医学生与病理实习生对人工智能的认知与态度调查研究

IF 3.2 Q1 EDUCATION, SCIENTIFIC DISCIPLINES
Anwar Rjoop, Mohammad Al-Qudah, Raja Alkhasawneh, Nesreen Bataineh, Maram Abdaljaleel, Moayad A Rjoub, Mustafa Alkhateeb, Mohammad Abdelraheem, Salem Al-Omari, Omar Bani-Mari, Anas Alkabalan, Saoud Altulaih, Iyad Rjoub, Rula Alshimi
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引用次数: 0

摘要

背景:人工智能(AI)将塑造医疗实践的未来。医学生的观点和理解对于指导教育课程和培训的发展至关重要。目的:本研究旨在评估和比较医科学生在全科医学和视觉导向领域(病理学)中与医学人工智能相关的态度,同时阐明他们对人工智能在快速发展的人工智能增强医疗保健领域中的预期作用。方法:这是一项横断面研究,采用基于网络的封闭式问卷调查。该调查涉及约旦5所公立医学院所有教育水平的医学生,以及4个住院医师项目的病理学住院医师。结果:共394人参与调查,其中医学生328人,住院医师66人。大多数受访者(272/394,69%)已经了解AI和医学领域的深度学习,主要依靠网站获取AI相关信息,而只有14%(56/394)的受访者通过医学院了解AI。认为自己是技术专家的受访者与不认为自己是技术专家的受访者在意识上存在统计学上的显著差异(P=.03)。超过一半的受访者认为AI可以用于自动诊断疾病(213/394,54.1%同意),医学生比病理住院医师更同意(P=.04)。然而,超过三分之一的人对最近的人工智能发展表示担忧(167/394,42.4%同意)。三分之二的受访者不认为他们的医学院教育了他们关于人工智能及其潜在用途的知识(261/394,66.2%不同意),而46.2%(182/394)的受访者表示有兴趣学习医学上的人工智能。在病理特异性问题上,75.4%(297/394)的受访者认为人工智能可以自动识别切片检查中的病理。医学生与病理住院医师的同意程度有显著差异(P=.001)。总体而言,医学生和病理实习生的反应相似。结论:应在医学院校课程中引入人工智能教育,提高医学生对人工智能的认识和态度。学生们一致认为,他们需要了解人工智能的应用、潜在危险以及法律和伦理影响。这是第一个分析约旦医学生对人工智能的看法和认识的研究,也是第一个包括病理住院医生观点的研究。这些发现与国际上早期的研究一致。与先前的研究相比,这些态度在低收入国家和工业化国家也很相似,这突出表明,在这个技术迅速发展的时代,需要制定一项全球战略,向各地的医学生介绍人工智能教学。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Awareness and Attitude Toward Artificial Intelligence Among Medical Students and Pathology Trainees: Survey Study.

Background: Artificial intelligence (AI) is set to shape the future of medical practice. The perspective and understanding of medical students are critical for guiding the development of educational curricula and training.

Objective: This study aims to assess and compare medical AI-related attitudes among medical students in general medicine and in one of the visually oriented fields (pathology), along with illuminating their anticipated role of AI in the rapidly evolving landscape of AI-enhanced health care.

Methods: This was a cross-sectional study that used a web-based survey composed of a closed-ended questionnaire. The survey addressed medical students at all educational levels across the 5 public medical schools, along with pathology residents in 4 residency programs in Jordan.

Results: A total of 394 respondents participated (328 medical students and 66 pathology residents). The majority of respondents (272/394, 69%) were already aware of AI and deep learning in medicine, mainly relying on websites for information on AI, while only 14% (56/394) were aware of AI through medical schools. There was a statistically significant difference in awareness among respondents who consider themselves tech experts compared with those who do not (P=.03). More than half of the respondents believed that AI could be used to diagnose diseases automatically (213/394, 54.1% agreement), with medical students agreeing more than pathology residents (P=.04). However, more than one-third expressed fear about recent AI developments (167/394, 42.4% agreed). Two-thirds of respondents disagreed that their medical schools had educated them about AI and its potential use (261/394, 66.2% disagreed), while 46.2% (182/394) expressed interest in learning about AI in medicine. In terms of pathology-specific questions, 75.4% (297/394) agreed that AI could be used to identify pathologies in slide examinations automatically. There was a significant difference between medical students and pathology residents in their agreement (P=.001). Overall, medical students and pathology trainees had similar responses.

Conclusions: AI education should be introduced into medical school curricula to improve medical students' understanding and attitudes. Students agreed that they need to learn about AI's applications, potential hazards, and legal and ethical implications. This is the first study to analyze medical students' views and awareness of AI in Jordan, as well as the first to include pathology residents' perspectives. The findings are consistent with earlier research internationally. In comparison with prior research, these attitudes are similar in low-income and industrialized countries, highlighting the need for a global strategy to introduce AI instruction to medical students everywhere in this era of rapidly expanding technology.

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来源期刊
JMIR Medical Education
JMIR Medical Education Social Sciences-Education
CiteScore
6.90
自引率
5.60%
发文量
54
审稿时长
8 weeks
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