2024年埃及医学生对生成式人工智能的知识、态度和实践：一项横断面研究。

Medical students' knowledge, attitudes, and practices toward generative artificial intelligence in Egypt 2024: a Cross-Sectional study.

作者信息

Ghanem Omar A, Hagag Abdelmonam M, Kormod Muhammed E, El-Refaay Mennatullah A, Khedr Alaa Mahmoud, Abozaid Omnia M, Abdelmoaty Karim M, Hamed Mona S

机构信息

Faculty of Medicine, Zagazig University, Zagazig, Egypt.

Faculty of Medicine, Al-Azhar University, Madinat Nasr, Egypt.

出版信息

BMC Med Educ. 2025 May 28;25(1):790. doi: 10.1186/s12909-025-07329-x.

DOI:10.1186/s12909-025-07329-x

PMID:40437443

Abstract

BACKGROUND

Generative artificial intelligence (generative AI) has revolutionized the healthcare system for medical students and their educational process worldwide. Several studies assessed its efficacy in improving medical studies learning, and others assessed medical students' knowledge and attitudes about generative AI. So, we aim to determine the knowledge, attitudes, and practices of generative AI among medical students in Egypt.

METHODS

In 2024, a cross-sectional study using a semi-structured questionnaire was performed, targeting 423 students as a convenient sample from 10 selected Egyptian universities by simple random sampling. The questionnaire was distributed via online platforms such as WhatsApp, Facebook, X, Telegram, and Messenger. Data about sociodemographic characteristics, students' general knowledge about generative AI and its limitations, and their attitudes and practices, respectively, were collected.

RESULTS

About 2\3 (61.5%) of the studied students had satisfactory knowledge about generative AI and (44.7%) had a positive attitude. Males demonstrated significantly higher knowledge than females (69.3% vs. 55%, P-value = 0.003). Knowledge level also differs significantly by university (P-value < 0.001), with Suez-Canal and 6th October university students achieving the highest satisfactory scores. Key significant predictors that affect knowledge level include gender, university and study phase according to binary logistic regression results. Furthermore, there is a positive correlation between satisfactory knowledge and Practice level (r = 0.303, P < 0.001). Finally, most students use generative AI to check Grammar and prepare their homework or assignments.

CONCLUSION AND RECOMMENDATIONS

There is moderate knowledge and positive attitude about AI that were reflected in medical students' practice. However, knowledge about AI influenced by gender, university and study phase. Importantly, better knowledge significantly correlates with greater generative AI practice. Offering specialized courses or faculty modules about AI enhance awareness among Egyptian medical students. Such initiatives will enable them to gain knowledge and apply it effectively and wisely.

摘要

背景

生成式人工智能已彻底改变了全球医学生的医疗保健系统及其教育过程。多项研究评估了其在改善医学学习方面的功效，其他研究则评估了医学生对生成式人工智能的知识和态度。因此，我们旨在确定埃及医学生对生成式人工智能的知识、态度和实践情况。

方法

2024年，采用半结构化问卷进行了一项横断面研究，通过简单随机抽样从埃及10所选定大学中选取423名学生作为便利样本。问卷通过WhatsApp、Facebook、X、Telegram和Messenger等在线平台分发。分别收集了社会人口学特征、学生对生成式人工智能及其局限性的一般知识以及他们的态度和实践方面的数据。

结果

约三分之二（61.5%）的研究学生对生成式人工智能有满意的知识，（44.7%）持积极态度。男性的知识水平显著高于女性（69.3%对55%，P值 = 0.003）。知识水平在不同大学之间也存在显著差异（P值 < 0.001），苏伊士运河大学和十月六日大学的学生获得了最高的满意分数。根据二元逻辑回归结果，影响知识水平的关键显著预测因素包括性别、大学和学习阶段。此外，满意的知识与实践水平之间存在正相关（r = 0.303，P < 0.001）。最后，大多数学生使用生成式人工智能来检查语法并准备作业或任务。