Optimistic and ambivalent attitudes toward clinical artificial intelligence.

IF 1.4 4区 医学 Q2 MEDICINE, GENERAL & INTERNAL
Turkish Journal of Medical Sciences Pub Date : 2026-05-16 eCollection Date: 2026-01-01 DOI:10.55730/1300-0144.6220
Sevil Uygun Ilikhan, Sinem Ülke, Mahmut Özer, Matjaž Perc, Yavuz Ayhan
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引用次数: 0

Abstract

Background/aim: Artificial intelligence (AI) is increasingly being integrated into healthcare systems; however, healthcare professionals' knowledge, attitudes, and perceptions regarding AI remain insufficiently understood. This study aimed to evaluate healthcare professionals' perceptions of AI in clinical practice.

Materials and methods: This descriptive cross-sectional study included 260 healthcare professionals, including physicians, nurses, and healthcare technicians working at a tertiary public hospital in Türkiye. Participants completed the Healthcare Professionals and Artificial Intelligence Questionnaire, which assessed demographic characteristics, AI knowledge, workplace AI use, attitudes toward AI applications, ethical and legal concerns, perceived professional impact, and educational needs.

Results: Most participants reported limited AI knowledge; 64.6% indicated basic knowledge, whereas 23.1% reported no knowledge. Only 24.6% reported using AI-based systems in clinical practice, while 35.4% were uncertain whether such systems were used in their workplaces. Despite limited experience, attitudes toward recent AI developments were generally positive. Most participants expressed willingness to receive AI-related education (76.9%), although only 6.2% had previously received formal training. Nearly half of the participants believed that the human factor would remain essential in healthcare, whereas a similar proportion considered partial replacement by AI possible. Physicians demonstrated greater confidence in AI usefulness and stronger willingness to integrate AI into clinical decision-making than nurses and other healthcare professionals. Nurses primarily emphasized data security and privacy concerns, whereas physicians highlighted patient safety and misdiagnosis risk. Exploratory psychometric analyses demonstrated a three-factor structure with acceptable sampling adequacy (KMO = 0.765).

Conclusion: Healthcare professionals generally perceive AI as a supportive tool rather than a replacement for human judgment. Limited AI literacy, uncertainty regarding legal responsibility, and insufficient training remain important barriers to responsible AI adoption. Profession-sensitive educational strategies and clearer governance frameworks may support safer AI integration into healthcare practice.

对临床人工智能的乐观和矛盾态度。
背景/目的:人工智能(AI)越来越多地集成到医疗系统中;然而,医疗保健专业人员对人工智能的知识、态度和看法仍然不够了解。本研究旨在评估医疗保健专业人员在临床实践中对人工智能的看法。材料和方法:本描述性横断面研究包括260名医疗保健专业人员,包括医生、护士和在基耶省一家三级公立医院工作的医疗保健技术人员。参与者完成了《医疗保健专业人员和人工智能问卷》,该问卷评估了人口统计学特征、人工智能知识、人工智能工作场所使用情况、对人工智能应用的态度、道德和法律问题、感知到的专业影响以及教育需求。结果:大多数参与者表示AI知识有限;有基本知识的占64.6%,不知道的占23.1%。只有24.6%的人报告在临床实践中使用了基于人工智能的系统,而35.4%的人不确定是否在工作场所使用了这种系统。尽管经验有限,但人们对近期人工智能发展的态度总体上是积极的。大多数参与者表示愿意接受与人工智能相关的教育(76.9%),尽管只有6.2%的人之前接受过正式的培训。近一半的参与者认为,在医疗保健领域,人为因素仍将至关重要,而类似比例的参与者认为,人工智能可能会部分取代人工智能。与护士和其他医疗保健专业人员相比,医生对人工智能的有用性表现出更大的信心,并更愿意将人工智能整合到临床决策中。护士主要强调数据安全和隐私问题,而医生则强调患者安全和误诊风险。探索性心理测量分析表明,三因素结构具有可接受的抽样充分性(KMO = 0.765)。结论:医疗保健专业人员普遍认为人工智能是一种辅助工具,而不是人类判断的替代品。有限的人工智能知识、法律责任的不确定性以及培训不足仍然是负责任的人工智能采用的重要障碍。对职业敏感的教育战略和更清晰的治理框架可以支持将人工智能更安全地整合到医疗保健实践中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Turkish Journal of Medical Sciences
Turkish Journal of Medical Sciences 医学-医学:内科
CiteScore
4.60
自引率
4.30%
发文量
143
审稿时长
3-8 weeks
期刊介绍: Turkish Journal of Medical sciences is a peer-reviewed comprehensive resource that provides critical up-to-date information on the broad spectrum of general medical sciences. The Journal intended to publish original medical scientific papers regarding the priority based on the prominence, significance, and timeliness of the findings. However since the audience of the Journal is not limited to any subspeciality in a wide variety of medical disciplines, the papers focusing on the technical  details of a given medical  subspeciality may not be evaluated for publication.
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