Predictors of empathy in health science students

J Allied Health. 2011 Fall;40(3):143-9.

Abstract

The significance of both empathy and effective communication as key components in the provision of health care services is widely acknowledged. It is important, therefore, to promote those communication styles which facilitate an empathetic understanding among health science students.

Objective: To explores whether listening and communication styles are predictive of empathy among health science students.

Methods: A cross-sectional study of 860 undergraduate health science students (response rate, 59%) using paper-based versions of the Jefferson Scale of Physician Empathy-Health Professional Version, Listening Styles Profile, Communicator Styles Measure, and a brief demographic questionnaire. Two stepwise linear regression analyses were completed using the empathy construct as the dependent/criterion variable and listening and communication styles as the two sets of independent/predictor variables.

Results: As there was a statistically significant difference in empathy between males and females, gender was controlled for in both regression models. In first model, the People and Time listening styles were found to be predictive of empathy, accounting for 20.3% of the total variance. In the second model, both the Friendly and Relaxed communication styles were predictive of empathy, accounting for 9.7% of the total variance.

Conclusion: The findings indicate that People and Time listening styles and the Friendly and Relaxed communication styles were significant predictors of empathy in health science students. The findings suggest that promoting effective communication among health science students may improve their ability to empathize.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Allied Health Personnel / education*
  • Allied Health Personnel / psychology*
  • Analysis of Variance
  • Communication*
  • Cross-Sectional Studies
  • Empathy*
  • Female
  • Humans
  • Male
  • Predictive Value of Tests
  • Regression Analysis
  • Surveys and Questionnaires