Construct validity of a Neck Palpation Simulator
Bibliographic record
Abstract
Objectives/Hypothesis: To assess the construct validity of a high-fidelity neck model with simulated lymph adenopathy. Study design: Prospective experimental validation study. Methods: Six first year medical students with prior training (novice learners) and six otolaryngology-head and neck surgery (OtoHNS) residents (experts) performed the head and neck lymph node examination on a novel tissue-mimicking construct model of the neck region. Two otolaryngologists, blinded to training type, evaluated the videotaped performances, using two assessment tools specifically designed for the head and neck lymph node examination: a global rating scale (GRS), and a task-based checklist (TBC). Results: The OtoHNS residents scored significantly higher than the medical student s on the GRS (p=0.008). There was also a trend towards better scores for the residents on the TBC (p=0.085). Conclusion: This is the first reported stud y of a high-fidelity lymphadenopathy model with task¬ specific assessment tools. The neck model demonstrated construct validity, by easily distinguishing between experts and novices on the basis of procedural competence. Using the global rating scale and task-based checklist, this model can be used to provide formative feedback, and to assess technical skill s acquisition in trainees.
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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 | 0.013 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".