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人工智能在护理教育中的整合:一项跨国探索。

Integration of artificial intelligence in nursing education: a cross-national exploration.

作者信息

Almalki Mohammed, Sacgaca Lailani, Pangket Petelyne, Pasay-An Eddieson, Deep Shereen Hussein, Maskay Georgina, Benjamin Lizy Sonia, Hashim Sahar Mahmoud Abdulla, Gonzales Analita, Rosal Rosalyn, Mohsen Maysa, Mostoles Romeo, Lagura Grace Ann Lim

机构信息

College of Nursing, Taif University, P.O. Box 11099, Taif, 21944, Kingdom of Saudi Arabia.

College of Nursing, King Khalid University, Abha, Saudi Arabia.

出版信息

BMC Nurs. 2025 Aug 5;24(1):1026. doi: 10.1186/s12912-025-03689-3.

DOI:10.1186/s12912-025-03689-3
PMID:40764580
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12326664/
Abstract

BACKGROUND

Understanding nurse educators' perceptions of Artificial Intelligence (AI) in education, particularly cross-nationally and considering cultural and exposure influences, remains limited. This study addressed this gap by determining the impact of AI integration in nursing education.

METHODS

Participants included 1021 nurse educators from the Philippines, Saudi Arabia, India, and Egypt, with data collected between January and March 2025.

RESULTS

Perceived benefits of AI showed consistent means across countries, though significant differences (p < 0.001) were observed in perceived threats, exposure, and the influence of culture by country. Strong positive correlations emerged between exposure to AI and both trust in AI (r = 0.653) and perceived benefits (r = 0.625). Nationality significantly predicted perceived risks, exposure, and cultural impact (all p < 0.001), emphasizing the relevance of cultural background to AI applicability.

CONCLUSION

Nurse educators acknowledge AI's educational potential but show diverse perceptions regarding risks, exposure, and cultural impact. Increased AI exposure fosters trust and perceived benefits, highlighting the need for contextualized, culturally-attuned, and exposure-driven AI integration in nursing education.

摘要

背景

了解护士教育工作者对教育中人工智能(AI)的看法,尤其是跨国界以及考虑文化和接触程度影响的看法,仍然有限。本研究通过确定人工智能融入护理教育的影响来填补这一空白。

方法

参与者包括来自菲律宾、沙特阿拉伯、印度和埃及的1021名护士教育工作者,数据于2025年1月至3月收集。

结果

尽管在感知到的威胁、接触程度以及各国文化的影响方面观察到显著差异(p < 0.001),但人工智能的感知益处显示各国均值一致。接触人工智能与对人工智能的信任(r = 0.653)和感知益处(r = 0.625)之间均呈现出强正相关。国籍显著预测了感知到的风险、接触程度和文化影响(均p < 0.001),强调了文化背景与人工智能适用性的相关性。

结论

护士教育工作者认可人工智能的教育潜力,但对风险、接触程度和文化影响表现出不同的看法。增加对人工智能的接触会增强信任和感知到的益处,凸显了在护理教育中进行情境化、文化适配和基于接触程度驱动的人工智能融入的必要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2e7/12326664/b69de726b9d8/12912_2025_3689_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2e7/12326664/b69de726b9d8/12912_2025_3689_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2e7/12326664/b69de726b9d8/12912_2025_3689_Fig1_HTML.jpg

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Exploring faculty perceptions and concerns regarding artificial intelligence Chatbots in nursing education: potential benefits and limitations.探索教师对护理教育中人工智能聊天机器人的看法和担忧:潜在的益处和局限性。
BMC Nurs. 2025 Apr 18;24(1):440. doi: 10.1186/s12912-025-03082-0.
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A systematic review and sequential explanatory synthesis: Artificial intelligence in healthcare education, a case of nursing.
一项系统评价与序列解释性综合分析:医疗保健教育中的人工智能,以护理为例。
Int Nurs Rev. 2025 Jun;72(2):e70018. doi: 10.1111/inr.70018.
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Trust and Acceptance Challenges in the Adoption of AI Applications in Health Care: Quantitative Survey Analysis.医疗保健领域采用人工智能应用中的信任与接受挑战:定量调查分析
J Med Internet Res. 2025 Mar 21;27:e65567. doi: 10.2196/65567.
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