{"title":"医疗可解释人工智能对护士创新行为的影响：结构方程建模方法","authors":"Xianmiao Li, Qilin Zong, Mengting Cheng","doi":"10.1155/2024/8885760","DOIUrl":null,"url":null,"abstract":"<div>\n <p><b>Aim:</b> This study aims to investigate the influence of medical explainable artificial intelligence (XAI) on the innovation behaviour of nurses, as well as explore the dual-pathway mediating effect of AI self-efficacy and AI anxiety and organizational ethical climate as the moderating effect.</p>\n <p><b>Background:</b> To address the practical application of medical AI technology, alleviate the scarcity of medical resources and fulfil the medical and health demands of the public, it is crucial to improve the innovation behaviour of nurses through the use of medical XAI.</p>\n <p><b>Methods:</b> A cross-sectional survey was conducted involving 368 Chinese nurses working at tertiary and secondary hospitals in Anhui Province, Jiangsu Province, Zhejiang Province and Shanghai.</p>\n <p><b>Results:</b> Implementing medical XAI significantly enhanced the innovation behaviour of nurses. Anxiety and self-efficacy regarding AI mediated the connection between medical XAI and the innovation behaviour of nurses. Furthermore, the organizational ethical climate positively moderated the relationship between medical XAI and AI self-efficacy.</p>\n <p><b>Conclusion:</b> Medical XAI helps to enhance nurses’ AI self-efficacy and reduce AI anxiety, thereby enhancing nurses’ innovation behaviour. An organizational ethical climate enhances the positive relationship between medical XAI and AI self-efficacy.</p>\n <p><b>Implications for Nursing Management:</b> Organizations and technology developers must augment the study about XAI and the system design of human-centred AI technology. The organizations aim to enhance the education and training of nurses in AI, specifically focussing on boosting nurses’ self-efficacy in utilizing AI technology. Moreover, they want to alleviate nurses’ fear of new technological advancements. Hospital administrators and leaders develop strategies to address the ethical atmosphere inside their organization.</p>\n </div>","PeriodicalId":49297,"journal":{"name":"Journal of Nursing Management","volume":"2024 1","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/8885760","citationCount":"0","resultStr":"{\"title\":\"The Impact of Medical Explainable Artificial Intelligence on Nurses’ Innovation Behaviour: A Structural Equation Modelling Approach\",\"authors\":\"Xianmiao Li, Qilin Zong, Mengting Cheng\",\"doi\":\"10.1155/2024/8885760\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n <p><b>Aim:</b> This study aims to investigate the influence of medical explainable artificial intelligence (XAI) on the innovation behaviour of nurses, as well as explore the dual-pathway mediating effect of AI self-efficacy and AI anxiety and organizational ethical climate as the moderating effect.</p>\\n <p><b>Background:</b> To address the practical application of medical AI technology, alleviate the scarcity of medical resources and fulfil the medical and health demands of the public, it is crucial to improve the innovation behaviour of nurses through the use of medical XAI.</p>\\n <p><b>Methods:</b> A cross-sectional survey was conducted involving 368 Chinese nurses working at tertiary and secondary hospitals in Anhui Province, Jiangsu Province, Zhejiang Province and Shanghai.</p>\\n <p><b>Results:</b> Implementing medical XAI significantly enhanced the innovation behaviour of nurses. Anxiety and self-efficacy regarding AI mediated the connection between medical XAI and the innovation behaviour of nurses. Furthermore, the organizational ethical climate positively moderated the relationship between medical XAI and AI self-efficacy.</p>\\n <p><b>Conclusion:</b> Medical XAI helps to enhance nurses’ AI self-efficacy and reduce AI anxiety, thereby enhancing nurses’ innovation behaviour. An organizational ethical climate enhances the positive relationship between medical XAI and AI self-efficacy.</p>\\n <p><b>Implications for Nursing Management:</b> Organizations and technology developers must augment the study about XAI and the system design of human-centred AI technology. The organizations aim to enhance the education and training of nurses in AI, specifically focussing on boosting nurses’ self-efficacy in utilizing AI technology. Moreover, they want to alleviate nurses’ fear of new technological advancements. Hospital administrators and leaders develop strategies to address the ethical atmosphere inside their organization.</p>\\n </div>\",\"PeriodicalId\":49297,\"journal\":{\"name\":\"Journal of Nursing Management\",\"volume\":\"2024 1\",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1155/2024/8885760\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Nursing Management\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1155/2024/8885760\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Nursing Management","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/2024/8885760","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MANAGEMENT","Score":null,"Total":0}
The Impact of Medical Explainable Artificial Intelligence on Nurses’ Innovation Behaviour: A Structural Equation Modelling Approach
Aim: This study aims to investigate the influence of medical explainable artificial intelligence (XAI) on the innovation behaviour of nurses, as well as explore the dual-pathway mediating effect of AI self-efficacy and AI anxiety and organizational ethical climate as the moderating effect.
Background: To address the practical application of medical AI technology, alleviate the scarcity of medical resources and fulfil the medical and health demands of the public, it is crucial to improve the innovation behaviour of nurses through the use of medical XAI.
Methods: A cross-sectional survey was conducted involving 368 Chinese nurses working at tertiary and secondary hospitals in Anhui Province, Jiangsu Province, Zhejiang Province and Shanghai.
Results: Implementing medical XAI significantly enhanced the innovation behaviour of nurses. Anxiety and self-efficacy regarding AI mediated the connection between medical XAI and the innovation behaviour of nurses. Furthermore, the organizational ethical climate positively moderated the relationship between medical XAI and AI self-efficacy.
Conclusion: Medical XAI helps to enhance nurses’ AI self-efficacy and reduce AI anxiety, thereby enhancing nurses’ innovation behaviour. An organizational ethical climate enhances the positive relationship between medical XAI and AI self-efficacy.
Implications for Nursing Management: Organizations and technology developers must augment the study about XAI and the system design of human-centred AI technology. The organizations aim to enhance the education and training of nurses in AI, specifically focussing on boosting nurses’ self-efficacy in utilizing AI technology. Moreover, they want to alleviate nurses’ fear of new technological advancements. Hospital administrators and leaders develop strategies to address the ethical atmosphere inside their organization.
期刊介绍：
The Journal of Nursing Management is an international forum which informs and advances the discipline of nursing management and leadership. The Journal encourages scholarly debate and critical analysis resulting in a rich source of evidence which underpins and illuminates the practice of management, innovation and leadership in nursing and health care. It publishes current issues and developments in practice in the form of research papers, in-depth commentaries and analyses.
The complex and rapidly changing nature of global health care is constantly generating new challenges and questions. The Journal of Nursing Management welcomes papers from researchers, academics, practitioners, managers, and policy makers from a range of countries and backgrounds which examine these issues and contribute to the body of knowledge in international nursing management and leadership worldwide.
The Journal of Nursing Management aims to:
-Inform practitioners and researchers in nursing management and leadership
-Explore and debate current issues in nursing management and leadership
-Assess the evidence for current practice
-Develop best practice in nursing management and leadership
-Examine the impact of policy developments
-Address issues in governance, quality and safety
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
