Understanding Stigmatizing Language Lexicons: A Comparative Analysis in Clinical Contexts
This work addresses healthcare inequities by identifying inconsistencies in stigmatizing language definitions, but it is incremental as it analyzes existing lexicons without proposing a new method.
The study tackled the lack of a standardized lexicon for stigmatizing language in healthcare by systematically comparing four existing lexicons, finding moderate semantic similarity and that most terms are judgmental expressions by clinicians, with sentiment analysis showing predominantly negative classifications.
Stigmatizing language results in healthcare inequities, yet there is no universally accepted or standardized lexicon defining which words, terms, or phrases constitute stigmatizing language in healthcare. We conducted a systematic search of the literature to identify existing stigmatizing language lexicons and then analyzed them comparatively to examine: 1) similarities and discrepancies between these lexicons, and 2) the distribution of positive, negative, or neutral terms based on an established sentiment dataset. Our search identified four lexicons. The analysis results revealed moderate semantic similarity among them, and that most stigmatizing terms are related to judgmental expressions by clinicians to describe perceived negative behaviors. Sentiment analysis showed a predominant proportion of negatively classified terms, though variations exist across lexicons. Our findings underscore the need for a standardized lexicon and highlight challenges in defining stigmatizing language in clinical texts.