東華大學圖書館 |

Gender, Sex, and Sexual Orientation in Medicine: A Linguistic Analysis.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Gender, Sex, and Sexual Orientation in Medicine: A Linguistic Analysis./
作者:	Kronk, Clair Artemis.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:	121 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-04, Section: B.
Contained By:	Dissertations Abstracts International83-04B.
標題:	Bioinformatics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28765530
ISBN:	9798538148073

Gender, Sex, and Sexual Orientation in Medicine: A Linguistic Analysis.
Kronk, Clair Artemis.

Gender, Sex, and Sexual Orientation in Medicine: A Linguistic Analysis. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 121 p.

Source: Dissertations Abstracts International, Volume: 83-04, Section: B.

Thesis (Ph.D.)--University of Cincinnati, 2017.

This item must not be sold to any third party vendors.

Nine million Americans identify as LGBTQIA+ (lesbian, gay, bisexual, transgender, queer/questioning, intersex, agender/asexual, and other umbrella gender and sexual identity minorities), with an additional 187,000 expressing intersex anatomical variations. LGBTQIA+ populations experience disproportionate amounts of discrimination and stigmatization. A 2017 survey revealed that 51% of LGBTQIA+ people said that they or an LGBTQIA+ friend had experienced violence due to their identity. LGBTQIA+ discrimination is also prevalent in healthcare, 33% of transgender individuals disclosed negative experiences related to a health care provider and 23% described avoiding seeing a doctor when they needed due to fear of mistreatment.Such negative experiences are often connected to language use. Linguistic stigmatization has been tied to poor patient outcomes in healthcare settings. However, current provider education on LGBTQIA+ topics is lacking with a median of 5 hours dedicated to such subjects.A first step to addressing health disparities is to adequately model domain-specific linguistic knowledge. In medicine, language is modelled using controlled vocabularies or ontologies. Ontologies are common, shared networks which explain information in a domain. Such systems allow for greater reuse of domain-specific knowledge, and analysis of that knowledge. Although there are hundreds of biomedical ontologies, none cover LGBTQIA+ subject areas, or the areas of gender, sex, and sexual orientation.We created the Gender, Sex, and Sexual Orientation (GSSO) ontology and evaluated its usage in research, education, and clinical domains for accuracy, completeness, conciseness, adaptability, clarity, computational efficiency, and consistency. The GSSO includes over 10,000 entries, 14,000 mappings to other databases, more than 200 slang terms with definitions, 200 nonbinary and culturally-specific gender identities, and 190 pronouns with linked example usages. The GSSO is freely available via GitHub (https://github.com/Superraptor/GSSO) and its website (https://gsso.research.cchmc.org/) as well as via the NCBO BioPortal, EMBL-EBI OLS, and Ontobee (as part of the OBO Foundry ontologies).In research domains, the GSSO was able to perform on par with manually curated literature reviews and outperformed other ontologies in the space. In education, it was able to be easily understood by clinical and non-clinical subgroups. In clinical systems, it outperformed current identification methodologies. We also tested the systems efficacy in LGBTQIA+ language identification in free-text, including research-related abstracts and clinical notes in electronic health records (EHRs). In an LGBTQIA+-specific set of MEDLINE abstracts, the GSSO was able to tag 99.85% versus MeSH tagging 82.62%. In a manually curated transgender bibliography, MeSH would only return 86.9% of results versus the GSSO returning 97.7%. In the EHR, the GSSO outperformed ICD-based identification of transgender persons in both the MIMIC-III (100% versus 46%) and CCHMC (recall and precision of 0.74 and 0.79 versus 0.50 and 0.53) datasets.The GSSO is an effective ontological tool which can be applied across a wide variety of domains and questions.

ISBN: 9798538148073Subjects--Topical Terms:

553671
Bioinformatics.
Subjects--Index Terms:

Gender

Gender, Sex, and Sexual Orientation in Medicine: A Linguistic Analysis.
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520 $a Nine million Americans identify as LGBTQIA+ (lesbian, gay, bisexual, transgender, queer/questioning, intersex, agender/asexual, and other umbrella gender and sexual identity minorities), with an additional 187,000 expressing intersex anatomical variations. LGBTQIA+ populations experience disproportionate amounts of discrimination and stigmatization. A 2017 survey revealed that 51% of LGBTQIA+ people said that they or an LGBTQIA+ friend had experienced violence due to their identity. LGBTQIA+ discrimination is also prevalent in healthcare, 33% of transgender individuals disclosed negative experiences related to a health care provider and 23% described avoiding seeing a doctor when they needed due to fear of mistreatment.Such negative experiences are often connected to language use. Linguistic stigmatization has been tied to poor patient outcomes in healthcare settings. However, current provider education on LGBTQIA+ topics is lacking with a median of 5 hours dedicated to such subjects.A first step to addressing health disparities is to adequately model domain-specific linguistic knowledge. In medicine, language is modelled using controlled vocabularies or ontologies. Ontologies are common, shared networks which explain information in a domain. Such systems allow for greater reuse of domain-specific knowledge, and analysis of that knowledge. Although there are hundreds of biomedical ontologies, none cover LGBTQIA+ subject areas, or the areas of gender, sex, and sexual orientation.We created the Gender, Sex, and Sexual Orientation (GSSO) ontology and evaluated its usage in research, education, and clinical domains for accuracy, completeness, conciseness, adaptability, clarity, computational efficiency, and consistency. The GSSO includes over 10,000 entries, 14,000 mappings to other databases, more than 200 slang terms with definitions, 200 nonbinary and culturally-specific gender identities, and 190 pronouns with linked example usages. The GSSO is freely available via GitHub (https://github.com/Superraptor/GSSO) and its website (https://gsso.research.cchmc.org/) as well as via the NCBO BioPortal, EMBL-EBI OLS, and Ontobee (as part of the OBO Foundry ontologies).In research domains, the GSSO was able to perform on par with manually curated literature reviews and outperformed other ontologies in the space. In education, it was able to be easily understood by clinical and non-clinical subgroups. In clinical systems, it outperformed current identification methodologies. We also tested the systems efficacy in LGBTQIA+ language identification in free-text, including research-related abstracts and clinical notes in electronic health records (EHRs). In an LGBTQIA+-specific set of MEDLINE abstracts, the GSSO was able to tag 99.85% versus MeSH tagging 82.62%. In a manually curated transgender bibliography, MeSH would only return 86.9% of results versus the GSSO returning 97.7%. In the EHR, the GSSO outperformed ICD-based identification of transgender persons in both the MIMIC-III (100% versus 46%) and CCHMC (recall and precision of 0.74 and 0.79 versus 0.50 and 0.53) datasets.The GSSO is an effective ontological tool which can be applied across a wide variety of domains and questions.
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