Using natural language processing to explore heterogeneity in moral terminology in palliative care consultations.

Journal: BMC palliative care
PMID: 33494745

Abstract

BACKGROUND: High quality serious illness communication requires good understanding of patients' values and beliefs for their treatment at end of life. Natural Language Processing (NLP) offers a reliable and scalable method for measuring and analyzing value- and belief-related features of conversations in the natural clinical setting. We use a validated NLP corpus and a series of statistical analyses to capture and explain conversation features that characterize the complex domain of moral values and beliefs. The objective of this study was to examine the frequency, distribution and clustering of morality lexicon expressed by patients during palliative care consultation using the Moral Foundations NLP Dictionary.

Authors

  • Eline van den Broek-Altenburg
    University of Vermont, Robert Larner, M.D. College of Medicine, 89 Beaumont Avenue, Burlington, VT, 05405, USA. eline.altenburg@med.uvm.edu.
  • Robert Gramling
    Department of Family Medicine, University of Vermont, Burlington, Vermont.
  • Kelly Gothard
    University of Vermont, Robert Larner, M.D. College of Medicine, 89 Beaumont Avenue, Burlington, VT, 05405, USA.
  • Maarten Kroesen
    Delft University of Technology, Stevinweg 1, Delft, CB, 2628, The Netherlands.
  • Caspar Chorus
    Delft University of Technology, Stevinweg 1, Delft, CB, 2628, The Netherlands.

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