Validation of the Toronto Empathy Questionnaire (TEQ) Among Medical Students in China: Analyses Using Three Psychometric Methods
Bibliographic record
Abstract
This study aimed to validate the simplified Chinese version of the Toronto Empathy Questionnaire (cTEQ) for use with the Chinese population. The original English version of the TEQ was translated into simplified Chinese based on international criteria. Psychometric analyses were performed based on three psychometric methods: classical test theory (CTT), item response theory (IRT), and Rasch model theory (RMT). Differential item functioning analysis was adopted to check possible item bias caused by responses from different subgroups based on sex and ethnicity. A total of 1296 medical students successfully completed the TEQ through an online survey; 75.2% of respondents were female and the average age was 19 years old. Forty students completed the questionnaire 2 weeks later to assess the test-retest reliability of the questionnaire. Confirmatory factor analysis supported a 3-factor structure of the cTEQ. The CTT analyses confirmed that the cTEQ has sound psychometric properties. However, IRT and RMT analyses suggested some items might need further modifications and revisions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".