Health Care Students’ Perspectives on Artificial Intelligence: Countrywide Survey in Canada
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Abstract
Background: Artificial 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. Objective: This 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. Methods: The 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. Results: A 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. Conclusions: We 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.
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63% of Canadian medical students recognize the importance of AI literacy training.
“Surveys indicate strong backing for AI literacy training, with 81% of UK physicians4 and 63% of Canadian medical students recognizing its importance12, while an overwhelming 93.8% of students in Turkey support structured AI education, particularly in the domains of knowledge, applications, and ethics13.”
From Developing a Canadian artificial intelligence medical curriculum using a Delphi study (2024) · cites this paper as [12]
The Results (Curriculum Integration; page unavailable) report that 63.36% of respondents believed basic AI literacy should be part of their curriculum. But the survey included students from 10 health professions (Abstract, Results), so the paper does not establish that 63% of Canadian medical students specifically held that view. (LLM, conf=0.89)
Experimental — accuracy not yet measured15 included studies were conducted in high-income countries and the remaining studies in low- and middle-income countries.
“Specifically, 15 studies were conducted in HICs [26–40], while other studies were conducted in LMICs [23, 24, 41–49].”
The survey used by Minnie Teng et al. was piloted by a small group from the same university, and questions were revised for clarity according to feedback from the pilot group.
“The survey was piloted by a small group from the same university. Questions were revised for clarity according to feedback from the pilot group.”
63.36% of medical students support fundamental AI literacy training.
“Banerjee et al. and Teng et al., reporting that 81% of physicians and 63·36% of medical students, respectively, support fundamental AI literacy training [7,8].”
From An evidence-based approach to artificial intelligence education for medical students: A systematic review (2023) · cites this paper as [8]
81% of physicians support fundamental AI literacy training.
“Banerjee et al. and Teng et al., reporting that 81% of physicians and 63·36% of medical students, respectively, support fundamental AI literacy training [7,8].”
From An evidence-based approach to artificial intelligence education for medical students: A systematic review (2023) · cites this paper as [8]
One study met the NOS criteria for good and 22 studies met the NOS criteria for fair.
“One study met the NOS criteria for good [17] and 22 studies met the NOS criteria for fair [7,8,18–36,37].”
From An evidence-based approach to artificial intelligence education for medical students: A systematic review (2023) · cites this paper as [8]
Perceptions and attitudes of medical students and professionals reflected some hesitancy about AI's impacts on medicine, such as unemployment, but ultimately showed overwhelming support in favour of AI.
“The perceptions and attitudes of medical students and professionals reflected some hesitancy surrounding the impacts of AI on medicine, such as unemployment [25], but ultimately showed overwhelming support in favour of AI [7–9,26].”
From An evidence-based approach to artificial intelligence education for medical students: A systematic review (2023) · cites this paper as [8]
There have been no studies to date that gauge the interest and perceived need for AI education among undergraduate medical students.
“However, there have been no studies to date that identify and assess exposure to existing educational opportunities about AI in medicine among undergraduate medical students, or that gauge the interest and perceived need for AI education among these learners [7, 8].”
From Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study (2022) · cites this paper as [7]
Previous studies have found poor self-reported knowledge about AI among medical trainees, including undergraduate medical students.
“These studies have also found poor self-reported knowledge about AI among medical trainees, including undergraduate medical students [7, 8].”
From Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study (2022) · cites this paper as [7]
Previous studies have found that undergraduate medical students believe AI will be an integral part of medical practice in the future.
“Previous studies have addressed the perceptions of undergraduate medical students about AI in medicine, noting that they believe AI will be an integral part of medical practise in the future [7, 8].”
From Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study (2022) · cites this paper as [7]
There have been no studies to date that identify and assess exposure to existing educational opportunities about AI in medicine among undergraduate medical students.
“However, there have been no studies to date that identify and assess exposure to existing educational opportunities about AI in medicine among undergraduate medical students, or that gauge the interest and perceived need for AI education among these learners [7, 8].”
From Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study (2022) · cites this paper as [7]
Medical students want AI incorporated into their formal medical curriculum.
“As both this study and previous surveys have confirmed that medical students want AI incorporated into their formal medical curriculum, any such changes should be well received by the undergraduate medical learner population [7, 17].”
From Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study (2022) · cites this paper as [7]
The study's findings are consistent with previous studies that identified limited knowledge of AI among medical trainees.
“Our findings are consistent with previous studies of medical learners, which have also identified limited knowledge of AI among medical trainees [7, 8, 16, 17].”
From Exploration of exposure to artificial intelligence in undergraduate medical education: a Canadian cross-sectional mixed-methods study (2022) · cites this paper as [7]
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Attitudes and anxiety levels of nursing students toward artificial intelligence
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Double bistable superposition strategy for improving the performance of triboelectric nanogenerator
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Artificial intelligence (AI) in nursing administration: Challenges and opportunities
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Possible Health Benefits and Risks of DeepFake Videos: A Qualitative Study in Nursing Students
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Artificial Intelligence Anxiety in Nursing Students
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PEMANFAATAN ARTIFICIAL INTELLIGENCE DALAM BIDANG KESEHATAN
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AI in Hospital Administration and Formulary Design
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Artificial Intelligence and Digital Divide in Physiotherapy Education
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Li, C., Tsuei, S. H., & Wu, H. (2025) · JMIR Medical Education · doi:10.2196/80604 · Cited by 12 · see citing works
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Micro-Credentials and AI in Higher Education
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Transforming Healthcare with Large Language Models and AI Agents
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AI Literacy, Technical Skills, and Ethical Awareness in Predicting Students’ Learning Performance
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Integrating AI into global fluid healthcare workforces: student perspectives and future trends
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AI in UK Medical Education: A Framework for Curriculum Reform
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Artificial Intelligence in Health and Applications
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From Anatomy to Algorithm: Scope of AI-Assisted Diagnostic Competencies in Health Sciences Education
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Artificial Intelligence in Health Professions Education: Qualitative Study of Student Experiences
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Leveraging Undergraduate Perspectives to Redefine AI Literacy
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- Authors
- Teng, M., Singla, R., Yau, O., Lamoureux, D., Gupta, A., Hu, Z., Hu, R., Aissiou, A., Eaton, S., Hamm, C., Hu, S., Kelly, D., MacMillan, K. M., Malik, S., Mazzoli, V., Teng, Y.-W., Laricheva, M., Jarus, T., & Field, T. S.
- Affiliations
- University of British Columbia (CA)
- NOSM University (CA)
- Queen's University (CA)
- University of Alberta (CA)
- University of Calgary (CA)
- Dalhousie University (CA)
- University of Toronto (CA)
- Vancouver Coastal Health (CA)
- Corresponding author
- Teng, Minnie
- ORCID
- Venue
- JMIR Medical Education
- Publisher
- JMIR Publications Inc.
- Published
- 2022-01-31
- Volume
- 8
- Issue
- 1
- Pages
- e33390
- ISSN
- 2369-3762 (ISSN-L)
- PMC
- PMC8845000
- OpenAlex
- W4200218394
- Cited by
- 214
- References
- 43
- Citations by year
- 2026: 53 · 2025: 72 · 2024: 60 · 2023: 19 · 2022: 9
- FWCI
- 6.41
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR Medical Education (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- University of British Columbia
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Keywords
- artificial intelligence, health professions students, attitudes toward AI, AI literacy, health professions education, curriculum development, student perceptions
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