Measuring empathy of medical students studying different curricula; a causal comparative study.
Bibliographic record
Abstract
OBJECTIVE: To determine the difference in empathy level of undergraduate medical students studying two different curricula. METHODS: This cross-sectional study was conducted at Independent Medical College of Faisalabad and Islamic International Medical Collegeof Islamabad, both in Pakistan, from July to September 2016. The two medical colleges had two different types of curriculum systems; the integrated modular system and the discipline-based curriculum. The Toronto empathy questionnaire was used to calculate empathy scores. The responses were scored between 0 and 64 by taking sum of all the 16 questions. T-test was used to compare the mean scores and empathy levels between the two groups. SPSS 20 was used for data analysis. RESULTS: Of the 160 students, there were 80(50%) belonging to each institute. In the integrated modular system, 44(55%) students were females, whereas in the discipline-based system 45(56%) students were males. Students enrolled in the integrated modular system had a higher mean empathy score than students in the discipline-based system (44.2±6.59 versus 39.7±6.54, p<0.001). CONCLUSIONS: Interventions during the educational journey about empathy had positive influence on students' personalities and their future practices.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".