Arthritis care & research · 2016
Computational Lexical Analysis of the Language Commonly Used to Describe Gout.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Lawrence Edwards N, Malouf Robert, Perez-Ruiz Fernando, Richette Pascal, Southam Siobhan, DiChiara Matthew
Аннотация
OBJECTIVE: To characterize the current language that is used in describing and defining gout, its symptoms, and its treatment by reviewing recent publications in rheumatology and determining how word choice may, or may not, be reflective of recent scientific developments in gout specifically.
METHODS: This was a computational linguistics study, using collocations analyses and concordance analyses on a database of scientific literature related to gout. The final data set for analysis included 2,590 articles, all relating to gout and published between May 2003 and May 2013 and amounting to 12,101,036 tokens (sentence segments). Analysis was conducted by a team of linguists and social scientists.
RESULTS: Our primary finding is that current disease language in gout is marked by ambiguity and imprecision, as evidenced by numerous terms that have similar but distinct meanings, but are nevertheless used interchangeably, therefore blending the slight but significant distinctions between these words. Whereas treatment language is characterized by a multitude of terms to describe a therapeutic mechanism of action, there is a relative void of terms and phrases used to describe success (treating to target) in gout.
CONCLUSION: The data suggest that the language used to describe gout could be improved and updated. A transformation from an antiquated and insufficiently descript terminological set to one that reflects the recent scientific and clinical advancements made in the category would maximize opportunities for patient and physician understanding.
METHODS: This was a computational linguistics study, using collocations analyses and concordance analyses on a database of scientific literature related to gout. The final data set for analysis included 2,590 articles, all relating to gout and published between May 2003 and May 2013 and amounting to 12,101,036 tokens (sentence segments). Analysis was conducted by a team of linguists and social scientists.
RESULTS: Our primary finding is that current disease language in gout is marked by ambiguity and imprecision, as evidenced by numerous terms that have similar but distinct meanings, but are nevertheless used interchangeably, therefore blending the slight but significant distinctions between these words. Whereas treatment language is characterized by a multitude of terms to describe a therapeutic mechanism of action, there is a relative void of terms and phrases used to describe success (treating to target) in gout.
CONCLUSION: The data suggest that the language used to describe gout could be improved and updated. A transformation from an antiquated and insufficiently descript terminological set to one that reflects the recent scientific and clinical advancements made in the category would maximize opportunities for patient and physician understanding.