Evaluation of Patient Education Materials From Large-Language Artificial Intelligence Models on Carpal Tunnel Release.

carpal tunnel syndrome diagnosis hand psychosocial research and health outcomes

Journal

Hand (New York, N.Y.)
ISSN: 1558-9455
Titre abrégé: Hand (N Y)
Pays: United States
ID NLM: 101264149

Informations de publication

Date de publication:
25 Apr 2024
Historique:
medline: 25 4 2024
pubmed: 25 4 2024
entrez: 25 4 2024
Statut: aheadofprint

Résumé

ChatGPT, an artificial intelligence technology, has the potential to be a useful patient aid, though the accuracy and appropriateness of its responses and recommendations on common hand surgical pathologies and procedures must be understood. Comparing the sources referenced and characteristics of responses from ChatGPT and an established search engine (Google) on carpal tunnel surgery will allow for an understanding of the utility of ChatGPT for patient education. A Google search of "carpal tunnel release surgery" was performed and "frequently asked questions (FAQs)" were recorded with their answer and source. ChatGPT was then asked to provide answers to the Google FAQs. The FAQs were compared, and answer content was compared using word count, readability analyses, and content source. There was 40% concordance among questions asked by the programs. Google answered each question with one source per answer, whereas ChatGPT's answers were created from two sources per answer. ChatGPT's answers were significantly longer than Google's and multiple readability analysis algorithms found ChatGPT responses to be statistically significantly more difficult to read and at a higher grade level than Google's. ChatGPT always recommended "contacting your surgeon." A comparison of ChatGPT's responses to Google's FAQ responses revealed that ChatGPT's answers were more in-depth, from multiple sources, and from a higher proportion of academic Web sites. However, ChatGPT answers were found to be more difficult to understand. Further study is needed to understand if the differences in the responses between programs correlate to a difference in patient comprehension.

Sections du résumé

BACKGROUND UNASSIGNED
ChatGPT, an artificial intelligence technology, has the potential to be a useful patient aid, though the accuracy and appropriateness of its responses and recommendations on common hand surgical pathologies and procedures must be understood. Comparing the sources referenced and characteristics of responses from ChatGPT and an established search engine (Google) on carpal tunnel surgery will allow for an understanding of the utility of ChatGPT for patient education.
METHODS UNASSIGNED
A Google search of "carpal tunnel release surgery" was performed and "frequently asked questions (FAQs)" were recorded with their answer and source. ChatGPT was then asked to provide answers to the Google FAQs. The FAQs were compared, and answer content was compared using word count, readability analyses, and content source.
RESULTS UNASSIGNED
There was 40% concordance among questions asked by the programs. Google answered each question with one source per answer, whereas ChatGPT's answers were created from two sources per answer. ChatGPT's answers were significantly longer than Google's and multiple readability analysis algorithms found ChatGPT responses to be statistically significantly more difficult to read and at a higher grade level than Google's. ChatGPT always recommended "contacting your surgeon."
CONCLUSION UNASSIGNED
A comparison of ChatGPT's responses to Google's FAQ responses revealed that ChatGPT's answers were more in-depth, from multiple sources, and from a higher proportion of academic Web sites. However, ChatGPT answers were found to be more difficult to understand. Further study is needed to understand if the differences in the responses between programs correlate to a difference in patient comprehension.

Identifiants

pubmed: 38660977
doi: 10.1177/15589447241247332
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

15589447241247332

Déclaration de conflit d'intérêts

Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Auteurs

Brett J Croen (BJ)

Department of Orthopaedic Surgery, Penn Medicine, Philadelphia, PA, USA.

Mohammed S Abdullah (MS)

Department of Orthopaedic Surgery, Penn Medicine, Philadelphia, PA, USA.

Ellis Berns (E)

Department of Orthopaedic Surgery, Penn Medicine, Philadelphia, PA, USA.

Sarah Rapaport (S)

Department of Orthopaedic Surgery, Penn Medicine, Philadelphia, PA, USA.

Alexander K Hahn (AK)

Department of Orthopaedic Surgery, University of Connecticut, Farmington, USA.

Caitlin C Barrett (CC)

Department of Orthopaedic Surgery, Penn Medicine, Philadelphia, PA, USA.

Andrew D Sobel (AD)

Department of Orthopaedic Surgery, Penn Medicine, Philadelphia, PA, USA.

Classifications MeSH