ArticleBMC medical education2025
Perceived artificial intelligence readiness in medical and health sciences education: a survey study of students in Saudi Arabia.
Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Nursing students' readiness for and acceptance of artificial intelligence technologies in clinical skills training: A cross-sectional study.International journal of nursing studies advances · 2026Article
- Use, Concerns, and Perspectives on AI in Health Care Among French Health Professionals and Students: Web-Based Cross-Sectional Survey.JMIR medical education · 2026Article
- From hype to reality: the feasibility, dilemmas, and solutions of Gen AI in medical education from students' perspectives.BMC medical education · 2026Article
- Faculty Perspectives on AI Integration in Anatomy Education in the United Arab Emirates: Cross-Sectional Survey.JMIR medical education · 2026Article
- Factors influencing large language model adoption among dental students: a cross-sectional study.Scientific reports · 2026Article
- Attitudes and readiness of nursing students practising in surgical units towards artificial intelligence: a cross-sectional study.BMC medical education · 2026Article
- Knowledge, attitudes, and practices of pharmacy students and graduates regarding artificial intelligence in healthcare: a multi-regional cross-sectional study predominantly from the Asir region of Saudi Arabia.Frontiers in public health · 2026Article
- Public Knowledge and Acceptance of Artificial Intelligence-Assisted Physicians in Saudi Arabia: A Cross-Sectional Study.International journal of general medicine · 2026Article
- ChatGPT in medical education: a cross-sectional analysis of usage, attitudes, perceptions, and practices among Saudi medical students.Frontiers in artificial intelligence · 2026Article
- Artificial intelligence readiness and its association with artificial intelligence literacy among Chinese medical students: a latent profile analysis.Frontiers in public health · 2026Article
- Nursing Students' Perception of and Readiness for Artificial Intelligence in Saudi Arabia.Nursing open · 2025Article
- Preparing Tomorrow's Physicians: The Case for Machine Learning in Medical Education.Journal of medical systems · 2025Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundAs artificial intelligence (AI) becomes increasingly integral to healthcare, preparing medical and health sciences students to engage with AI technologies is critical.
objectivesThis study investigates the perceived AI readiness of medical and health sciences students in Saudi Arabia, focusing on four domains: cognition, ability, vision, and ethical perspectives, using the Medical Artificial Intelligences Readiness Scale for Medical Students (MAIRS-MS).
methodsA cross-sectional survey was conducted between October and November 2023, targeting students from various universities and medical schools in Saudi Arabia. A total of 1,221 students e-consented to participate. Data were collected via a 20-minute Google Form survey, incorporating a 22-item MAIRS-MS scale. Descriptive and multivariate statistical analyses were performed using Stata version 16.0. Cronbach alpha was calculated to ensure reliability, and least squares linear regression was used to explore relationships between students' demographics and their AI readiness scores.
resultsThe overall mean AI readiness score was 62 out of 110, indicating a moderate level of readiness. Domain-specific scores revealed generally consistent levels of readiness: cognition (58%, 23.2/40), ability (57%, 22.8/40), vision (54%, 8.1/15) and ethics (57%, 8.5/15). Nearly 44.5% of students believed AI-related courses should be mandatory whereas only 41% reported having such a required course in their program.
conclusionsMedical and health sciences students in Saudi Arabia demonstrate moderate AI readiness across cognition, ability, vision, and ethics, indicating both a solid foundation and areas for growth. Enhancing AI curricula and emphasizing practical, ethical, and forward-thinking skills can better equip future healthcare professionals for an AI-driven future.
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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.