AlZaabi Adhari, Masters Ken
Human and Clinical Anatomy Department, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Sultanate of Oman.
Medical Education and Informatics Department, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Sultanate of Oman.
BMC Med Educ. 2025 Jun 2;25(1):824. doi: 10.1186/s12909-025-07008-x.
Artificial intelligence (AI) is becoming increasingly relevant in healthcare, necessitating healthcare professionals' proficiency in its use. Medical students and practitioners require fundamental understanding and skills development to manage data, oversee AI tools and make informed decisions based on AI applications. Integrating AI into medical education is essential to meet this demand.
This cross-sectional study aimed to evaluate the level of undergraduate medical students' readiness for AI as they enter their clinical years at Sultan Qaboos University's College of Medicine and Health Sciences. The students' readiness was assessed after being exposed to various AI related topics in several courses in the preclinical phases of the medical curriculum. The Medical Artificial Intelligence Readiness Scale For Medical Students (MAIRS-MS) questionnaire was used as the study instrument.
A total of 84 out of 115 students completed the questionnaire (73.04% response rate). Of these, 45 (53.57%) were female while 39 (46.43%) were male. The cognition section, which evaluated the participants' cognitive preparedness in terms of knowledge of medical AI terminology, the logic behind AI applications, and data science, received the lowest score (Mean = 3.52). Conversely, the vision section of the questionnaire, which assessed the participants' capacity to comprehend the limitations and potential of medical AI, and anticipate opportunities and risks displayed the highest level of preparedness, had the highest score (Mean = 3.90). Notably, there were no statistically significant differences in AI competency scores by gender or academic year.
This study's findings suggest while medical students demonstrate a moderate level of AI-readiness as they enter their clinical years, significant gaps remain, particularly in cognitive areas such as understanding AI terminology, logic, and data science. The majority of students use ChatGPT as their AI tool, with a notable difference in attitudes between tech-savvy and non-tech-savvy individuals. Further efforts are needed to improve students' competency in evaluating AI tools. Medical schools should consider integrating AI into their curricula to enhance students' preparedness for future medical practice. Assessing students' readiness for AI in healthcare is crucial for identifying knowledge and skills gaps and guiding future training efforts.
人工智能（AI）在医疗保健领域的相关性日益增强，这就要求医疗保健专业人员熟练掌握其使用方法。医学生和从业者需要有基本的理解并开展技能培养，以管理数据、监督人工智能工具并基于人工智能应用做出明智决策。将人工智能融入医学教育对于满足这一需求至关重要。
这项横断面研究旨在评估苏丹卡布斯大学医学与健康科学学院的本科医学生在进入临床学习阶段时对人工智能的准备程度。在医学课程临床前阶段的几门课程中接触了各种与人工智能相关的主题后，对学生的准备程度进行了评估。使用医学生医学人工智能准备量表（MAIRS-MS）问卷作为研究工具。
115名学生中共有84名完成了问卷（回复率为73.04%）。其中，45名（53.57%）为女性，39名（46.43%）为男性。认知部分评估了参与者在医学人工智能术语知识、人工智能应用背后的逻辑和数据科学方面的认知准备情况，得分最低（平均值 = 3.52）。相反，问卷的愿景部分评估了参与者理解医学人工智能的局限性和潜力以及预测机会和风险的能力，显示出最高的准备水平，得分最高（平均值 = 3.90）。值得注意的是，人工智能能力得分在性别或学年方面没有统计学上的显著差异。
这项研究的结果表明，虽然医学生在进入临床学习阶段时表现出中等程度的人工智能准备水平，但仍存在显著差距，尤其是在理解人工智能术语、逻辑和数据科学等认知领域。大多数学生将ChatGPT用作他们的人工智能工具，技术娴熟和不娴熟的个体之间态度存在显著差异。需要进一步努力提高学生评估人工智能工具的能力。医学院校应考虑将人工智能纳入其课程，以增强学生对未来医疗实践的准备。评估学生在医疗保健领域对人工智能的准备程度对于识别知识和技能差距以及指导未来的培训工作至关重要。
