A scoping review of feedback features during clinical education for anaesthesia trainees
Bibliographic record
Abstract
Our scoping review aimed to provide an overview of the evidence on feedback for clinical education in anaesthesia and to identify opportunities for systematic review. The authors searched PubMed, Scopus and Web of Science databases from 2014 to 2023. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews guideline, we independently screened titles, abstracts and full text for suitability based on predetermined inclusion and exclusion criteria. Our review encompassed all types of feedback studies specifically involving anaesthesia trainees. We collected data on various feedback contexts, such as task performance, processes, trainees’ self-assessment, trainee–faculty relationships and residency programme-related endpoints. The search strategy identified 14 articles from two countries: n = 12 from the USA and n = 2 from Canada. Few studies ( n = 4) reported different types of data provided automatically as feedback to the anaesthesia residents. We found that studies were conducted in different clinical contexts, including for residents’ clinical performance, documentation and quality metrics ( n = 4), feedback initiative ( n = 1), feedback model ( n = 1) and feedback agreement ( n = 1). No meta-analysis would be suitable because we did not observe a continuous dependent variable in at least five studies. Feedback parameters and perception are variable during clinical supervision and training of anaesthesia residents. We found that several techniques and technological instruments are applied to facilitate feedback conversations. This scoping review shows that a systematic review can be performed for one topic involving anaesthesia trainee feedback, that is, the categories of information provided automatically to residents. Further research is required to confirm the applicability of our findings, specifically in other countries outside the USA and Canada.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".