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Cited by 107Artificial Intelligence in Healthcare and EducationInnovations in Medical EducationArtificial Intelligence in Education

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Western Australian medical students’ attitudes towards artificial intelligence in healthcare

Open access
Stewart, Jonathon, Lu, Juan, Gahungu, Nestor, Goudie, Adrian, Fegan, P. Gerry, Bennamoun, Mohammed, Sprivulis, Peter, Dwivedi, Girish·2023·PLOS ONE
DOI 10.1371/journal.pone.0290642PMC PMC10470885
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Abstract

INTRODUCTION: Surveys conducted internationally have found widespread interest in artificial intelligence (AI) amongst medical students. No similar surveys have been conducted in Western Australia (WA) and it is not known how medical students in WA feel about the use of AI in healthcare or their understanding of AI. We aim to assess WA medical students' attitudes towards AI in general, AI in healthcare, and the inclusion of AI education in the medical curriculum. METHODS: A digital survey instrument was developed based on a review of available literature and consultation with subject matter experts. The survey was piloted with a group of medical students and refined based on their feedback. We then sent this anonymous digital survey to all medical students in WA (approximately 1539 students). Responses were open from the 7th of September 2021 to the 7th of November 2021. Students' categorical responses were qualitatively analysed, and free text comments from the survey were qualitatively analysed using open coding techniques. RESULTS: Overall, 134 students answered one or more questions (8.9% response rate). The majority of students (82.0%) were 20-29 years old, studying medicine as a postgraduate degree (77.6%), and had started clinical rotations (62.7%). Students were interested in AI (82.6%), self-reported having a basic understanding of AI (84.8%), but few agreed that they had an understanding of the basic computational principles of AI (33.3%) or the limitations of AI (46.2%). Most students (87.5%) had not received teaching in AI. The majority of students (58.6%) agreed that AI should be part of medical training and most (72.7%) wanted more teaching focusing on AI in medicine. Medical students appeared optimistic regarding the role of AI in medicine, with most (74.4%) agreeing with the statement that AI will improve medicine in general. The majority (56.6%) of medical students were not concerned about the impact of AI on their job security as a doctor. Students selected radiology (72.6%), pathology (58.2%), and medical administration (44.8%) as the specialties most likely to be impacted by AI, and psychiatry (61.2%), palliative care (48.5%), and obstetrics and gynaecology (41.0%) as the specialties least likely to be impacted by AI. Qualitative analysis of free text comments identified the use of AI as a tool, and that doctors will not be replaced as common themes. CONCLUSION: Medical students in WA appear to be interested in AI. However, they have not received education about AI and do not feel they understand its basic computational principles or limitations. AI appears to be a current deficit in the medical curriculum in WA, and most students surveyed were supportive of its introduction. These results are consistent with previous surveys conducted internationally.

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Fig 1 Medical students’ self-reported knowledge of artificial intelligence and interest in artificial intelligence. Percentages of students who strongly disagreed, somewhat disagreed, neither agreed nor disagreed, somewhat agreed, or strongly agreed with corresponding statements. Percentage ≤ 2 are not labelled in the figure to improve readability.
Fig 1 Medical students’ self-reported knowledge of artificial intelligence and interest in artificial intelligence. Percentages of students who strongly disagreed, somewhat disagreed, neither agreed nor disagreed, somewhat agreed, or strongly agreed with corresponding statements. Percentage ≤ 2 are not labelled in the figure to improve readability.CC BY · PubMed Central
Fig 2 Medical students’ education in artificial intelligence and attitudes towards incorporation of artificial intelligence into the medical curriculum. Percentages of students who strongly disagreed, somewhat disagreed, neither agreed nor disagreed, somewhat agreed, or strongly agreed with corresponding statements. Percentage ≤ 2 are not labelled in the figure to improve readability.
Fig 2 Medical students’ education in artificial intelligence and attitudes towards incorporation of artificial intelligence into the medical curriculum. Percentages of students who strongly disagreed, somewhat disagreed, neither agreed nor disagreed, somewhat agreed, or strongly agreed with corresponding statements. Percentage ≤ 2 are not labelled in the figure to improve readability.CC BY · PubMed Central
Fig 3 Medical students’ attitudes towards AI in medicine. Percentages of students who strongly disagreed, somewhat disagreed, neither agreed nor disagreed, somewhat agreed, or strongly agreed with corresponding statements. Percentage ≤ 2 are not labelled in the figure to improve readability.
Fig 3 Medical students’ attitudes towards AI in medicine. Percentages of students who strongly disagreed, somewhat disagreed, neither agreed nor disagreed, somewhat agreed, or strongly agreed with corresponding statements. Percentage ≤ 2 are not labelled in the figure to improve readability.CC BY · PubMed Central
Fig 4 Medical students’ attitudes towards the use of AI in their future practice. Percentages of students who strongly disagreed, somewhat disagreed, neither agreed nor disagreed, somewhat agreed, or strongly agreed with corresponding statements. Percentage ≤ 2 are not labelled in the figure to improve readability.
Fig 4 Medical students’ attitudes towards the use of AI in their future practice. Percentages of students who strongly disagreed, somewhat disagreed, neither agreed nor disagreed, somewhat agreed, or strongly agreed with corresponding statements. Percentage ≤ 2 are not labelled in the figure to improve readability.CC BY · PubMed Central

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Metadata

Authors
Stewart, J., Lu, J., Gahungu, N., Goudie, A., Fegan, P. G., Bennamoun, M., Sprivulis, P., & Dwivedi, G.
Affiliations
  • The University of Western Australia (AU)
  • Fiona Stanley Hospital (AU)
  • Curtin University (AU)
  • Government of Western Australia Department of Health (AU)
Corresponding author
Stewart, Jonathon
ORCID
Venue
PLOS ONE
Publisher
Public Library of Science (PLoS)
Published
2023-08-31
Volume
18
Issue
8
Pages
e0290642
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0290642
PMC
PMC10470885
OpenAlex
W4386323538
Cited by
104
References
21
Citations by year
2026: 33 · 2025: 41 · 2024: 27 · 2023: 3
FWCI
4.18
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • UWA Profiles and Research Repository (UWA) (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Western Australian Health Translation Network
  • the Australian Government’s Medical Research Future Fund
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Social Sciences › Education › Innovations in Medical Education
  • Social Sciences › Education › Artificial Intelligence in Education
Keywords
artificial intelligence in healthcare, medical students' attitudes, Western Australia, AI literacy, student perceptions of AI
MeSH terms
Adult, Artificial Intelligence, Attitude, Australia, Delivery of Health Care, Female, Humans, Obstetrics, Pregnancy, Students, Medical, Young Adult

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