Knowledge Attitudes and Ethical Concerns About Artificial Intelligence Among Medical Students at Taibah University: A Cross-Sectional Study.

IF 1.7 Q2 EDUCATION, SCIENTIFIC DISCIPLINES
Advances in Medical Education and Practice Pub Date : 2025-09-01 eCollection Date: 2025-01-01 DOI:10.2147/AMEP.S528281
Samah Alfahl
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引用次数: 0

Abstract

Background: 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.

Methods: 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.

Results: 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).

Conclusion: 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.

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Taibah大学医学生对人工智能的知识态度和伦理关注:一项横断面研究
背景:人工智能(AI)是医学教育和医疗保健领域越来越重要的工具。了解未来医生对人工智能整合的准备程度,对于开发有效的课程和促进负责任地使用这项技术至关重要。方法:本横断面研究在Taibah大学的189名医学生中进行,采用一份有效的、自我管理的在线问卷。该工具测量了人工智能知识(7项)、态度(10项)、实践(7项)和感知障碍。调查采用李克特5分制。描述性和推断性统计,包括单因素方差分析,用于分析不同学年的差异。结果: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)的学生了解机器学习和深度学习。只有11.21% (n=21)的人接受过正式的人工智能指导,21.18% (n=40)的人参加过专门的课程。74.60% (n=141)的人认为人工智能将彻底改变教育,41.91% (n=79)的人担心人工智能会取代教师。52.02% (n=98)定期使用人工智能备考。相比之下,只有11.64% (n=22)的人将其用于客观结构化临床检查(OSCE)准备。主要障碍包括伦理问题(n=44)、剽窃风险(n=56)、缺乏知识(n=46)和工具获取有限(n=28)。结论:医学生对人工智能在教育中的应用表现出谨慎的乐观态度,他们的实践知识有限,并担心伦理影响。整合结构化的人工智能教育、培训计划和道德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。
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来源期刊
Advances in Medical Education and Practice
Advances in Medical Education and Practice EDUCATION, SCIENTIFIC DISCIPLINES-
CiteScore
3.10
自引率
10.00%
发文量
189
审稿时长
16 weeks
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