice
Bibliographic record
Abstract
Interprofessional education is considered the first step to providing students with the knowledge and skill required to participate in interprofessional collaboration. The lingering question in research is if students can take these skills from the classroom to clinical practice. The answer to this question will help guide educators when developing effective IPE training. This quantitative, correlational study aimed to explore if healthcare students that participated in a two-part, case-based interprofessional educational session were able to transfer that skill to their clinical experience. Data was collected from healthcare students in the professions of physical therapy, occupational therapy, and nursing. The participants completed an electronic survey that consisted of the validated Interprofessional Collaborative Competency Attainment Survey (ICCAS) and basic demographic questions. The electronic survey assessed the participants’ behaviors associated with the six interprofessional collaboration core competencies developed by the Canadian Interprofessional Health Collaborative. Participants completed it after their clinical experience coursework. The data from this survey were compared to the results of data collected with the ICCAS during a previous research study the same cohort of students had participated in. The data were analyzed using the repeated measures ANOVA testing. There were statistical significances found between the ex post facto and pre-clinical experience as well as the pre-clinical and post-clinical experience. However, the mean scores were higher with the ex post facto data than the other two points in time. This outcome suggests the participants felt more confident with their interprofessional collaborative skills after their classroom training than they did prior to and after their clinical experience.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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".