Perceptions of Peer-to-Peer Interprofessional Feedback Among Students in the Health Professions
Bibliographic record
Abstract
PURPOSE: Interprofessional teamwork should include interprofessional feedback to optimize performance and collaboration. Social identity theory predicts that hierarchy and stereotypes may limit receptiveness to interprofessional feedback, but literature on this is sparse. This study explores perceptions among health professions students regarding interprofessional peer feedback received after a team exercise. METHOD: In 2012-2013, students from seven health professions schools (medicine, pharmacy, nursing, dentistry, physical therapy, dietetics, and social work) participated in a team-based interprofessional exercise early in clinical training. Afterward, they wrote anonymous feedback comments for each other. Each student subsequently completed an online survey to rate the usefulness and positivity (on five-point scales) of feedback received and guessed each comment's source. Data analysis included analysis of variance to examine interactions (on usefulness and positivity ratings) between profession of feedback recipients and providers. RESULTS: Of 353 study participants, 242 (68.6%) accessed the feedback and 221 (62.6%) completed the survey. Overall, students perceived the feedback as useful (means across professions = 3.84-4.27) and positive (means = 4.17-4.86). There was no main effect of profession of the feedback provider, and no interactions between profession of recipient and profession of provider regardless of whether the actual or guessed provider profession was entered into the analysis. CONCLUSIONS: These findings suggest that students have positive perceptions of interprofessional feedback without systematic bias against any specific group. Whether students actually use interprofessional feedback for performance improvement and remain receptive toward such feedback as they progress in their professional education deserves further study.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".