Using parent feedback: A qualitative study of residents’ and physician-educators’ perspectives
Bibliographic record
Abstract
INTRODUCTION: Patients and family members can contribute to resident assessment in competency-based medical education. However, few studies have examined the use of patient/family member feedback generated from questionnaire-based assessments. To implement appropriate assessment strategies and optimize feedback use, we need to understand how residents and physician-educators would use feedback from these stakeholders. This study aimed to understand how paediatric residents and physician-educators would use parent feedback generated from questionnaire-based assessments. METHODS: This study was conducted at a paediatric academic health science centre. We held dyadic interviews with six residents and six physician-educators. A three-step approach was used to analyze the data: data reduction, data display, and conclusions/verifications. We developed an initial coding scheme, conducted an in-depth review of the data and coded it, finalized our coding scheme, and identified categories. RESULTS: Participants described that they would use parent feedback to: (a) provide additional direct observations of residents' performances, (b) teach and coach residents, (c) assess residents' overall performance and progression, and (d) encourage resident self-assessment and behaviour change. DISCUSSION: Parents directly observe residents as they interact with them and their children and, therefore, can provide feedback on residents' performances. Residency programs should include parent feedback and promote and facilitate its use by residents and physician-educators. CONCLUSION: This study provides an initial understanding of how paediatric residents and physician-educators would use parent feedback if they were to receive it. This information, combined with future research, can inform the development and implementation of parent feedback strategies in competency-based medical education.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".