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An Informatics Framework to Assess Consumer Health Language Complexity Differences: Proof-of-Concept Study

BACKGROUND: The language gap between health consumers and health professionals has been long recognized as the main hindrance to effective health information comprehension. Although providing health information access in consumer health language (CHL) is widely accepted as the solution to the proble...

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Autores principales: Yu, Biyang, He, Zhe, Xing, Aiwen, Lustria, Mia Liza A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273233/
https://www.ncbi.nlm.nih.gov/pubmed/32436849
http://dx.doi.org/10.2196/16795
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author Yu, Biyang
He, Zhe
Xing, Aiwen
Lustria, Mia Liza A
author_facet Yu, Biyang
He, Zhe
Xing, Aiwen
Lustria, Mia Liza A
author_sort Yu, Biyang
collection PubMed
description BACKGROUND: The language gap between health consumers and health professionals has been long recognized as the main hindrance to effective health information comprehension. Although providing health information access in consumer health language (CHL) is widely accepted as the solution to the problem, health consumers are found to have varying health language preferences and proficiencies. To simplify health documents for heterogeneous consumer groups, it is important to quantify how CHLs are different in terms of complexity among various consumer groups. OBJECTIVE: This study aimed to propose an informatics framework (consumer health language complexity [CHELC]) to assess the complexity differences of CHL using syntax-level, text-level, term-level, and semantic-level complexity metrics. Specifically, we identified 8 language complexity metrics validated in previous literature and combined them into a 4-faceted framework. Through a rank-based algorithm, we developed unifying scores (CHELC scores [CHELCS]) to quantify syntax-level, text-level, term-level, semantic-level, and overall CHL complexity. We applied CHELCS to compare posts of each individual on online health forums designed for (1) the general public, (2) deaf and hearing-impaired people, and (3) people with autism spectrum disorder (ASD). METHODS: We examined posts with more than 4 sentences of each user from 3 health forums to understand CHL complexity differences among these groups: 12,560 posts from 3756 users in Yahoo! Answers, 25,545 posts from 1623 users in AllDeaf, and 26,484 posts from 2751 users in Wrong Planet. We calculated CHELCS for each user and compared the scores of 3 user groups (ie, deaf and hearing-impaired people, people with ASD, and the public) through 2-sample Kolmogorov-Smirnov tests and analysis of covariance tests. RESULTS: The results suggest that users in the public forum used more complex CHL, particularly more diverse semantics and more complex health terms compared with users in the ASD and deaf and hearing-impaired user forums. However, between the latter 2 groups, people with ASD used more complex words, and deaf and hearing-impaired users used more complex syntax. CONCLUSIONS: Our results show that the users in 3 online forums had significantly different CHL complexities in different facets. The proposed framework and detailed measurements help to quantify these CHL complexity differences comprehensively. The results emphasize the importance of tailoring health-related content for different consumer groups with varying CHL complexities.
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spelling pubmed-72732332020-06-05 An Informatics Framework to Assess Consumer Health Language Complexity Differences: Proof-of-Concept Study Yu, Biyang He, Zhe Xing, Aiwen Lustria, Mia Liza A J Med Internet Res Original Paper BACKGROUND: The language gap between health consumers and health professionals has been long recognized as the main hindrance to effective health information comprehension. Although providing health information access in consumer health language (CHL) is widely accepted as the solution to the problem, health consumers are found to have varying health language preferences and proficiencies. To simplify health documents for heterogeneous consumer groups, it is important to quantify how CHLs are different in terms of complexity among various consumer groups. OBJECTIVE: This study aimed to propose an informatics framework (consumer health language complexity [CHELC]) to assess the complexity differences of CHL using syntax-level, text-level, term-level, and semantic-level complexity metrics. Specifically, we identified 8 language complexity metrics validated in previous literature and combined them into a 4-faceted framework. Through a rank-based algorithm, we developed unifying scores (CHELC scores [CHELCS]) to quantify syntax-level, text-level, term-level, semantic-level, and overall CHL complexity. We applied CHELCS to compare posts of each individual on online health forums designed for (1) the general public, (2) deaf and hearing-impaired people, and (3) people with autism spectrum disorder (ASD). METHODS: We examined posts with more than 4 sentences of each user from 3 health forums to understand CHL complexity differences among these groups: 12,560 posts from 3756 users in Yahoo! Answers, 25,545 posts from 1623 users in AllDeaf, and 26,484 posts from 2751 users in Wrong Planet. We calculated CHELCS for each user and compared the scores of 3 user groups (ie, deaf and hearing-impaired people, people with ASD, and the public) through 2-sample Kolmogorov-Smirnov tests and analysis of covariance tests. RESULTS: The results suggest that users in the public forum used more complex CHL, particularly more diverse semantics and more complex health terms compared with users in the ASD and deaf and hearing-impaired user forums. However, between the latter 2 groups, people with ASD used more complex words, and deaf and hearing-impaired users used more complex syntax. CONCLUSIONS: Our results show that the users in 3 online forums had significantly different CHL complexities in different facets. The proposed framework and detailed measurements help to quantify these CHL complexity differences comprehensively. The results emphasize the importance of tailoring health-related content for different consumer groups with varying CHL complexities. JMIR Publications 2020-05-21 /pmc/articles/PMC7273233/ /pubmed/32436849 http://dx.doi.org/10.2196/16795 Text en ©Biyang Yu, Zhe He, Aiwen Xing, Mia Liza A Lustria. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 21.05.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Yu, Biyang
He, Zhe
Xing, Aiwen
Lustria, Mia Liza A
An Informatics Framework to Assess Consumer Health Language Complexity Differences: Proof-of-Concept Study
title An Informatics Framework to Assess Consumer Health Language Complexity Differences: Proof-of-Concept Study
title_full An Informatics Framework to Assess Consumer Health Language Complexity Differences: Proof-of-Concept Study
title_fullStr An Informatics Framework to Assess Consumer Health Language Complexity Differences: Proof-of-Concept Study
title_full_unstemmed An Informatics Framework to Assess Consumer Health Language Complexity Differences: Proof-of-Concept Study
title_short An Informatics Framework to Assess Consumer Health Language Complexity Differences: Proof-of-Concept Study
title_sort informatics framework to assess consumer health language complexity differences: proof-of-concept study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273233/
https://www.ncbi.nlm.nih.gov/pubmed/32436849
http://dx.doi.org/10.2196/16795
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