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Health Care Students’ Perspectives on Artificial Intelligence: Countrywide Survey in Canada
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 fu...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8845000/ https://www.ncbi.nlm.nih.gov/pubmed/35099397 http://dx.doi.org/10.2196/33390 |
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author | Teng, Minnie Singla, Rohit Yau, Olivia Lamoureux, Daniel Gupta, Aurinjoy Hu, Zoe Hu, Ricky Aissiou, Amira Eaton, Shane Hamm, Camille Hu, Sophie Kelly, Dayton MacMillan, Kathleen M Malik, Shamir Mazzoli, Vienna Teng, Yu-Wen Laricheva, Maria Jarus, Tal Field, Thalia S |
author_facet | Teng, Minnie Singla, Rohit Yau, Olivia Lamoureux, Daniel Gupta, Aurinjoy Hu, Zoe Hu, Ricky Aissiou, Amira Eaton, Shane Hamm, Camille Hu, Sophie Kelly, Dayton MacMillan, Kathleen M Malik, Shamir Mazzoli, Vienna Teng, Yu-Wen Laricheva, Maria Jarus, Tal Field, Thalia S |
author_sort | Teng, Minnie |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8845000 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-88450002022-03-10 Health Care Students’ Perspectives on Artificial Intelligence: Countrywide Survey in Canada Teng, Minnie Singla, Rohit Yau, Olivia Lamoureux, Daniel Gupta, Aurinjoy Hu, Zoe Hu, Ricky Aissiou, Amira Eaton, Shane Hamm, Camille Hu, Sophie Kelly, Dayton MacMillan, Kathleen M Malik, Shamir Mazzoli, Vienna Teng, Yu-Wen Laricheva, Maria Jarus, Tal Field, Thalia S JMIR Med Educ Original Paper 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. JMIR Publications 2022-01-31 /pmc/articles/PMC8845000/ /pubmed/35099397 http://dx.doi.org/10.2196/33390 Text en ©Minnie Teng, Rohit Singla, Olivia Yau, Daniel Lamoureux, Aurinjoy Gupta, Zoe Hu, Ricky Hu, Amira Aissiou, Shane Eaton, Camille Hamm, Sophie Hu, Dayton Kelly, Kathleen M MacMillan, Shamir Malik, Vienna Mazzoli, Yu-Wen Teng, Maria Laricheva, Tal Jarus, Thalia S Field. Originally published in JMIR Medical Education (https://mededu.jmir.org), 31.01.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Education, is properly cited. The complete bibliographic information, a link to the original publication on https://mededu.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Teng, Minnie Singla, Rohit Yau, Olivia Lamoureux, Daniel Gupta, Aurinjoy Hu, Zoe Hu, Ricky Aissiou, Amira Eaton, Shane Hamm, Camille Hu, Sophie Kelly, Dayton MacMillan, Kathleen M Malik, Shamir Mazzoli, Vienna Teng, Yu-Wen Laricheva, Maria Jarus, Tal Field, Thalia S Health Care Students’ Perspectives on Artificial Intelligence: Countrywide Survey in Canada |
title | Health Care Students’ Perspectives on Artificial Intelligence: Countrywide Survey in Canada |
title_full | Health Care Students’ Perspectives on Artificial Intelligence: Countrywide Survey in Canada |
title_fullStr | Health Care Students’ Perspectives on Artificial Intelligence: Countrywide Survey in Canada |
title_full_unstemmed | Health Care Students’ Perspectives on Artificial Intelligence: Countrywide Survey in Canada |
title_short | Health Care Students’ Perspectives on Artificial Intelligence: Countrywide Survey in Canada |
title_sort | health care students’ perspectives on artificial intelligence: countrywide survey in canada |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8845000/ https://www.ncbi.nlm.nih.gov/pubmed/35099397 http://dx.doi.org/10.2196/33390 |
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