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A scoping review of empathy recognition in text using natural language processing
Vishal Anand Shetty1, Shauna Durbin2, Meghan S Weyrich3
1Department of Health Promotion and Policy, University of Massachusetts, Amherst, MA 01003, United States.
Journal of the American Medical Informatics Association : JAMIA
|December 13, 2023
Summary
This review explores natural language processing (NLP) for recognizing empathy in text. While NLP shows promise for physician-patient communication, defining and measuring empathy remains challenging.
Area of Science:
- Natural Language Processing (NLP)
- Computational Linguistics
- Health Informatics
Background:
- Empathic communication is crucial in healthcare.
- Patient portals are increasingly used for physician-patient interaction.
- Automated recognition of empathy in text is an emerging area.
Purpose of the Study:
- To conduct a scoping review of studies on empathy recognition in text using NLP.
- To inform approaches for identifying physician empathic communication in patient portal messages.
Main Methods:
- Systematic search of 6 databases for relevant studies up to May 1, 2023.
- Study selection via title screening, abstract review, and full-text review.
- Adherence to PRISMA-ScR guidelines for the review process.
Main Results:
- 39 studies were selected from 2446 publications.
- Summarized definitions of empathy, data sources, tested models, and model performance.
- Observed a shift towards transformer-based models in NLP for empathy tasks.
Conclusions:
- Current NLP methods show potential for empathy-related tasks.
- Challenges persist in defining and measuring empathy accurately in text.
- Further consideration of empathy conceptualization is needed for patient-physician communication studies.
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