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1.
J Med Internet Res ; 20(8): e10779, 2018 08 02.
Artigo em Inglês | MEDLINE | ID: mdl-30072361

RESUMO

BACKGROUND: While health literacy is important for people to maintain good health and manage diseases, medical educational texts are often written beyond the reading level of the average individual. To mitigate this disconnect, text simplification research provides methods to increase readability and, therefore, comprehension. One method of text simplification is to isolate particularly difficult terms within a document and replace them with easier synonyms (lexical simplification) or an explanation in plain language (semantic simplification). Unfortunately, existing dictionaries are seldom complete, and consequently, resources for many difficult terms are unavailable. This is the case for English and Spanish resources. OBJECTIVE: Our objective was to automatically generate explanations for difficult terms in both English and Spanish when they are not covered by existing resources. The system we present combines existing resources for explanation generation using a novel algorithm (SubSimplify) to create additional explanations. METHODS: SubSimplify uses word-level parsing techniques and specialized medical affix dictionaries to identify the morphological units of a term and then source their definitions. While the underlying resources are different, SubSimplify applies the same principles in both languages. To evaluate our approach, we used term familiarity to identify difficult terms in English and Spanish and then generated explanations for them. For each language, we extracted 400 difficult terms from two different article types (General and Medical topics) balanced for frequency. For English terms, we compared SubSimplify's explanation with the explanations from the Consumer Health Vocabulary, WordNet Synonyms and Summaries, as well as Word Embedding Vector (WEV) synonyms. For Spanish terms, we compared the explanation to WordNet Summaries and WEV Embedding synonyms. We evaluated quality, coverage, and usefulness for the simplification provided for each term. Quality is the average score from two subject experts on a 1-4 Likert scale (two per language) for the synonyms or explanations provided by the source. Coverage is the number of terms for which a source could provide an explanation. Usefulness is the same expert score, however, with a 0 assigned when no explanations or synonyms were available for a term. RESULTS: SubSimplify resulted in quality scores of 1.64 for English (P<.001) and 1.49 for Spanish (P<.001), which were lower than those of existing resources (Consumer Health Vocabulary [CHV]=2.81). However, in coverage, SubSimplify outperforms all existing written resources, increasing the coverage from 53.0% to 80.5% in English and from 20.8% to 90.8% in Spanish (P<.001). This result means that the usefulness score of SubSimplify (1.32; P<.001) is greater than that of most existing resources (eg, CHV=0.169). CONCLUSIONS: Our approach is intended as an additional resource to existing, manually created resources. It greatly increases the number of difficult terms for which an easier alternative can be made available, resulting in greater actual usefulness.


Assuntos
Letramento em Saúde/métodos , Semântica , Algoritmos , Compreensão , Humanos , Idioma , Estudos de Validação como Assunto
2.
AMIA Annu Symp Proc ; 2021: 697-706, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-35309000

RESUMO

Audio is increasingly used to communicate health information. Initial evaluations have shown it to be an effective means with many features that can be optimized. This study focuses on missing functional elements: words that relate concepts in a sentence but are often excluded for brevity. They are not easily recognizable without linguistics expertise but can be detected algorithmically. Two studies showed that they are common and affect comprehension. A corpus statistics study with medical (Cochrane sentences, N=44,488) and general text (English and Simple English Wikipedia sentences, N=318,056 each) showed that functional elements were missing in 20-30% of sentences. A user study with Cochrane (N=50) and Wikipedia (N=50) paragraphs in text and audio format showed that more missing functional elements increased perceived difficulty of reading text, with the effect less pronounced with audio, and increased actual difficulty of both written and audio information with less information recalled with more missing elements.


Assuntos
Compreensão , Leitura , Humanos , Incidência , Idioma , Linguística
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