単語がどのように誹謗中傷するのか: 電子医療記録における汚名付け言語の分類
Amanda McArthur1, Alya Ahmad1, Anne R Links1
1The Johns Hopkins University School of Medicine, 733 N Broadway, Baltimore, MD 21205, USA.
Patient education and counseling
|February 14, 2026
まとめ
電子医療記録 (EHR) には,患者を傷つける不名誉な言葉が含まれています. この言語の分類を策定することは,患者中心のケアと害の軽減に不可欠です.
科学分野:
- 医療情報工学 医療情報工学
- 言語学 言語学とは
- 健康の社会学 健康の社会学
背景:
- 電子医療記録 (EHR) の言語は,汚名を永続化させることができます.
- この不名誉は,患者と臨床医の関係と将来のケアを損なう可能性があります.
- EHRにおける汚名付け言語の体系的な理解は欠けている.
研究 の 目的:
- EHRにおける汚名付け言語の分類を策定する.
- 患者の汚名付けのカテゴリーを特定する.
- スティグマを伝えるために使われる言語的メカニズムを理解する.
主な方法:
- 大規模な学術保健システムからのEHRノートの2段階の定性分析.
- 自然言語処理 (NLP) は,標識化キーワードを持つノートを識別するために使用されます.
- 296枚の紙幣をオープン・コーディングし,さらに400枚の紙幣を精製した.
主要な成果:
- 差別的な感情の6つのカテゴリが特定されました:社会的に望ましくない,やり取りが難しい,無能,操作的,不従順,信用できない.
- 患者の行動の否定的な記述 (例えば,要求する,欺く) を通して伝達された汚名.
- 言語的メカニズムには,患者の表現を形作るための強化器,懐疑的証拠,優美語が含まれていた.
結論:
- EHRにおける言語の侮辱は,キーワードだけでなく,言語的慣行に組み込まれています.
- この言語は,親権的な規範を強化し,患者のケアを損なう.
- これらのダイナミクスを理解することは,患者中心の文書化と害の軽減の鍵です.
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