Evaluation High-Quality of Information from ChatGPT (Artificial Intelligence-Large Language Model) Artificial Intelligence on Shoulder Stabilization Surgery.

dc.contributor.author

Hurley, Eoghan T

dc.contributor.author

Crook, Bryan S

dc.contributor.author

Lorentz, Samuel G

dc.contributor.author

Danilkowicz, Richard M

dc.contributor.author

Lau, Brian C

dc.contributor.author

Taylor, Dean C

dc.contributor.author

Dickens, Jonathan F

dc.contributor.author

Anakwenze, Oke

dc.contributor.author

Klifto, Christopher S

dc.date.accessioned

2024-03-19T16:34:30Z

dc.date.available

2024-03-19T16:34:30Z

dc.date.issued

2024-03

dc.description.abstract

Purpose

To analyze the quality and readability of information regarding shoulder stabilization surgery available using an online AI software (ChatGPT), using standardized scoring systems, as well as to report on the given answers by the AI.

Methods

An open AI model (ChatGPT) was used to answer 23 commonly asked questions from patients on shoulder stabilization surgery. These answers were evaluated for medical accuracy, quality, and readability using The JAMA Benchmark criteria, DISCERN score, Flesch-Kincaid Reading Ease Score (FRES) & Grade Level (FKGL).

Results

The JAMA Benchmark criteria score was 0, which is the lowest score, indicating no reliable resources cited. The DISCERN score was 60, which is considered a good score. The areas that open AI model did not achieve full marks were also related to the lack of available source material used to compile the answers, and finally some shortcomings with information not fully supported by the literature. The FRES was 26.2, and the FKGL was considered to be that of a college graduate.

Conclusions

There was generally high quality in the answers given on questions relating to shoulder stabilization surgery, but there was a high reading level required to comprehend the information presented. However, it is unclear where the answers came from with no source material cited. It is important to note that the ChatGPT software repeatedly references the need to discuss these questions with an orthopaedic surgeon and the importance of shared discussion making, as well as compliance with surgeon treatment recommendations.

Clinical relevance

As shoulder instability is an injury that predominantly affects younger individuals who may use the Internet for information, this study shows what information patients may be getting online.
dc.identifier

S0749-8063(23)00642-4

dc.identifier.issn

0749-8063

dc.identifier.issn

1526-3231

dc.identifier.uri

https://hdl.handle.net/10161/30373

dc.language

eng

dc.publisher

Elsevier BV

dc.relation.ispartof

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association

dc.relation.isversionof

10.1016/j.arthro.2023.07.048

dc.rights.uri

https://creativecommons.org/licenses/by-nc/4.0

dc.subject

Shoulder

dc.subject

Shoulder Joint

dc.subject

Humans

dc.subject

Joint Instability

dc.subject

Language

dc.subject

Comprehension

dc.subject

Artificial Intelligence

dc.title

Evaluation High-Quality of Information from ChatGPT (Artificial Intelligence-Large Language Model) Artificial Intelligence on Shoulder Stabilization Surgery.

dc.type

Journal article

duke.contributor.orcid

Taylor, Dean C|0000-0001-7748-0469

duke.contributor.orcid

Dickens, Jonathan F|0000-0002-3723-8296|0000-0002-4189-0287

pubs.begin-page

726

pubs.end-page

731.e6

pubs.issue

3

pubs.organisational-group

Duke

pubs.organisational-group

School of Medicine

pubs.organisational-group

Staff

pubs.organisational-group

Clinical Science Departments

pubs.organisational-group

Orthopaedic Surgery

pubs.organisational-group

University Initiatives & Academic Support Units

pubs.organisational-group

Initiatives

pubs.organisational-group

Duke Innovation & Entrepreneurship

pubs.publication-status

Published

pubs.volume

40

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