ArticleJournal of the American Medical Informatics Association : JAMIA
Estimating consumer familiarity with health terminology: a context-based approach.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Adverse Drug Reaction Related Post Detecting Using Sentiment Feature.Iranian journal of public health · 2018Article
- Overcoming consumer inertia to dietary guidance.Advances in nutrition (Bethesda, Md.) · 2015Article
- Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features.Journal of the American Medical Informatics Association : JAMIA · 2015Article
- Effects of individual health topic familiarity on activity patterns during health information searches.JMIR medical informatics · 2015Article
- Portable automatic text classification for adverse drug reaction detection via multi-corpus training.Journal of biomedical informatics · 2015Article
- Pharmacovigilance on twitter? Mining tweets for adverse drug reactions.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014Article
- User evaluation of the effects of a text simplification algorithm using term familiarity on perception, understanding, learning, and information retention.Journal of medical Internet research · 2013Article
- No change in physician dictation patterns when visit notes are made available online for patients.Mayo Clinic proceedings · 2011Article
- A semantic and syntactic text simplification tool for health content.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2010Article
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Authors and funding
5 authors.
Funding
Abstract
objectivesEffective health communication is often hindered by a "vocabulary gap" between language familiar to consumers and jargon used in medical practice and research. To present health information to consumers in a comprehensible fashion, we need to develop a mechanism to quantify health terms as being more likely or less likely to be understood by typical members of the lay public. Prior research has used approaches including syllable count, easy word list, and frequency count, all of which have significant limitations.
designIn this article, we present a new method that predicts consumer familiarity using contextual information. The method was applied to a large query log data set and validated using results from two previously conducted consumer surveys. MEASUREMENTS: We measured the correlation between the survey result and the context-based prediction, syllable count, frequency count, and log normalized frequency count.
resultsThe correlation coefficient between the context-based prediction and the survey result was 0.773 (p < 0.001), which was higher than the correlation coefficients between the survey result and the syllable count, frequency count, and log normalized frequency count (p < or = 0.012).
conclusionsThe context-based approach provides a good alternative to the existing term familiarity assessment methods.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.