Empathy and Burnout Among Naturopathic Medical Students

Principal Investigator: Melissa Gard, ND

Student Investigator: Matt Hicks

Abstract: In recent years the shift toward patient-centered care has lead investigators to measure empathy among physicians, residents, and medical students in order to better understand how it affects doctor-patient interactions, outcomes, and quality of life for physicians. Physicians and/or medical students with higher ratings of empathy have been correlated with: better clinical competency,1 higher likelihood to be identified for professionalism and leadership by peers,2 choosing people-oriented rather than technology driven specialties,3 higher ratings of communication by standardized patients in clinical exams,4 and overall patient satisfaction.5–7 It is an important interpersonal skill, especially among healthcare providers, yet the prevailing view is that empathy declines over the course of medical school and residency,8,9 Research has suggested that people who may otherwise be empathetic and compassionate tend to lack these traits when under stressful circumstances including professional burnout.10–13 When experienced by medical professionals burnout has been shown to decrease the quality of care patients receive.14 The primary aim of this study is to determine if burnout and a decline in empathy exists among Naturopathic medical students. No such studies have been done with this population. Results from this study will inform educators, administrators, and students about the characteristics of empathy among the Naturopathic student population in order to make informed decisions and comparisons.

Methods: An electronic questionnaire will be sent to Naturopathic students at the National College of Natural Medicine. The questionnaire will include basic demographic information, the Interpersonal Reactivity Index to measure empathy, and the Maslach Burnout Inventory. All data will be kept anonymous. In addition to a presentation of the descriptive statistics, a cross-sectional analysis will include various correlations, regressions, and potential adjustments for confounders.