Bibliographic record
Abstract
Introduction: It has been shown that communication skills acquired during undergraduate medical education are of great importance. Hence, many countries require teaching communication as part of their medical curricula. To assess students’ learning progress, “Catering to the Patient”, as an aspect of showing empathy, should be evaluated. Since there was no description of a validated instrument fitting for this purpose, one had to be developed. To describe its process of development and its psychometric properties were the aims of this study. Methods: Based on the Calgary-Cambridge Observation Guide (CCOG), items describing catering to the patient were selected and modified. Cognitive pretest interviews were conducted to check understandability. Therefore, 7 raters assessed 1 video (R=7, V=1). In the following pilot study (R=3, V=10) first psychometric properties were evaluated and necessary corrections in the preliminary evaluation form were carried out before the final evaluation form was used to assess students’ ability to cater to the patient and psychometric properties were described in detail (R=2, V=35). Results: The final assessment instrument, “Catering to the Patient”, contains 11 checklist items and two global ratings (items 12 and 13). In the final evaluation, the inter-rater reliability (IRR) ranged from 0 to 0.562, the median was r=0.305. Concerning item 13 (a global rating), 88.6% of the videos were scored with the maximum difference of one point. The internal consistency was very high (Cronbach’s α: α=0.937 and α=0.962), and the correlation between the checklist items and the global rating was high (Pearson’s r: r=0.856 and r=0.898). Discussion: The assessment instrument “Catering to the Patient” is suitable for giving feedback and for using it in formative examinations. Its use for summative examinations can be considered. Further examinations should evaluate if a three-point Likert scale could reach higher values and if item 13 can be used as a stand-alone item.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".