Surgical Residents’ Perception of Feedback on Their Education: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Feedback is an essential tool for learning and improving performance in any sphere of education, including training of resident physicians. The learner's perception of the feedback they receive is extremely relevant to their learning progress, which must aim at providing qualified care for patients. Studies pertinent to the matter differ substantially with respect to methodology, population, context, and objective, which makes it even more difficult to achieve a clear understanding of the topic. A scoping review on this theme will unequivocally enhance and organize what is already known. OBJECTIVE: The aim of this study is to identify and map out data from studies that report surgical residents' perception of the feedback received during their education. METHODS: The review will consider studies on the feedback perception of resident physicians of any surgical specialty and age group, attending any year of residency, regardless of the type of feedback given and the way the perceptions were measured. Primary studies published in English, Spanish, and Portuguese since 2017 will be considered. The search will be carried out in 6 databases and reference lists will also be searched for additional studies. Duplicates will be removed, and 2 independent reviewers will screen the selected studies' titles, abstracts, and full texts. Data extraction will be performed through a tool developed by the researchers. Descriptive statistics and qualitative analysis (content analysis) will be used to analyze the data. A summary of the results will be presented in the form of diagrams, narratives, and tables. RESULTS: The findings of this scoping review were submitted to an indexed journal in July 2024, currently awaiting reviewer approval. The search was executed on March 15, 2024, and resulted in 588 articles. After the exclusion of the duplicate articles and those that did not meet the eligibility criteria as well as the inclusion of articles through a manual search, 13 articles were included in the review. CONCLUSIONS: Conducting a scoping review is the best way to map what is known about a subject. By focusing on the feedback perception more than the feedback itself, the results of this study will surely contribute to gaining a deeper understanding of how to proceed to enhance internal feedback and surgical residents' learning progress. TRIAL REGISTRATION: Open Science Framework yexb; https://osf.io/yexkb. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/56727.
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 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 | 0.116 | 0.099 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.013 | 0.013 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.095 | 0.018 |
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".