A Nordic survey on artificial intelligence in the radiography profession - Is the profession ready for a culture change?

Artificial intelligence Motivation Profession Radiography Survey

Journal

Radiography (London, England : 1995)
ISSN: 1532-2831
Titre abrégé: Radiography (Lond)
Pays: Netherlands
ID NLM: 9604102

Informations de publication

Date de publication:
22 May 2024
Historique:
received: 18 01 2024
revised: 12 04 2024
accepted: 22 04 2024
medline: 24 5 2024
pubmed: 24 5 2024
entrez: 23 5 2024
Statut: aheadofprint

Résumé

The impact of artificial intelligence (AI) on the radiography profession remains uncertain. Although AI has been increasingly used in clinical radiography, the perspectives of the radiography professionals in Nordic countries have yet to be examined. The primary aim was to examine views of Nordic radiographers 'on AI, with focus on perspectives, engagement, and knowledge of AI. Radiographers from Denmark, Norway, Sweden, Iceland, Greenland, and the Faroe Island were invited through social media platforms to participate in an online survey from March to June 2023. The survey encompassed 29-items and included 4 sections a) demographics, b) barriers and enablers on AI, c) perspectives and experiences of AI and d) knowledge of AI in radiography. Edgars Schein's model of organizational culture was employed to analyse Nordic radiographers' perspectives on AI. Overall, a total of 421 respondents participated in the survey. A majority were positive/somewhat positive towards AI in radiography e.g., 77.9 % (n = 342) thought that AI would have a positive effect on the profession, and 26% thought that AI would reduce the administrative workload. Most radiographers agreed or strongly agreed that clinicians may have access to AI generated reports (76.8 %, n = 297). Nevertheless, a total of 86 (20.1%) agree or somewhat agreed that AI a potential risk for radiography. Nordic radiographers are generally positive towards AI, yet uncertainties regarding its implementation persist. The findings underscore the importance of understanding these challenges for the responsible integration of AI systems. Carefully weighing the expected influence of AI against key incentives will support a seamless integration of AI for the benefit not just of the patients, but also of the radiography profession. Understanding incentives factors and barriers can help address uncertainties during implementation of AI in clinical practice.

Identifiants

pubmed: 38781794
pii: S1078-8174(24)00097-X
doi: 10.1016/j.radi.2024.04.020
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1106-1115

Informations de copyright

Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Conflict of interest statement The authors have no conflict of interest to declare.

Auteurs

M R V Pedersen (MRV)

Department of Radiology, Vejle Hospital - Part of Lillebaelt Hospital, Vejle, Denmark; Department of Regional Health Research, University of Southern Denmark, Odense, Denmark; Discipline of Medical Imaging & Radiation Therapy, School of Medicine, University College Cork, Ireland. Electronic address: malene.roland.vils.pedersen@rsyd.dk.

M W Kusk (MW)

Department of Regional Health Research, University of Southern Denmark, Odense, Denmark; Department of Radiology and Nuclear Medicine, University Hospital of Southern Denmark, Esbjerg, Denmark; IRIS - Imaging Research Initiative Southwest, University Hospital of Southern Denmark, Esbjerg, Denmark; Radiography and Diagnostic Imaging, School of Medicine, University College Dublin, Dublin, Ireland.

S Lysdahlgaard (S)

Department of Regional Health Research, University of Southern Denmark, Odense, Denmark; Department of Radiology and Nuclear Medicine, University Hospital of Southern Denmark, Esbjerg, Denmark; IRIS - Imaging Research Initiative Southwest, University Hospital of Southern Denmark, Esbjerg, Denmark.

H Mork-Knudsen (H)

Department of Radiology, Haukeland University Hospital, Norway.

C Malamateniou (C)

Department of Radiography, Division of Midwifery and Radiography, School of Health and Psychological Sciences, University of London, UK; European Federation of Radiographer Societies, Churchilllaan 11, 3527 GV, Utrecht, the Netherlands.

J Jensen (J)

Research and Innovation Unit of Radiology, University Hospital of Southern Denmark, Odense Denmark; Department of Radiology, Odense University Hospital, Odense, Denmark.

Classifications MeSH