Multisource feedback to assess pediatric practice: a systematic review
Bibliographic record
Abstract
INTRODUCTION: The assessment and maintenance of competence for pediatricians has recently received increased attention. The aim of the present study was to investigate further the use of multisource feedback for assessing pediatricians in practice. METHODS: A systematic literature review was conducted using the electronic databases EMBASE, PsycINFO, MEDLINE, PUBMED, and CINAHL for English-language articles. RESULTS: 762 articles were identified with the initial search and 756 articles were excluded for a total of six studies that met the inclusion criteria for this systematic review. Internal consistency reliability was reported in five studies with α ≥ 0.95 for both subscales and full scales. Generalizability was also reported in two studies with Ep (2) generally ≥ 0.78. These adequate Ep (2) coefficients were achieved with different numbers of raters. Evidence for content, criterion-related (e.g., Pearson's r) and construct validity (e.g., principal component factor analysis) was reported in all 6 studies. CONCLUSION: Multisource feedback is a feasible, reliable, and valid method to assess pediatricians in practice. The results indicate that multisource feedback system can be used to assess key competencies such as communication skills, interpersonal skills, collegiality, and medical expertise. Further implementation of multisource feedback is desirable.
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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 | 0.005 | 0.326 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 0.005 |
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; both teacher heads agree on what is shown here.
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".