• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

中国不同类别专业人员对护理领域人工智能的认知与态度：一项横断面研究

Knowledge and attitudes toward artificial intelligence in nursing among various categories of professionals in China: a cross-sectional study.

作者信息

Wang Xiaoyan, Fei Fangqin, Wei Jiawen, Huang Mingxue, Xiang Fengling, Tu Jing, Wang Yaping, Gan Jinhua

机构信息

School of Nursing, Southwest Medical University, Luzhou, Sichuan Province, China.

Department of Ophthalmology, The Affiliated Hospital, Southwest Medical University, Luzhou, Sichuan, China.

出版信息

Front Public Health. 2024 Jul 2;12:1433252. doi: 10.3389/fpubh.2024.1433252. eCollection 2024.

DOI:10.3389/fpubh.2024.1433252
PMID:39015390
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11250283/
Abstract

OBJECTIVES

The application of artificial intelligence (AI) in healthcare is an important public health issue. However, few studies have investigated the perceptions and attitudes of healthcare professionals toward its applications in nursing. This study aimed to explore the knowledge, attitudes, and concerns of healthcare professionals, AI-related professionals, and others in China toward AI in nursing.

METHODS

We conducted an online cross-sectional study on nursing students, nurses, other healthcare professionals, AI-related professionals, and others in China between March and April 2024. They were invited to complete a questionnaire containing 21 questions with four sections. The survey followed the principle of voluntary participation and was conducted anonymously. The participants could withdraw from the survey at any time during the study.

RESULTS

This study obtained 1,243 valid questionnaires. The participants came from 25 provinces and municipalities in seven regions of China. Regarding knowledge of AI in nursing, 57% of the participants knew only a little about AI, 4.7% did not know anything about AI, 64.7% knew only a little about AI in nursing, and 13.4% did not know anything about AI in nursing. For attitudes toward AI in nursing, participants were positive about AI in nursing, with more than 50% agreeing and strongly agreeing with each question on attitudes toward AI in nursing. Differences in the numbers of participants with various categories of professionals regarding knowledge and attitudes toward AI in nursing were statistically significant ( < 0.05). Regarding concerns and ethical issues about AI in nursing, every participant expressed concerns about AI in nursing, and 95.7% of participants believed that it is necessary to strengthen medical ethics toward AI in nursing.

CONCLUSION

Nursing students and healthcare professionals lacked knowledge about AI or its application in nursing, but they had a positive attitude toward AI. It is necessary to strengthen medical ethics toward AI in nursing. The study's findings could help develop new strategies benefiting healthcare.

摘要

目的

人工智能（AI）在医疗保健中的应用是一个重要的公共卫生问题。然而，很少有研究调查医疗保健专业人员对其在护理领域应用的看法和态度。本研究旨在探讨中国医疗保健专业人员、人工智能相关专业人员及其他人员对护理领域人工智能的知识、态度和担忧。

方法

2024年3月至4月，我们对中国的护理专业学生、护士、其他医疗保健专业人员、人工智能相关专业人员及其他人员进行了一项在线横断面研究。邀请他们完成一份包含21个问题、分为四个部分的问卷。调查遵循自愿参与原则，采用匿名方式进行。参与者在研究过程中可随时退出调查。

结果

本研究共获得1243份有效问卷。参与者来自中国七个地区的25个省和直辖市。在护理领域人工智能知识方面，57%的参与者对人工智能了解甚少，4.7%的参与者对人工智能一无所知，64.7%的参与者对护理领域人工智能了解甚少，13.4%的参与者对护理领域人工智能一无所知。对于护理领域人工智能的态度，参与者对护理领域人工智能持积极态度，超过50%的参与者对护理领域人工智能态度相关的每个问题表示同意或强烈同意。不同类别专业人员在护理领域人工智能知识和态度方面的参与者数量差异具有统计学意义（<0.05）。在护理领域人工智能的担忧和伦理问题方面，每位参与者都表达了对护理领域人工智能的担忧，95.7%的参与者认为有必要加强护理领域人工智能的医学伦理。

结论

护理专业学生和医疗保健专业人员缺乏关于人工智能或其在护理领域应用的知识，但他们对人工智能持积极态度。有必要加强护理领域人工智能的医学伦理。该研究结果有助于制定有益于医疗保健的新策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/f6d0afbd1168/fpubh-12-1433252-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/46b2fb5b4b4f/fpubh-12-1433252-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/68acf5855dea/fpubh-12-1433252-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/98942bc067eb/fpubh-12-1433252-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/4651dafa3e6e/fpubh-12-1433252-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/c4d85d38efa6/fpubh-12-1433252-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/222c80b09148/fpubh-12-1433252-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/5422a148b4e6/fpubh-12-1433252-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/1bd8eef04d0a/fpubh-12-1433252-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/f6d0afbd1168/fpubh-12-1433252-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/46b2fb5b4b4f/fpubh-12-1433252-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/68acf5855dea/fpubh-12-1433252-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/98942bc067eb/fpubh-12-1433252-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/4651dafa3e6e/fpubh-12-1433252-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/c4d85d38efa6/fpubh-12-1433252-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/222c80b09148/fpubh-12-1433252-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/5422a148b4e6/fpubh-12-1433252-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/1bd8eef04d0a/fpubh-12-1433252-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/184c/11250283/f6d0afbd1168/fpubh-12-1433252-g009.jpg

相似文献

1
Knowledge and attitudes toward artificial intelligence in nursing among various categories of professionals in China: a cross-sectional study.中国不同类别专业人员对护理领域人工智能的认知与态度：一项横断面研究
Front Public Health. 2024 Jul 2;12:1433252. doi: 10.3389/fpubh.2024.1433252. eCollection 2024.
2
Knowledge, attitude, and perception of Arab medical students towards artificial intelligence in medicine and radiology: A multi-national cross-sectional study.阿拉伯医学专业学生对医学和放射学人工智能的知识、态度和看法：一项多国横断面研究。
Eur Radiol. 2024 Jul;34(7):1-14. doi: 10.1007/s00330-023-10509-2. Epub 2023 Dec 27.
3
Shaping the future: perspectives on the Integration of Artificial Intelligence in health profession education: a multi-country survey.塑造未来：对人工智能在健康职业教育中融合的观点：一项多国家调查。
BMC Med Educ. 2024 Oct 18;24(1):1166. doi: 10.1186/s12909-024-06076-9.
4
Attitudes of medical workers in China toward artificial intelligence in ophthalmology: a comparative survey.中国眼科医务人员对人工智能的态度：一项对比调查。
BMC Health Serv Res. 2021 Oct 9;21(1):1067. doi: 10.1186/s12913-021-07044-5.
5
Digital proficiency: assessing knowledge, attitudes, and skills in digital transformation, health literacy, and artificial intelligence among university nursing students.数字化素养：评估大学生护理学生在数字化转型、健康素养和人工智能方面的知识、态度和技能。
BMC Med Educ. 2024 May 7;24(1):508. doi: 10.1186/s12909-024-05482-3.
6
Knowledge, attitude and practice among pharmacy students and faculty members towards artificial intelligence in pharmacy practice: A multinational cross-sectional study.药学专业学生和教师对药学实践中人工智能的知识、态度和实践：一项多国家的横断面研究。
PLoS One. 2024 Mar 1;19(3):e0296884. doi: 10.1371/journal.pone.0296884. eCollection 2024.
7
Shaping future practices: German-speaking medical and dental students' perceptions of artificial intelligence in healthcare.塑造未来实践：德语国家医学生和牙科学学生对医疗保健中人工智能的看法。
BMC Med Educ. 2024 Aug 6;24(1):844. doi: 10.1186/s12909-024-05826-z.
8
Student nurses' attitudes, perceived utilization, and intention to adopt artificial intelligence (AI) technology in nursing practice: A cross-sectional study.护生对人工智能（AI）技术在护理实践中的态度、感知利用度和采用意愿：一项横断面研究。
Nurse Educ Pract. 2023 Nov;73:103815. doi: 10.1016/j.nepr.2023.103815. Epub 2023 Oct 19.
9
Korean dental hygiene students' perceptions and attitudes toward artificial intelligence: An online survey.韩国口腔卫生专业学生对人工智能的认知和态度：一项在线调查。
J Dent Educ. 2023 Jun;87(6):804-812. doi: 10.1002/jdd.13189. Epub 2023 Feb 17.
10
Artificial Intelligence Readiness, Perceptions, and Educational Needs Among Dental Students: A Cross-Sectional Study.人工智能准备情况、认知与牙科学子的教育需求：一项横断面研究。
Clin Exp Dent Res. 2024 Aug;10(4):e925. doi: 10.1002/cre2.925.

引用本文的文献

1
Structural equation modeling for influencing factors on behavioral intention to adopt medical AI among Chinese nurses: a nationwide cross-sectional study.中国护士采用医学人工智能行为意向影响因素的结构方程模型：一项全国性横断面研究
BMC Nurs. 2025 Aug 18;24(1):1084. doi: 10.1186/s12912-025-03748-9.
2
Mechanisms of nurses' AI use intention formation in Sichuan, Yunnan, and Beijing, China: mediating effects of AI literacy via self-efficacy-to-attitude pathways.中国四川、云南和北京护士人工智能使用意图形成机制：通过自我效能感-态度路径的人工智能素养中介作用
Front Public Health. 2025 Jul 10;13:1622802. doi: 10.3389/fpubh.2025.1622802. eCollection 2025.
3

本文引用的文献

1
Advances in the Application of AI Robots in Critical Care: Scoping Review.人工智能机器人在重症监护中的应用进展：范围综述。
J Med Internet Res. 2024 May 27;26:e54095. doi: 10.2196/54095.
2
Enhancing nursing competency through virtual reality simulation among nursing students: a systematic review and meta-analysis.通过虚拟现实模拟提高护生护理能力：一项系统评价和荟萃分析
Front Med (Lausanne). 2024 May 7;11:1351300. doi: 10.3389/fmed.2024.1351300. eCollection 2024.
3
Preoperative prediction model for risk of readmission after total joint replacement surgery: a random forest approach leveraging NLP and unfairness mitigation for improved patient care and cost-effectiveness.
Embracing artificial intelligence in nursing: exploring the relationship between artificial intelligence-related attitudes, creative self-efficacy, and clinical reasoning competency among nurses.
护理领域接纳人工智能：探讨护士对人工智能的态度、创造性自我效能感与临床推理能力之间的关系。
BMC Nurs. 2025 Jun 20;24(1):661. doi: 10.1186/s12912-025-03306-3.
4
Healthcare providers' perceptions of artificial intelligence in diabetes care: A cross-sectional study in China.医疗服务提供者对糖尿病护理中人工智能的认知：一项中国的横断面研究。
Int J Nurs Sci. 2025 Apr 28;12(3):218-224. doi: 10.1016/j.ijnss.2025.04.013. eCollection 2025 May.
5
Nurses' Perception of Artificial Intelligence-Driven Monitoring Systems for Enhancing Compliance With Infection Prevention and Control Measures in Al-Ahsa, Saudi Arabia.护士对人工智能驱动的监测系统在沙特阿拉伯艾哈萨提高感染预防与控制措施依从性方面的认知
Cureus. 2025 Apr 24;17(4):e82943. doi: 10.7759/cureus.82943. eCollection 2025 Apr.
6
Knowledge, attitudes, practices, and barriers of artificial intelligence as predictors of intent to stay among nurses: A cross-sectional study.作为护士留任意向预测因素的人工智能相关知识、态度、实践及障碍：一项横断面研究。
Digit Health. 2025 Apr 22;11:20552076251336106. doi: 10.1177/20552076251336106. eCollection 2025 Jan-Dec.
7
Demand analysis of transitional care for patients undergoing minimally invasive cardiac interventions with AI-driven solutions: a mixed-methods approach.人工智能驱动的解决方案在微创心脏介入治疗患者过渡护理中的需求分析：一种混合方法研究。
BMC Nurs. 2025 Apr 23;24(1):453. doi: 10.1186/s12912-025-03037-5.
8
Demographic factors, knowledge, attitude and perception and their association with nursing students' intention to use artificial intelligence (AI): a multicentre survey across 10 Arab countries.人口统计学因素、知识、态度和认知及其与护理专业学生使用人工智能意愿的关联：一项涵盖10个阿拉伯国家的多中心调查。
BMC Med Educ. 2024 Dec 18;24(1):1456. doi: 10.1186/s12909-024-06452-5.
9
Healthcare workers' knowledge and attitudes regarding artificial intelligence adoption in healthcare: A cross-sectional study.医护人员对医疗保健领域采用人工智能的知识和态度：一项横断面研究。
Heliyon. 2024 Nov 29;10(23):e40775. doi: 10.1016/j.heliyon.2024.e40775. eCollection 2024 Dec 15.
全关节置换术后再入院风险的术前预测模型：一种利用 NLP 和不公平性缓解的随机森林方法，以改善患者护理和成本效益。
J Orthop Surg Res. 2024 May 10;19(1):287. doi: 10.1186/s13018-024-04774-0.
4
Embracing the future: Integrating ChatGPT into China's nursing education system.拥抱未来：将ChatGPT融入中国护理教育体系。
Int J Nurs Sci. 2024 Mar 7;11(2):295-299. doi: 10.1016/j.ijnss.2024.03.006. eCollection 2024 Apr.
5
Medical, dental, and nursing students' attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis.医学、牙科和护理专业学生对人工智能的态度和知识：系统评价和荟萃分析。
BMC Med Educ. 2024 Apr 15;24(1):412. doi: 10.1186/s12909-024-05406-1.
6
Predicting pressure injury risk in hospitalised patients using machine learning with electronic health records: a US multilevel cohort study.利用电子健康记录的机器学习预测住院患者的压疮风险：一项美国多层次队列研究。
BMJ Open. 2024 Apr 9;14(4):e082540. doi: 10.1136/bmjopen-2023-082540.
7
Preact to lower the risk of falling by customized rehabilitation across Europe: the feasibility study protocol of the PRECISE project in Italy.在欧洲范围内，通过定制康复来降低跌倒风险：意大利 PRECISE 项目的可行性研究方案。
Front Public Health. 2024 Mar 22;12:1293621. doi: 10.3389/fpubh.2024.1293621. eCollection 2024.
8
Mobile robots for isolation-room hospital settings: A scenario-based preliminary study.用于隔离病房医院环境的移动机器人：一项基于场景的初步研究。
Comput Struct Biotechnol J. 2024 Mar 15;24:237-246. doi: 10.1016/j.csbj.2024.03.001. eCollection 2024 Dec.
9
A rapid review on current and potential uses of large language models in nursing.关于大型语言模型在护理中的当前和潜在用途的快速综述。
Int J Nurs Stud. 2024 Jun;154:104753. doi: 10.1016/j.ijnurstu.2024.104753. Epub 2024 Mar 13.
10
Nurses' perceptions, experience and knowledge regarding artificial intelligence: results from a cross-sectional online survey in Germany.护士对人工智能的认知、经验和知识：德国一项横断面在线调查的结果。
BMC Nurs. 2024 Mar 27;23(1):205. doi: 10.1186/s12912-024-01884-2.