Artificial Intelligence (AI) readiness among medical students in Yemen: a cross-sectional study using the MAIRS-MS Scale
4 affiliations
- 1Faculty of Medicine, University of Aden, Aden, Yemen
- 2Faculty of Pharmacy, University of Aden, Aden, Yemen
- 3Faculty of Dentistry, University of Aden, Aden, Yemen
- 4Department of Internal Medicine, Faculty of Medicine, University of Aden, Aden, Yemen
Abstract
Background: Artificial intelligence (AI) is becoming increasingly integrated into modern healthcare and medical education. Recent advances in AI applications, including diagnostic support systems and healthcare technologies, have highlighted the growing need to prepare future healthcare professionals to work effectively with these tools. However, limited educational integration and ongoing ethical concerns remain major challenges, particularly in developing countries such as Yemen. This study aimed to assess the readiness of medical and health sciences students at the University of Aden toward AI applications in healthcare.
Methods: A cross-sectional study was conducted among undergraduate students from the medical and health sciences faculties at the University of Aden, Yemen. Data were collected using an electronic questionnaire based on the previously validated Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS). The instrument consists of 22 items distributed across four domains: cognition, ability, vision, and ethics. Responses were recorded using a five-point Likert scale, with higher scores reflecting greater AI readiness.
Results: A total of 415 students from the faculties of Medicine, Dentistry, Pharmacy, Medical Laboratory Sciences, and Nursing participated in the study. The overall mean AI readiness score was 79.82 out of 110, indicating a relatively favorable perceived AI readiness. Among the evaluated domains, the highest scores were observed in ethics and ability. Male students demonstrated significantly higher cognition scores compared with female students (27.73 vs. 26.07, p = 0.005). Most participants reported previous awareness of AI technologies (80.2%), whereas 44.8% indicated prior experience using AI in medical contexts. No statistically significant associations were identified between overall AI readiness and age, GPA, academic year, or income level.
Conclusion: Medical and health sciences students in Yemen demonstrated a relatively favorable perceived AI readiness toward artificial intelligence in healthcare. Expanding AI-related education and practical exposure within undergraduate curricula may help improve students’ preparedness for future AI-driven medical practice.
Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s12909-026-10106-z.
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BibTeX
@article{almadhagi2026artificial,
title = {{Artificial Intelligence (AI) readiness among medical students in Yemen: a cross-sectional study using the MAIRS-MS Scale}},
author = {Omar A. Al-Madhagi and Hussam H. Al-Shadadi and Abdullah K. Al-Hubaishi and Sami A. Dobian and Amr K. Alkhalifi and Linda Mustafa Hashem},
journal = {BMC Medical Education},
year = {2026},
month = aug,
doi = {10.1186/s12909-026-10106-z},
url = {https://doi.org/10.1186/s12909-026-10106-z},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Artificial Intelligence (AI) readiness among medical students in Yemen: a cross-sectional study using the MAIRS-MS Scale
AU - Omar A. Al-Madhagi
AU - Hussam H. Al-Shadadi
AU - Abdullah K. Al-Hubaishi
AU - Sami A. Dobian
AU - Amr K. Alkhalifi
AU - Linda Mustafa Hashem
PY - 2026
DA - 2026/08/07
JO - BMC Medical Education
DO - 10.1186/s12909-026-10106-z
UR - https://doi.org/10.1186/s12909-026-10106-z
AB - Background: Artificial intelligence (AI) is becoming increasingly integrated into modern healthcare and medical education. Recent advances in AI applications, including diagnostic support systems and healthcare technologies, have highlighted the growing need to prepare future healthcare professionals to work effectively with these tools. However, limited educational integration and ongoing ethical concerns remain major challenges, particularly in developing countries such as Yemen. This study aimed to assess the readiness of medical and health sciences students at the University of Aden toward AI applications in healthcare. Methods: A cross-sectional study was conducted among undergraduate students from the medical and health sciences faculties at the University of Aden, Yemen. Data were collected using an electronic questionnaire based on the previously validated Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS). The instrument consists of 22 items distributed across four domains: cognition, ability, vision, and ethics. Responses were recorded using a five-point Likert scale, with higher scores reflecting greater AI readiness. Results: A total of 415 students from the faculties of Medicine, Dentistry, Pharmacy, Medical Laboratory Sciences, and Nursing participated in the study. The overall mean AI readiness score was 79.82 out of 110, indicating a relatively favorable perceived AI readiness. Among the evaluated domains, the highest scores were observed in ethics and ability. Male students demonstrated significantly higher cognition scores compared with female students (27.73 vs. 26.07, p = 0.005). Most participants reported previous awareness of AI technologies (80.2%), whereas 44.8% indicated prior experience using AI in medical contexts. No statistically significant associations were identified between overall AI readiness and age, GPA, academic year, or income level. Conclusion: Medical and health sciences students in Yemen demonstrated a relatively favorable perceived AI readiness toward artificial intelligence in healthcare. Expanding AI-related education and practical exposure within undergraduate curricula may help improve students’ preparedness for future AI-driven medical practice. Supplementary Information: The online version contains supplementary material available at https://doi.org/10.1186/s12909-026-10106-z.
SN - 1472-6920
ER -