The Creation of an Objective Assessment Tool for Ultrasound-Guided Regional Anesthesia Using the Delphi Method
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The assessment of technical skills in ultrasound-guided regional anesthesia is currently subjective and relies largely on observations of the trainer. The objective of this study was to develop a checklist to assess training progress and to detect training gaps in ultrasound-guided regional anesthesia using the Delphi method. METHODS: A 30-item checklist was developed and then e-mailed to 18 reviewers for feedback. The checklist was modified on the basis of their feedback. This process of iteration was repeated until no further feedback was received, and a consensus was reached on the final composition of the checklist. A global rating scale (GRS) was introduced as a result of the feedback. RESULTS: Three rounds of feedback were required to reach consensus on the composition of the checklist and the GRS. The final checklist contains 22 items, and the GRS contains 9 categories. CONCLUSIONS: Using the Delphi method, a checklist and GRS were developed. These tools can serve as an objective means of assessing progress in ultrasound technical skills acquisition.
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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 | 0.167 | 0.200 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".