Empathy amongst doctors: an observational study.
Bibliographic record
Abstract
INTRODUCTION: Empathy is the ability to put oneself in another's emotional space and experience what they feel. Either due to lack of experience or mundaness of practice, a state of empathy can become premised, and individuals become indifferent or detached. We aimed to explore the level of empathy among doctors at different levels of practice, age, gender, academics, non-academics and discipline. MATERIALS AND METHODS: This was a cross-sectional, observational study on empathy among doctors practicing in the private, public hospital sector and faculty at a medical university in Negeri Sembilan, Malaysia that utilised convenience sampling for data collection. The Toronto Empathy Questionnaire (TEQ) a validated tool was used to measure empathy. RESULTS: The questionnaire was completed by 127 doctors, 52% (n= 66) were males and 48% (n=61) females. There was no significant difference in empathy between male (M=46.44; SD=6.01) and female (M=45.05, SD=5.69) doctors; t (123) = 1.326, p=0.187. Pearson correlation coefficient was computed to assess the linear relationship between age and empathy and revealed no correlation between the two variables: r (125) =0.15, p=0.099. Medical-based doctors (M= 47.47, SD=5.98) demonstrated more empathy than surgicalbased (M=44.32, SD=5.41); t (123) =-3.09, p=0.002. Those already specialised in their fields (M=47.38, SD=4.57) had more empathy than those who had not (M= 44.36, SD=6.52); t (123) =-2.96, p = 0.004. Doctors in the university (M=47.97, SD=4.31) tended to have more empathy than those in the public hospitals (M= 44.63, SD=6.27); t (117) =-2.91, p=0.004. Academicians had more empathy than non-academicians but there was no difference between those who were in clinical practice and not. CONCLUSION: Our findings indicate that medical-based doctors demonstrate more empathy than surgical-based doctors, and there appeared to be no correlation between age and empathy. However, clinical experience and growth within the specialty seem to improve empathy. Doctors teaching in the university setting demonstrated more empathy than those practicing in the hospital setting. Inclusion of empathy-related sessions in the undergraduate and post-graduate curriculum could bridge the gap in empathy noted with age, discipline, and experience in practice. Further research on empathy among doctors using a wider population in Malaysia and a TEQ questionnaire validated to the Asian population would provide better insight regarding this area of medical practice. Future research on outcomes of inclusion of programmes targeted at improving empathy to create awareness during practice would support patient satisfaction and safety.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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".