Al Shahrani Abeer, Alhumaidan Norah, AlHindawi Zeena, Althobaiti Abdullah, Aloufi Khalid, Almughamisi Rasil, Aldalbahi Ahad
Family and Community Medicine Department, College of Medicine, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia.
College of Medicine, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia.
Healthcare (Basel). 2024 Dec 11;12(24):2504. doi: 10.3390/healthcare12242504.
BACKGROUND/OBJECTIVES: Artificial intelligence (AI) is rapidly reshaping healthcare, offering transformative potential for diagnostics, treatment, and patient management. Despite its growing significance, there is limited integration of AI education in medical curricula, raising concerns about the readiness of future healthcare professionals to utilize AI technologies. This study aims to evaluate the readiness of medical students in Saudi Arabia to embrace AI and to assess the current state of AI education, AI Application use, and future perspectives for medical students.
a cross-sectional design was employed. It involved medical students from various regions of Saudi Arabia. Data were collected using an anonymous, online, structured, and validated tool from previous studies. The survey included sociodemographic information, details on AI education, the usage of AI applications, intended specialties, and a Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS). The data were extracted and revised in an Excel sheet. Statistical analysis was conducted using the IBM SPSS computer program with appropriate statistical tests.
This study enrolled 572 medical students, with a mean age of 21.93 years. Most students were Saudi (99.0%), and 43.7% lived in the western region of Saudi Arabia. Most students attended a government medical college (97.41%), and 64.3% of students were in their clinical years. Only 14.5% of the students had received formal AI education, while 34.3% had participated in extracurricular AI training. The mean (SD) MAIRS-MS score was 68.39 (18.3), with higher scores associated with female students, those from the central region, and those with advanced English and computer technology skills ( < 0.001).
there is limited AI education and moderate AI readiness among medical students in Saudi colleges, with significant variability in terms of gender, region, and educational background. These findings underscore the need to integrate AI education into medical curricula to better prepare future physicians for AI-enabled healthcare systems.
背景/目的：人工智能（AI）正在迅速重塑医疗保健领域，为诊断、治疗和患者管理带来变革潜力。尽管其重要性日益凸显，但医学课程中人工智能教育的整合有限，这引发了人们对未来医疗保健专业人员使用人工智能技术准备情况的担忧。本研究旨在评估沙特阿拉伯医学生接受人工智能的准备情况，并评估人工智能教育、人工智能应用使用的现状以及医学生的未来展望。
采用横断面设计。研究对象包括来自沙特阿拉伯各个地区的医学生。数据通过使用先前研究中经过验证的匿名在线结构化工具收集。该调查包括社会人口统计学信息、人工智能教育细节、人工智能应用的使用情况、意向专业以及医学生医学人工智能准备度量表（MAIRS-MS）。数据在Excel工作表中提取和修订。使用IBM SPSS计算机程序进行适当的统计检验进行统计分析。
本研究招募了572名医学生，平均年龄为21.93岁。大多数学生是沙特人（99.0%），43.7%居住在沙特阿拉伯西部地区。大多数学生就读于政府医学院（97.41%），64.3%的学生处于临床学习阶段。只有14.5%的学生接受过正规的人工智能教育，而34.3%的学生参加过课外人工智能培训。MAIRS-MS评分的平均值（标准差）为68.39（18.3），女生、来自中部地区的学生以及具有高级英语和计算机技术技能的学生得分较高（<0.001）。
沙特各学院的医学生中人工智能教育有限，接受人工智能的准备程度中等，在性别、地区和教育背景方面存在显著差异。这些发现强调了将人工智能教育纳入医学课程的必要性，以便更好地让未来的医生为人工智能支持的医疗系统做好准备。
