Validation of the National Aeronautics and Space Administration Task Load Index as a Tool to Evaluate-The Learning Curve for Endoscopy Training
Bibliographic record
Abstract
BACKGROUND: Although workplace workload assessments exist in different fields, an endoscopy-specific workload assessment tool is lacking. OBJECTIVE: To validate such a workload tool and use it to map the progression of novice trainees in gastroenterology in performing their first endoscopies. METHODS: The National Aeronautics and Space Administration Task Load Index (NASA-TLX) workload assessment tool was completed by eight novice trainees in gastroenterology and 10 practicing gastroenterologists⁄surgeons. An exploratory factor analysis was performed to construct a streamlined endoscopy-specific task load index, which was subsequently validated. The 'Endoscopy Task Load Index' was used to monitor progression of trainee exertion and self-assessed performance over their first 40 procedures. RESULTS: From the factor analysis of the NASA-TLX, two principal components emerged: a measure of exertion and a measure of self-efficacy. These items became the components of the newly validated Endoscopy Task Load Index. There was a steady decline in self-perceived exertion over the training period, which was more rapid for gastroscopy than colonoscopy. The self-efficacy scores for gastroscopy rapidly increased over the first few procedures, reaching a plateau after this period of time. For colonoscopy, there was a progressive increase in reported self-efficacy over the first three quartiles of procedures, followed by a drop in self-efficacy scores over the final quartile. DISCUSSION: The present study validated an Endoscopy Task Load Index that can be completed in <1 min. Practical implications of such a tool in endoscopy education include identifying periods of higher perceived exertion among novice endoscopists, facilitating appropriate levels of guidance from trainers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".