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Can Generative Artificial Intelligence Enhance Health Literacy About Lateral Epicondylitis?
Miskiewicz, Michael J; Leonardo, Christian; Capotosto, Salvatore; Ling, Kenny; Cohen, Dorian; Komatsu, David; Wang, Edward D.
Afiliação
  • Miskiewicz MJ; Department of Orthopaedic Surgery, Stony Brook University, Stony Brook, USA.
  • Leonardo C; Department of Orthopaedic Surgery, Stony Brook University, Stony Brook, USA.
  • Capotosto S; Department of Orthopaedic Surgery, Stony Brook University, Stony Brook, USA.
  • Ling K; Department of Orthopaedics, Stony Brook University Hospital, Stony Brook, USA.
  • Cohen D; Department of Orthopaedic Surgery, Stony Brook University, Stony Brook, USA.
  • Komatsu D; Department of Orthopaedic Surgery, Stony Brook University, Stony Brook, USA.
  • Wang ED; Department of Orthopaedic Surgery, Stony Brook University, Stony Brook, USA.
Cureus ; 16(5): e61384, 2024 May.
Article em En | MEDLINE | ID: mdl-38947706
ABSTRACT

INTRODUCTION:

Health literacy is a critical determinant of a patient's overall health status, and studies have demonstrated a consistent link between poor health literacy and negative health outcomes. The Centers for Disease Control and Prevention (CDC) and the National Institutes of Health (NIH) advise that patient educational materials (PEMs) should be written at an eighth-grade reading level or lower, matching the average reading level of adult Americans. The purpose of this study was to investigate the ability of generative artificial intelligence (AI) to edit PEMs from orthopaedic institutions to meet the CDC and NIH guidelines.

METHODS:

PEMs about lateral epicondylitis (LE) from the top 25 ranked orthopaedic institutions from the 2022 U.S. News & World Report Best Hospitals Specialty Ranking were gathered. ChatGPT Plus (version 4.0) was then instructed to rewrite PEMs on LE from these institutions to comply with CDC and NIH-recommended guidelines. Readability scores were calculated for the original and rewritten PEMs, and paired t-tests were used to determine statistical significance.

RESULTS:

Analysis of the original and edited PEMs about LE revealed significant reductions in reading grade level and word count of 3.70 ± 1.84 (p<0.001) and 346.72 ± 364.63 (p<0.001), respectively.

CONCLUSION:

Our study demonstrated generative AI's ability to rewrite PEM about LE at a reading comprehension level that conforms to the CDC and NIH guidelines. Hospital administrators and orthopaedic surgeons should consider the findings of this study and the potential utility of artificial intelligence when crafting PEMs of their own.
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Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Idioma: En Revista: Cureus Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Temas: Geral Base de dados: MEDLINE Idioma: En Revista: Cureus Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos