Psychometric properties of the <scp>G</scp>reek version of the <scp>T</scp>oronto <scp>C</scp>omposite <scp>E</scp>mpathy <scp>S</scp>cale in <scp>G</scp>reek dental students
Bibliographic record
Abstract
INTRODUCTION: Empathy levels of health practitioners are related to patient satisfaction and treatment outcomes. The Toronto Composite Empathy Scale (TCES) was recently developed to assess cognitive and emotional empathy levels in both professional and personal spheres, and tested in an English-speaking sample of dental students. The aim of this study was to examine the psychometrics of the Greek version of the TCES. MATERIALS AND METHODS: The TCES was translated into Greek and administered to all of the dental students at Aristotle University of Thessaloniki. A random subset of students completed the questionnaire twice for test-retest analysis. RESULTS: Nearly all (96.5%) of the students completed the questionnaire. The internal consistencies of each of the four subscales were generally acceptable (Cronbach's alphas: 0.676-0.805), and the scale showed good discriminant and convergent validities (r's for discriminant validity: 0.217 and 0.103; r's for convergent validity: 0.595 and 0.700). Test-retest reliabilities ranged from 0.478 to 0.779. After eliminating items that fell on both cognitive and emotional factors, a rotated factor analysis indicated that the items loaded on two cognitive and three emotional factors. DISCUSSION: Our results indicate that the Greek version of the TCES has good psychometric properties. The factor analysis indicates that the emotional and cognitive aspects of empathy are distinct, supporting the need to address both aspects in studies of empathy. CONCLUSIONS: The Greek version of the TCES is a reliable and valid tool for the measurement of cognitive and emotional empathy, in both professional and personal life, in Greek dental students.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".