Effects of two different instructional formats on scores and reliability of a script concordance test
Bibliographic record
Abstract
The script concordance test (SCT) is designed to assess clinical reasoning by adapting the likelihood of a case diagnosis, based on provided new information. In the standard instructions students are asked to exclude alternative diagnoses they have in mind when answering the questions, but it might be more authentic to include these. Fifty-nine final-year medical students completed an SCT. Twenty-nine were asked to take their differential diagnosis into account (adapted instructions). Thirty students were asked not to consider other diagnoses (standard instructions). All participants were asked to indicate for each question whether they were confused answering it with the given instructions ('confusion indication'). Mean score of the test with the adapted instructions was 81.5 (SD 3.8) and of the test with the standard instructions 82.9 (SD 5.0) (p = 0.220). Cronbach's alpha was 0.39 for the adapted instructions and 0.66 for the standard instructions. The mean number of confusion indications was 4.2 (SD 4.4) per student for the adapted instructions and 16.7 (SD 28.5) for the standard instructions (p = 0.139). Our attempt to improve SCTs reliability by modifying the instructions did not lead to a higher alpha; therefore we do not recommend this change in the instructional format.
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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 | 0.078 | 0.454 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".