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Updated: Feb 24, 2026

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Understanding Stigmatizing Language Lexicons: A Comparative Analysis in Clinical Contexts.

Yiliang Zhou1, Di Hu1, Tianchu Lyu1

  • 1University of California, Irvine, Irvine, CA, United States.

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|February 23, 2026
PubMed
Summary
This summary is machine-generated.

Healthcare professionals need a standardized lexicon to avoid stigmatizing language, which contributes to inequities. Analysis of existing lexicons reveals most terms are judgmental and negatively classified, highlighting the need for clear definitions.

Keywords:
electronic health recordhealth equitynatural language processingstigmastigmatizing language

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Area of Science:

  • Medical Ethics
  • Health Communication
  • Linguistics in Healthcare

Background:

  • Stigmatizing language in healthcare contributes to significant inequities.
  • A universally accepted lexicon for identifying such language is currently lacking.
  • This absence hinders efforts to standardize communication and mitigate harm.

Purpose of the Study:

  • To systematically identify and comparatively analyze existing lexicons of stigmatizing language in healthcare.
  • To examine similarities, discrepancies, and term distribution (positive, negative, neutral) within these lexicons.
  • To underscore the need for a standardized lexicon and identify challenges in defining stigmatizing clinical language.

Main Methods:

  • Systematic literature search to identify relevant lexicons of stigmatizing language.
  • Comparative analysis of identified lexicons for semantic similarity and discrepancies.
  • Sentiment analysis of terms within lexicons using an established dataset to classify sentiment (positive, negative, neutral).

Main Results:

  • Four distinct lexicons of stigmatizing language were identified.
  • Moderate semantic similarity was found among the lexicons, with notable discrepancies.
  • The majority of identified stigmatizing terms were judgmental expressions used by clinicians for perceived negative behaviors.
  • Sentiment analysis revealed a predominant proportion of negatively classified terms, though variations existed across lexicons.

Conclusions:

  • Existing lexicons show moderate agreement but lack standardization, indicating a significant gap in healthcare communication.
  • The prevalence of negatively valenced and judgmental terms highlights the impact of clinician language on patient perception and care.
  • Developing a standardized lexicon is crucial for addressing healthcare inequities stemming from stigmatizing language.