Self-assessment and observer rating of empathetic communication in pharmacy students
Bibliographic record
Abstract
Methods First year pharmacy students enrolled in a communications course completed the empathic concern and perspective taking scales from the Interpersonal Reactivity Index (IRI) and participated in a video recorded patient interaction focusing on initial medication use. Students used the Empathic Communication Coding System (ECCS) to rate the first empathic opportunity in their video recording. Two researchers separately rated the video recordings using the ECCS for the empathic opportunity identified by the students and discrepancies were discussed until consensus was reached. Description statistics, correlations, and T-tests were used as appropriate to analyse the data. Results Analyses were performed on 63 students (class of 131) who consented and had complete data. Students rated themselves higher on the ECCS (3.6, SD=1.4) when compared with observers (2.6, SD=1.1) (T-test, p<0.05). There were no statistically significant correlations between the IRI self-report and either student or observer ECCS ratings. Male students rated themselves lower on the ECCS (3.2, SD=0.3) than females (3.8, SD=0.8) while there were no gender differences in observer ECCS scores (male: 2.7, SD=1.5; female: 2.6, SD=1.3). Discussion Pharmacy students were not able to accurately assess their own empathic communication. Our results indicate that students’ self-report empathy was not correlated with behaviour. Observers found no difference between male and female empathetic communication; although males has lower self-assessment than their female colleagues. Further work is required to find appropriate methods for evaluating student empathy and developing accurate self-assessment of empathic communication.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".