Artificial Intelligence -based technologies in nursing: A scoping literature review of the evidence

奇纳 医疗保健 背景(考古学) 护理研究 人工智能 计算机科学 现存分类群 梅德林 系统回顾 心理学 知识管理 护理部 数据科学 医学 政治学 古生物学 进化生物学 心理干预 法学 生物
作者
Hanna von Gerich,Hans Moen,Lorraine J. Block,Charlene H. Chu,Haley Deforest,Mollie Hobensack,Martin Michalowski,James Mitchell,Raji Nibber,Mary Anne Olalia,Lisiane Pruinelli,Charlene Ronquillo,Maxim Topaz,Laura‐Maria Peltonen
出处
期刊:International Journal of Nursing Studies [Elsevier]
卷期号:127: 104153-104153 被引量:117
标识
DOI:10.1016/j.ijnurstu.2021.104153
摘要

Research on technologies based on artificial intelligence in healthcare has increased during the last decade, with applications showing great potential in assisting and improving care. However, introducing these technologies into nursing can raise concerns related to data bias in the context of training algorithms and potential implications for certain populations. Little evidence exists in the extant literature regarding the efficacious application of many artificial intelligence -based health technologies used in healthcare. To synthesize currently available state-of the-art research in artificial intelligence -based technologies applied in nursing practice. Scoping review PubMed, CINAHL, Web of Science and IEEE Xplore were searched for relevant articles with queries that combine names and terms related to nursing, artificial intelligence and machine learning methods. Included studies focused on developing or validating artificial intelligence -based technologies with a clear description of their impacts on nursing. We excluded non-experimental studies and research targeted at robotics, nursing management and technologies used in nursing research and education. A total of 7610 articles published between January 2010 and March 2021 were revealed, with 93 articles included in this review. Most studies explored the technology development (n = 55, 59.1%) and formation (testing) (n = 28, 30.1%) phases, followed by implementation (n = 9, 9.7%) and operational (n = 1, 1.1%) phases. The vast majority (73.1%) of studies provided evidence with a descriptive design (level VI) while only a small portion (4.3%) were randomised controlled trials (level II). The study aims, settings and methods were poorly described in the articles, and discussion of ethical considerations were lacking in 36.6% of studies. Additionally, one-third of papers (33.3%) were reported without the involvement of nurses. Contemporary research on applications of artificial intelligence -based technologies in nursing mainly cover the earlier stages of technology development, leaving scarce evidence of the impact of these technologies and implementation aspects into practice. The content of research reported is varied. Therefore, guidelines on research reporting and implementing artificial intelligence -based technologies in nursing are needed. Furthermore, integrating basic knowledge of artificial intelligence -related technologies and their applications in nursing education is imperative, and interventions to increase the inclusion of nurses throughout the technology research and development process is needed.
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