Evidence map›Paper›PMID 35099397›Full record

ArticleJMIR medical education2022

Health Care Students' Perspectives on Artificial Intelligence: Countrywide Survey in Canada.

Minnie Teng, Rohit Singla, Olivia Yau, Daniel Lamoureux, Aurinjoy Gupta, Zoe Hu, Ricky Hu, Amira Aissiou, Shane Eaton, Camille Hamm and 9 more

Abstract read
In one paragraph

Article in JMIR medical education, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

76 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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16 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Minnie TengFaculty of Medicine, University of British Columbia, Vancouver, BC, Canada.ORCID https://orcid.org/0000-0002-8819-6516
Rohit SinglaFaculty of Medicine, University of British Columbia, Vancouver, BC, Canada.ORCID https://orcid.org/0000-0002-8876-654X
Olivia YauFaculty of Medicine, University of British Columbia, Vancouver, BC, Canada.ORCID https://orcid.org/0000-0002-4866-8910
Daniel LamoureuxNorthern Ontario School of Medicine, Thunder Bay, ON, Canada.ORCID https://orcid.org/0000-0001-5314-214X
Aurinjoy GuptaNorthern Ontario School of Medicine, Thunder Bay, ON, Canada.ORCID https://orcid.org/0000-0003-0518-6847
Zoe HuQueen's University, Kingston, ON, Canada.ORCID https://orcid.org/0000-0001-7353-4490
Ricky HuQueen's University, Kingston, ON, Canada.ORCID https://orcid.org/0000-0002-2843-3532
Amira AissiouUniversity of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0002-3061-7744
Shane EatonUniversity of Alberta, Edmonton, AB, Canada.ORCID https://orcid.org/0000-0002-8361-1733
Camille HammNorthern Ontario School of Medicine, Thunder Bay, ON, Canada.ORCID https://orcid.org/0000-0001-5158-9319
Sophie HuUniversity of Calgary, Calgary, AB, Canada.ORCID https://orcid.org/0000-0002-2904-8804
Dayton KellyNorthern Ontario School of Medicine, Sudbury, ON, Canada.ORCID https://orcid.org/0000-0003-3971-3692
Kathleen M MacMillanFaculty of Medicine, Dalhousie University, Saint John, NB, Canada.ORCID https://orcid.org/0000-0003-1796-8053
Shamir MalikTemerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0000-0003-2476-8279
Vienna MazzoliTemerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0000-0003-3716-284X
Yu-Wen TengVancouver Coastal Health, Vancouver, BC, Canada.ORCID https://orcid.org/0000-0003-2219-7062
Maria LarichevaFaculty of Arts, University of British Columbia, Vancouver, BC, Canada.ORCID https://orcid.org/0000-0003-0369-387X
Tal JarusFaculty of Medicine, University of British Columbia, Vancouver, BC, Canada.ORCID https://orcid.org/0000-0003-4124-7782
Thalia S FieldFaculty of Medicine, University of British Columbia, Vancouver, BC, Canada.ORCID https://orcid.org/0000-0002-1176-0633

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is no longer a futuristic concept; it is increasingly being integrated into health care. As studies on attitudes toward AI have primarily focused on physicians, there is a need to assess the perspectives of students across health care disciplines to inform future curriculum development.

objectiveThis study aims to explore and identify gaps in the knowledge that Canadian health care students have regarding AI, capture how health care students in different fields differ in their knowledge and perspectives on AI, and present student-identified ways that AI literacy may be incorporated into the health care curriculum.

methodsThe survey was developed from a narrative literature review of topics in attitudinal surveys on AI. The final survey comprised 15 items, including multiple-choice questions, pick-group-rank questions, 11-point Likert scale items, slider scale questions, and narrative questions. We used snowball and convenience sampling methods by distributing an email with a description and a link to the web-based survey to representatives from 18 Canadian schools.

resultsA total of 2167 students across 10 different health professions from 18 universities across Canada responded to the survey. Overall, 78.77% (1707/2167) predicted that AI technology would affect their careers within the coming decade and 74.5% (1595/2167) reported a positive outlook toward the emerging role of AI in their respective fields. Attitudes toward AI varied by discipline. Students, even those opposed to AI, identified the need to incorporate a basic understanding of AI into their curricula.

conclusionsWe performed a nationwide survey of health care students across 10 different health professions in Canada. The findings would inform student-identified topics within AI and their preferred delivery formats, which would advance education across different health care professions.

Indexed as

allied health educationartificial intelligenceeducationhealth care studentsmedical curriculummedical educationmedical students

Identifiers

PMID35099397
PMCPMC8845000

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.