Abstract

Empathy is commonly defined as the capacity to stand in another's shoes and can be generally divided into two major components: affective and cognitive empathy. The role and importance of empathy in clinical practice have been widely discussed in the research community at large and there have been numerous initiatives to train physicians and nurses in empathic communication. Qualitative and quantitative investigations of clinical practice settings involving empathy have primarily focused on patient experience, yet little has been done on the quantitative analysis and modeling of clinical empathy themselves. In this paper, we address two important aspects of clinical empathy modeling: the design and implementation of a new annotation protocol, and an automatic classification system trained on a new corpus of narrative essays written by pre-med students. To develop the annotation protocol, we built MedicalCare, a corpus of essays simulating a doctor's delivery of bad news to a hypothetical patient. We compared our results with state-of-the-art research on empathy prediction using self-rated empathy scores. Our research suggests that the classification system we built is effective in modeling clinical empathy and that our annotation protocol is more reliable when compared with self-assessment approaches to empathy prediction.

Original languageEnglish (US)
Title of host publicationProceedings - 2021 IEEE 15th International Conference on Semantic Computing, ICSC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages215-220
Number of pages6
ISBN (Electronic)9781728188997
DOIs
StatePublished - Jan 2021
Event15th IEEE International Conference on Semantic Computing, ICSC 2021 - Virtual, Laguna Hills, United States
Duration: Jan 27 2021Jan 29 2021

Publication series

NameProceedings - 2021 IEEE 15th International Conference on Semantic Computing, ICSC 2021

Conference

Conference15th IEEE International Conference on Semantic Computing, ICSC 2021
CountryUnited States
CityVirtual, Laguna Hills
Period1/27/211/29/21

Keywords

  • clinical empathy
  • empathy
  • self rated empathy
  • third party rated empathy

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Decision Sciences (miscellaneous)

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