An exploratory survey about using ChatGPT in education, healthcare, and research.


Journal

medRxiv : the preprint server for health sciences
Titre abrégé: medRxiv
Pays: United States
ID NLM: 101767986

Informations de publication

Date de publication:
03 Apr 2023
Historique:
medline: 18 4 2023
entrez: 17 4 2023
pubmed: 18 4 2023
Statut: epublish

Résumé

Objective ChatGPT is the first large language model (LLM) to reach a large, mainstream audience. Its rapid adoption and exploration by the population at large has sparked a wide range of discussions regarding its acceptable and optimal integration in different areas. In a hybrid (virtual and in-person) panel discussion event, we examined various perspectives regarding the use of ChatGPT in education, research, and healthcare. Materials and Methods We surveyed in-person and online attendees using an audience interaction platform (Slido). We quantitatively analyzed received responses on questions about the use of ChatGPT in various contexts. We compared pairwise categorical groups with Fisher's Exact. Furthermore, we used qualitative methods to analyze and code discussions. Results We received 420 responses from an estimated 844 participants (response rate 49.7%). Only 40% of the audience had tried ChatGPT. More trainees had tried ChatGPT compared with faculty. Those who had used ChatGPT were more interested in using it in a wider range of contexts going forwards. Of the three discussed contexts, the greatest uncertainty was shown about using ChatGPT in education. Pros and cons were raised during discussion for the use of this technology in education, research, and healthcare. Discussion There was a range of perspectives around the uses of ChatGPT in education, research, and healthcare, with still much uncertainty around its acceptability and optimal uses. There were different perspectives from respondents of different roles (trainee vs faculty vs staff). More discussion is needed to explore perceptions around the use of LLMs such as ChatGPT in vital sectors such as education, healthcare and research. Given involved risks and unforeseen challenges, taking a thoughtful and measured approach in adoption would reduce the likelihood of harm.

Identifiants

pubmed: 37066228
doi: 10.1101/2023.03.31.23287979
pmc: PMC10104227
pii:
doi:

Types de publication

Preprint

Langues

eng

Subventions

Organisme : NHLBI NIH HHS
ID : F32 HL162377
Pays : United States
Organisme : NHLBI NIH HHS
ID : K23 HL155970
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001422
Pays : United States

Commentaires et corrections

Type : UpdateIn

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Auteurs

Mohammad Hosseini (M)

Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.

Catherine A Gao (CA)

Department of Medicine (Division of Pulmonary and Critical Care), Northwestern University Feinberg School of Medicine, Chicago, IL.

David Liebovitz (D)

Department of Medicine (Divisions of General Internal Medicine and Health and Biomedical Informatics), Northwestern University Feinberg School of Medicine, Chicago, IL.
Center for Medical Education in Digital Health and Data Science, Northwestern University Feinberg School of Medicine, Chicago, IL.

Alexandre Carvalho (A)

Department of Medicine (Division of Infectious Diseases), Northwestern University Feinberg School of Medicine, Chicago, IL.
Center for Pathogen Genomics & Microbial Evolution, Northwestern University Feinberg School of Medicine, Chicago, IL.

Faraz S Ahmad (FS)

Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.
Department of Medicine (Division of Cardiology), Northwestern University Feinberg School of Medicine, Chicago, IL.
Bluhm Cardiovascular Center for Artificial Intelligence, Northwestern Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.

Yuan Luo (Y)

Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.

Ngan MacDonald (N)

Institute for Augmented Intelligence in Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.

Kristi Holmes (K)

Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.
Galter Health Sciences Library and Learning Center, Northwestern University Feinberg School of Medicine, Chicago, IL.

Abel Kho (A)

Department of Medicine (Divisions of General Internal Medicine and Health and Biomedical Informatics), Northwestern University Feinberg School of Medicine, Chicago, IL.
Institute for Augmented Intelligence in Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.

Classifications MeSH