Does source matter? Nurses' and Physicians' perceptions of interprofessional feedback
Bibliographic record
Abstract
OBJECTIVE: Receptiveness to interprofessional feedback, which is important for optimal collaboration, may be influenced by 'in-group or out-group' categorisation, as suggested by social identity theory. We used an experimental design to explore how nurses and resident physicians perceive feedback from people within and outside their own professional group. METHODS: Paediatric residents and nurses participated in a simulation-based team exercise. Two nurses and two physicians wrote anonymous performance feedback for each participant. Participants each received a survey containing these feedback comments with prompts to rate (i) the usefulness (ii) the positivity and (iii) their agreement with each comment. Half of the participants received feedback labelled with the feedback provider's profession (two comments correctly labelled and two incorrectly labelled). Half received unlabelled feedback and were asked to guess the provider's profession. For each group, we performed separate three-way anovas on usefulness, positivity and agreement ratings to examine interactions between the recipient's profession, actual provider profession and perceived provider profession. RESULTS: Forty-five out of 50 participants completed the survey. There were no significant interactions between profession of the recipient and the actual profession of the feedback provider for any of the 3 variables. Among participants who guessed the source of the feedback, we found significant interactions between the profession of the feedback recipient and the guessed source of the feedback for both usefulness (F1,48 = 25.6; p < 0.001; η(2) = 0.35) and agreement ratings (F1,48 = 8.49; p < 0.01; η(2) = 0.15). Nurses' ratings of feedback they guessed to be from nurses were higher than ratings of feedback they guessed to be from physicians, and vice versa. Among participants who received labelled feedback, we noted a similar interaction between the profession of the feedback recipient and labelled source of feedback for usefulness ratings (F1,92 = 4.72; p < 0.05; η(2) = 0.05). CONCLUSION: Our data suggest that physicians and nurses are more likely to attribute favourably perceived feedback to the in-group than to the out-group. This finding has potential implications for interprofessional feedback practices.
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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 | 0.014 | 0.118 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".