Examining the empathy levels of medical students using CHAID analysis

Empathy is a key factor in the medical field as it strengthens doctor-patient relationships, enhances communication, and leads to improved patient outcomes. This study aims to investigate the empathy levels of medical students, providing insights into the factors that influence these levels and using advanced analytical methods for accurate predictions.

The study was conducted with 322 medical students from a public university in Turkey. A relational screening model was applied, using a "Personal Information Form" and an "Empathy Scale" to gather data. CHAID analysis was employed to identify the key predictors influencing empathy levels, whereas machine learning algorithms were utilized to classify and predict individuals' empathy levels.

The analysis revealed that 41.3% of students displayed high empathy, 44.7% moderate empathy, and 14.0% low empathy. Factors such as parental education, maternal occupation, and gender were significant in determining empathy levels, with gender being the most influential. The machine learning models achieved an 80.1% accuracy in predicting empathy levels.

The findings indicate that targeted educational and social interventions, especially those addressing gender differences, could improve empathy in medical students, potentially leading to better patient care.

Not applicable, as this study does not report results from a health care intervention involving human participants.