Simulation-based training in flexible fibreoptic intubation
Bibliographic record
Abstract
BACKGROUND: Flexible fibreoptic intubation (FOI) is a key element in difficult airway management. Training of FOI skills is an important part of the anaesthesiology curriculum. Simulation-based training has been shown to be effective when learning FOI, but the optimal structure of the training is debated. The aspect of dividing the training into segments (part-task training) or assembling into one piece (whole-task training) has not been studied. OBJECTIVE: The aims of this study were to compare the effect of training the motor skills of FOI as part-task training or as whole-task training and to relate the performance levels achieved by the novices to the standard of performance of experienced FOI practitioners. DESIGN: A randomised controlled study. SETTING: Centre for Clinical Education, University of Copenhagen and the Capital Region of Denmark, between January and April 2013. PARTICIPANTS: Twenty-three anaesthesia residents in their first year of training in anaesthesiology with no experience in FOI, and 10 anaesthesia consultants experienced in FOI. INTERVENTIONS: The novices to FOI were allocated randomly to receive either part-task or whole-task training of FOI on virtual reality simulators. Procedures were subsequently trained on a manikin and assessed by an experienced anaesthesiologist. The experienced group was assessed in the same manner with no prior simulation-based training. MAIN OUTCOME MEASURES: The primary outcome measure was the score of performance on testing FOI skills on a manikin. RESULTS: A positive learning effect was observed in both the part-task training group and the whole-task training group. There was no statistically significant difference in final performance scores of the two novice groups (P = 0.61). Furthermore, both groups of novices were able to improve their skill level significantly by the end of manikin training to levels comparable to the experienced anaesthesiologists. CONCLUSION: Part-task training did not prove more effective than whole-task training when training novices in FOI skills. FOI is very suitable for simulation-based training and segmentation of the procedure during training is not necessary.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".