Exploring health care learners’ perceptions of AI integration in the curriculum
A survey tool and findings
Bibliographic Data
| ID | 22424296 |
|---|---|
| Authors | Linda Chang (0000-0001-9681-5025, University of Illinois Chicago, Rockford campus, corresponding author), Maura Polansky (0009-0006-2865-1966, University of Illinois Chicago), Darvin Yi (University of Illinois Chicago), Martin Macdowell (0000-0002-7648-852X, Rockford University), Radhika Sreedhar (0000-0002-1598-2292, University of Illinois Chicago), Dawn Mosher (0009-0002-5837-3611, Saint Anthony College of Nursing), A Schwartz (0000-0003-3809-6637, University of Illinois Chicago) |
| Year | 2026 |
| Volume | 26 |
| Issue | 1 |
| Publication date | 2026-03-10 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | BMC Medical Education (JOURNAL) |
| Journal identifiers | ISSN: 1472-6920 • E-ISSN: 1472-6920 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1186/s12909-026-08931-3 |
| PMID | 41808119 |
| OpenAlex | W7134984665 |
| Language | EN |
| References cited | 24 |
BACKGROUND: Few studies have assessed students in different healthcare disciplines’ perceptions of the importance of learning standard competencies in AI technology. This study aimed to evaluate the learning needs, apprehensions/anxieties, and digital self-efficacy of students in medicine, nursing, and pharmacy regarding AI technology in healthcare. METHODS: This cross-sectional survey study included 521 students: 384 medical, 67 nursing, and 78 pharmacy students, with response rates of 32%, 61%, and 52% from the colleges of medicine, nursing, and pharmacy, respectively. Survey data were collected over a 3-month period using a self-reported questionnaire. Data analysis was conducted using SPSS, including descriptive statistics, ANOVA, and chi-square tests. RESULTS: Students from all three disciplines agreed on the importance of learning about AI in healthcare, with agreement rates for the six core AI skill domains ranging from 80 to 92%. The AI Learning Anxiety/Fears questionnaire revealed varying anxiety levels about AI technology learning across the disciplines. Over 20% of students across all disciplines agreed or strongly agreed that they experience anxiety on the AI Learning Anxiety/Fears questionnaire. The digital self-efficacy scale score was negatively correlated with AI learning anxiety (r=-0.32, p = 0.01). CONCLUSION: This study offers insights into students’ perspectives on learning about AI, which will inform the development of effective AI curricula. These findings highlight the need for standardized AI curricula that can address learning needs and reduce anxiety across the healthcare disciplines.
Curriculum · Health care · MEDLINE · Patient care · Perception · AI in Service Interactions · Artificial Intelligence in Healthcare and Education · Simulation-Based Education in Healthcare
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| Highly cited | No |
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