Alfahl Samah
Department of Family and Community Medicine, College of Medicine, Taibah University, Madinah, Saudi Arabia.
Adv Med Educ Pract. 2025 Sep 1;16:1609-1620. doi: 10.2147/AMEP.S528281. eCollection 2025.
Artificial Intelligence (AI) is increasingly relevant tool to medical education and healthcare. Understanding the readiness of future physicians for AI integration is essential for developing effective curricula and fostering responsible use of this technology.
This cross-sectional study was conducted among 189 medical students at Taibah University using a validated, self-administered online questionnaire. The tool measured AI knowledge (7 items), attitudes (10 items), practices (7 items), and perceived barriers. Responses were captured on a 5-point Likert scale. Descriptive and inferential statistics, including one-way ANOVA, were used to analyze differences across academic years.
Out of 189 respondents, 53.97% (n=102) of students reported familiarity with basic AI concepts, and 5.66% (n=11) were aware of machine learning and deep learning. Only 11.21% (n=21) had received formal AI instruction, and 21.18% (n=40) had attended dedicated courses. 74.60% (n=141) believed AI would revolutionize education, yet 41.91% (n=79) expressed concerns about AI replacing teachers. 52.02% (n=98) used AI regularly for exam preparation. In comparison, only 11.64% (n=22) used it for Objective Structured Clinical Examination (OSCE) preparation Key barriers included ethical concerns (n=44 responses), risk of plagiarism (n=56), lack of knowledge (n=46), and limited access to tools (n=28).
Medical students display cautious optimism about AI in education, with limited practical knowledge and concerns about ethical implications. Integrating structured AI education, training program, and ethical guideline is essential for preparing students for an AI-enhanced healthcare landscape.
人工智能（AI）在医学教育和医疗保健领域正日益成为一种重要工具。了解未来医生对整合人工智能的准备情况对于制定有效的课程以及促进对该技术的合理使用至关重要。
本横断面研究在泰巴赫大学的189名医学生中进行，使用经过验证的自填式在线问卷。该工具测量了人工智能知识（7项）、态度（10项）、实践（7项）以及感知到的障碍。回答采用5点李克特量表进行记录。使用描述性和推断性统计，包括单因素方差分析，来分析不同学年之间的差异。
在189名受访者中，53.97%（n = 102）的学生表示熟悉基本的人工智能概念，5.66%（n = 11）了解机器学习和深度学习。只有11.21%（n = 21）接受过正式的人工智能教学，21.18%（n = 40）参加过专门课程。74.60%（n = 141）认为人工智能将给教育带来变革，但41.91%（n = 79）对人工智能取代教师表示担忧。52.02%（n = 98）经常使用人工智能进行考试准备。相比之下，只有11.64%（n = 22）将其用于客观结构化临床考试（OSCE）准备。主要障碍包括伦理问题（44份回答）、抄袭风险（56份）、知识不足（46份）以及工具获取受限（28份）。
医学生对教育中的人工智能表现出谨慎的乐观态度，实践知识有限且对伦理影响存在担忧。整合结构化的人工智能教育、培训计划和伦理准则对于让学生为人工智能增强的医疗保健环境做好准备至关重要。
