Moving Beyond Readability Metrics for Health-Related Text Simplification
AffiliationUniv Arizona, Eller Coll Management, Management Informat Syst
Keywordsconsumer health information
MetadataShow full item record
PublisherIEEE COMPUTER SOC
CitationKauchak, David, and Gondy Leroy. "Moving Beyond Readability Metrics for Health-Related Text Simplification." IT Professional 18, no. 3 (2016): 45-51.
Rights© 2016 IEEE
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractLimited health literacy is a barrier to understanding health information. Simplifying text can reduce this barrier and possibly other known disparities in health. Unfortunately, few tools exist to simplify text with demonstrated impact on comprehension. By leveraging modern data sources integrated with natural language processing algorithms, we are developing the first semi-automated text simplification tool. We present two main contributions. First, we introduce our evidence-based development strategy for designing effective text simplification software and summarize initial, promising results. Second, we present a new study examining existing readability formulas, which are the most commonly used tools for text simplification in healthcare. We compare syllable count, the proxy for word difficulty used by most readability formulas, with our new metric ‘term familiarity’ and find that syllable count measures how difficult words ‘appear’ to be, but not their actual difficulty. In contrast, term familiarity can be used to measure actual difficulty.
VersionFinal accepted manuscript
SponsorsResearch reported in this publication was supported by the National Library Of Medicine of the National Institutes of Health under Award Number R01LM011975.