10.51847/jclOlmW
Bibliographic record
Abstract
This study examined the validity and reliability of the student version of Jefferson Scale of Empathy-Health Profession (JSE-HPS) in a sample of pharmacy students and to subsequently use JSE-HPS to assess empathy levels in first to fourth (final) year pharmacy students in public and private universities in Malaysia. The JSE-HPS was administered to 719 first to fourth (final) year pharmacy students; 313 were enrolled at a public university and 406 at a private university in Malaysia. Both descriptive and inferential statistics were performed using SPSS® version 18. The JSE-HPS demonstrated good internal consistency (Cronbach’s ? = 0.70). A three-factor solution emerged and included ‘perspective taking’, ‘compassionate care’ and ‘standing in patient’s shoes’ factors, accounting for 16.4%, 16%, and 7.6% of the variance, respectively. The total mean empathy score was 83.02±8.23, the actual score ranged between 46.05 and 113.25. Overall, males and students of Malay origin were more empathic than females and students of other ethnic origins. Junior students (year one and two) were more empathic than senior students (year three and four), and public university students had significantly higher mean empathy score compared to those enrolled at a private university (83.89 versus 82.34, p=0.012). This study confirms the construct validity and internal consistency of the JSE-HPS for measuring empathy in pharmacy students. Empathy scores among students vary depending on type of university and year of study.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.908 | 0.903 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".