Journal of Nursing Regulation最新文献

英文中文

Regulatory Reflection: Collaborative expertise, shared purpose: How the Editorial Advisory Board informs JNR's work 监管反思：合作的专业知识，共同的目标：编辑顾问委员会如何通知JNR的工作

IF 6.3 4区医学 Q1 NURSING

Journal of Nursing Regulation

Pub Date : 2026-01-01 DOI: 10.1016/j.jnr.2025.11.006

Ellen Lanser May (Senior Managing Editor)

引用次数: 0

Text 文本

IF 6.3 4区医学 Q1 NURSING

Journal of Nursing Regulation

Pub Date : 2026-01-01 DOI: 10.1016/S2155-8256(26)00004-9

引用次数: 0

Bringing the NCLEX into the next generation: Results from the first year of measuring clinical judgment 将NCLEX带入下一代：第一年测量临床判断的结果

IF 6.3 4区医学 Q1 NURSING

Journal of Nursing Regulation

Pub Date : 2026-01-01 DOI: 10.1016/j.jnr.2025.11.005

Joe Betts PhD, EdS, MMIS, Nicole Williams DNP, RN, NPD-BC, NEA-BC, Cary Lin PhD, Shu-chuan Kao PhD, Hyung Jin Kim PhD, William Muntean PhD, MS

Background

In April 2023, the NCLEX-RN added a framework to measure clinical judgment (CJ).

Purpose

To evaluate results from the first year of the implementation of CJ (post-CJ) compared with the previous year's NCLEX (pre-CJ), which did not include the measurement of CJ.

Methods

Performance of candidates on test blueprint domains was compared between those who took the licensing examination post-CJ and those who took the NCLEX pre-CJ. Examination-level readability of both examinations was also evaluated. In addition, entry-level nurses were surveyed regarding the extent to which they believed the CJ items in the post-CJ examination reflected their entry-level practice in the field of nursing.

Results

The licensing examination had a similar level of readability pre-CJ and post-CJ. First-time candidates performed similarly on the test blueprint domains in both examined time frames; however, post-CJ candidates performed consistently better on the CJ items than on the blueprint domain items. Finally, entry-level nurses practicing for less than a year who took the post-CJ examination indicated a high level of utility and fidelity with respect to the CJ case studies.

Conclusion

Results highlight the fidelity and utility of the addition of the CJ measurement to the licensing examination. Even with the extended CJ scenarios, the post-CJ examination readability was comparable to that of the NCLEX pre-CJ.

2023年4月，NCLEX-RN增加了一个衡量临床判断（CJ）的框架。目的比较实施第一年（后CJ）与前一年（前CJ）的NCLEX结果，后者不包括CJ的测量。方法比较执业医师考试后与执业医师考试前在考试蓝图域上的表现。对两项考试的可读性也进行了评估。此外，对初级护士进行了调查，了解他们认为后CJ考试中的CJ项目反映了他们在护理领域的初级实践的程度。结果执业医师执业前和执业医师执业后执业医师执业资格考试的可读性基本一致。第一次参加测试的考生在两个测试时间框架内的测试蓝图域表现相似；然而，后CJ候选人在CJ项目上的表现始终比在蓝图领域项目上的表现要好。最后，实习不到一年的初级护士参加了后CJ考试，表明了对CJ案例研究的高度实用性和保真性。结论在执业资格考试中增加CJ测量具有较高的准确性和实用性。即使在扩展的CJ场景下，CJ后考试的可读性与NCLEX pre-CJ相当。

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引用次数: 0

Developing a pan-Canadian nursing regulation research agenda 制定泛加拿大护理法规研究议程

IF 6.3 4区医学 Q1 NURSING

Journal of Nursing Regulation

Pub Date : 2026-01-01 DOI: 10.1016/j.jnr.2025.09.001

Patrick Chiu RN, PhD , Kathleen Leslie PhD, JD, RN , Sophia Myles PhD , Houssem Eddine Ben-Ahmed RN, PhD , Gina Jang RN, BScN, BA

Effective nursing regulation is vital for maintaining a competent, agile, and safe nursing workforce. Yet, the evidence available to inform nursing regulation within the Canadian context is largely descriptive and fragmented, with limited utility to support decision-making. While nursing regulators, which exist at the provincial and territorial levels, continue to engage in pan-Canadian policy initiatives, no coordinated research agenda exists to drive nursing regulatory science forward. To address this gap, we conducted a virtual deliberative dialogue with diverse system partners across Canada to co-create a pan-Canadian nursing regulation research agenda. Examples of research areas of interest identified by the participants include strategies for regulatory harmonization, evaluation of regulatory reforms, licensure policy development, improved regulatory data management, and regulatory approaches for new and emerging practices. Barriers to collaboration centered on jurisdictional differences in legislative frameworks and priorities, lack of resources and time, poor role clarity, and legislative barriers to data collection. Examples of facilitators include leveraging existing collaborative networks, addressing barriers to data sharing, and enhancing partnerships between regulators and researchers. Guided by the learning health system framework, we explore strategic opportunities to create a “learning regulatory system” by highlighting scientific, social, technological, policy, legal, and ethical considerations. Insights from our dialogue reinforce the need for intentional investment in collaborative infrastructure to support continuous improvement and innovation in nursing regulation.

有效的护理管理对于维持一支称职、敏捷和安全的护理队伍至关重要。然而，在加拿大的背景下，为护理监管提供信息的证据在很大程度上是描述性的和碎片化的，对支持决策的效用有限。虽然存在于省和地区层面的护理监管机构继续参与泛加拿大政策倡议，但没有协调的研究议程来推动护理监管科学向前发展。为了解决这一差距，我们与加拿大各地的不同系统合作伙伴进行了虚拟审议对话，共同制定了泛加拿大护理法规研究议程。与会者确定的感兴趣的研究领域包括监管协调战略、监管改革评估、许可证政策制定、改进的监管数据管理以及针对新兴实践的监管方法。合作的障碍集中在立法框架和优先事项的管辖差异、缺乏资源和时间、角色不明确以及数据收集方面的立法障碍。促进者的例子包括利用现有的协作网络，解决数据共享的障碍，以及加强监管机构和研究人员之间的伙伴关系。在学习型卫生系统框架的指导下，我们通过强调科学、社会、技术、政策、法律和道德方面的考虑，探索创建“学习型监管系统”的战略机遇。我们从对话中获得的见解强调了有意投资协作基础设施的必要性，以支持护理监管的持续改进和创新。

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引用次数: 0

Impact of reduced restrictions in scope of practice of nurse anesthetists on patient safety across states 各州护士麻醉师执业范围限制的减少对患者安全的影响

IF 6.3 4区医学 Q1 NURSING

Journal of Nursing Regulation

Pub Date : 2026-01-01 DOI: 10.1016/j.jnr.2025.10.003

Wafa W. Tarazi PhD, MHPA, Projesh Ghosh PhD, Emily E. Ferrara MPH, Nwanneamaka Ume MPH, Paul F. Hogan MS, Emily D. Parker PhD, MPH

Background

Before the COVID-19 pandemic, some states granted certified registered nurse anesthetists (CRNAs) full practice rights (no supervision), other states required direction/collaboration under a physician, and yet others required physician supervision. However, during the pandemic, the growing healthcare needs and simultaneous shortage of healthcare providers prompted major shifts in the delivery of healthcare services via efforts at both the federal and state levels.

Purpose

To examine the impact of the pandemic-related reduced restrictions in scope of practice, specifically allowing CRNAs to practice to the full extent of their education and training, on anesthesia-related complications rates.

Methods

Using administrative claims data from Optum's de-identified Normative Health Information between January 1, 2018, and December 31, 2022, and a difference-in-differences model, we examined the association between reduced restrictions in state scope of practice and anesthesia-related complications, controlling for procedure, patient, and geographic-level characteristics.

Results

During the pandemic, there was a statistically significant (p = 0.0006) reduction of 0.02 percentage points in anesthesia complications (two anesthesia complications per 10,000 anesthesia procedures) in states that allowed pandemic-related reduced restrictions in state scope of practice compared to states with no change in scope of practice.

Conclusion

Reduced restrictions in state scope of practice during the pandemic were not associated with any increase in anesthesia-related complications. These findings add to existing evidence on the safety of anesthesia procedures performed by CRNAs and expand the evidence to include safe procedures during the pandemic. Our findings inform strategic planning and public policy to support teamwork and reform the healthcare system to prepare prudently for future healthcare emergencies.

在2019冠状病毒病大流行之前，一些州授予注册麻醉师（crna）完全执业权（不受监督），其他州要求医生指导/合作，还有一些州要求医生监督。然而，在大流行期间，不断增长的医疗保健需求和同时出现的医疗保健提供者短缺促使联邦和州两级在提供医疗保健服务方面做出重大转变。目的研究与大流行相关的业务范围限制的减少，特别是允许crna在其教育和培训的范围内进行业务，对麻醉相关并发症发生率的影响。方法利用Optum 2018年1月1日至2022年12月31日的去识别规范健康信息中的行政索赔数据，以及差异中的差异模型，研究了在控制程序、患者和地理水平特征的情况下，减少国家实践范围限制与麻醉相关并发症之间的关系。结果在大流行期间，与未改变执业范围的州相比，在允许减少与大流行相关的限制的州，麻醉并发症（每10,000次麻醉手术中有2次麻醉并发症）减少了0.02个百分点，具有统计学意义（p = 0.0006）。结论大流行期间国家范围限制的减少与麻醉相关并发症的增加无关。这些发现补充了关于crna实施麻醉程序安全性的现有证据，并将证据扩大到包括大流行期间的安全程序。我们的研究结果为战略规划和公共政策提供了信息，以支持团队合作和改革医疗体系，为未来的医疗紧急情况做好谨慎的准备。

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引用次数: 0

Policy Perspective: The burden of education debt for today’s nursing workforce 政策视角：当今护理人员的教育债务负担

IF 6.3 4区医学 Q1 NURSING

Journal of Nursing Regulation

Pub Date : 2025-10-01 DOI: 10.1016/j.jnr.2025.08.011

Thomas Harrington BA

引用次数: 0

A scoping review of virtual nursing models in inpatient, noncritical care settings 在住院病人，非重症护理设置虚拟护理模式的范围审查

IF 6.3 4区医学 Q1 NURSING

Journal of Nursing Regulation

Pub Date : 2025-10-01 DOI: 10.1016/j.jnr.2025.08.005

Tajudaullah Bhaloo PhD, MHA , Caitlin McVey MBA, RN, CPHQ, CLSSBB , Jessica Peterson PhD, RN , Marjory Williams PhD, RN

Background

The success of virtual nursing models in intensive care units has prompted its expansion to other acute care settings.

Purpose

The aim was to summarize peer-reviewed literature that described or evaluated virtual nursing models in noncritical care settings and describe policy and practice implications and future research needed to create actionable evidence.

Methods

Using the Arksey and O'Malley methodological framework, the PubMed, CINAHL, and Embase databases were searched for relevant published literature. The research team screened titles and abstracts; agreement from at least two members was required for article inclusion and data extraction.

Results

Of the 588 articles retrieved, 35 were included. Most virtual nursing care models had a specific, focused role for virtual nurses (e.g., admissions and discharges) rather than a co-caring model in which the virtual nurse had a more expanded role. Patient and nurse satisfaction were the most common outcome measures, followed by hospital throughput and efficiency measures. Factors associated with successful implementation included incorporating bedside nurse input during model development, in-person team building, and ongoing bi-directional communication between bedside and virtual nurses.

Conclusion

Model variability substantiates the need for more specific operational guidelines that define scopes and standards of practice with detailed role descriptions. Long-term implications of dividing nursing responsibilities remain unclear but may include the need to maintain competencies among bedside nurses and the development of virtual care competencies. Future research needs a unifying framework and should utilize longitudinal and multisite studies that test models in different environments.

虚拟护理模式在重症监护室的成功促使其扩展到其他急性护理环境。目的：总结描述或评估非重症护理环境中虚拟护理模式的同行评议文献，描述政策和实践意义以及创建可操作证据所需的未来研究。方法采用Arksey和O’malley方法学框架，检索PubMed、CINAHL和Embase数据库，检索相关已发表文献。研究团队筛选了题目和摘要；文章纳入和数据提取需要至少两名成员的同意。结果588篇文献中，35篇被纳入。大多数虚拟护理模式对虚拟护士都有一个特定的、重点突出的角色（例如，入院和出院），而不是虚拟护士扮演更广泛角色的共同护理模式。患者和护士满意度是最常见的结果测量，其次是医院吞吐量和效率测量。与成功实施相关的因素包括在模型开发过程中纳入床边护士的意见，面对面的团队建设，以及床边和虚拟护士之间持续的双向沟通。结论模型的可变性表明需要制定更具体的操作指南，通过详细的角色描述来定义实践的范围和标准。划分护理职责的长期影响尚不清楚，但可能包括需要保持床边护士的能力和虚拟护理能力的发展。未来的研究需要一个统一的框架，并应利用纵向和多地点的研究，在不同的环境中测试模型。

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引用次数: 0

Regulating at the AI frontier: The collision of policy, regulation, and nursing practice 人工智能前沿的监管：政策、监管和护理实践的碰撞

IF 6.3 4区医学 Q1 NURSING

Journal of Nursing Regulation

Pub Date : 2025-10-01 DOI: 10.1016/j.jnr.2025.08.012

Benjamin J. Galatzan PhD, RN , Elizabeth A. Johnson PhD, MS-CRM, RN , Meghan Reading Turchioe PhD, MPH, RN, FAHA , Christina Baker PhD, RN, NCSN, NI-BC , Ann Wieben PhD, RN

Background

Artificial intelligence (AI) is rapidly transforming clinical decision-making and healthcare delivery, yet state-level legislation addressing AI integration in patient care often lacks alignment with nursing-specific regulatory frameworks.

Purpose

This policy analysis examines enacted and proposed AI-related legislation across the United States, with specific attention on implications for nursing practice, licensure, and professional accountability.

Methods/Results

Using a structured review and thematic categorization of state legislation, eight major policy domains were identified, such as “AI in Clinical Decision-Making,” “Nursing Scope-of-Practice or Autonomy Protections,” and “AI Governance via Task Forces or Commissions.” While development of state-level AI policy is gaining momentum, few legislative efforts explicitly define nursing roles, responsibilities, or protections within AI-integrated environments. Furthermore, the majority of proposals addressing nursing autonomy are pending rather than enacted.

Conclusion

These findings highlight a growing regulatory gap that may expose nurses to increased liability, ambiguous role expectations, and reduced clinical authority in AI-augmented care settings. Key AI policy and regulatory priorities for the nursing profession focus on competencies in nursing education, updated licensure frameworks, and structured approaches for boards of nursing to assess disciplinary concerns arising from AI use. Foundational insights for nursing organizations seeking to proactively engage with AI policy development and ensure safe, ethical nursing practice in the digital era are provided.

人工智能（AI）正在迅速改变临床决策和医疗保健服务，但涉及人工智能在患者护理中的整合的州级立法往往缺乏与护理特定监管框架的一致性。本政策分析考察了美国各地颁布和提议的人工智能相关立法，特别关注对护理实践、执照和专业问责制的影响。方法/结果通过对州立法进行结构化审查和专题分类，确定了八个主要政策领域，如“临床决策中的人工智能”、“护理实践范围或自主保护”和“通过工作组或委员会进行人工智能治理”。虽然国家级人工智能政策的发展势头正在增强，但很少有立法努力明确定义人工智能集成环境中的护理角色、责任或保护。此外，大多数关于护理自主权的建议都悬而未决，而不是颁布。这些发现突出了监管差距的扩大，这可能使护士在人工智能增强的护理环境中承担更多的责任，角色期望模糊，临床权威降低。护理专业的关键人工智能政策和监管重点关注护理教育的能力、更新的执照框架以及护理委员会评估人工智能使用引起的纪律问题的结构化方法。为寻求积极参与人工智能政策制定并确保数字时代安全、道德的护理实践的护理组织提供了基本见解。

{"title":"Regulating at the AI frontier: The collision of policy, regulation, and nursing practice","authors":"Benjamin J. Galatzan PhD, RN , Elizabeth A. Johnson PhD, MS-CRM, RN , Meghan Reading Turchioe PhD, MPH, RN, FAHA , Christina Baker PhD, RN, NCSN, NI-BC , Ann Wieben PhD, RN","doi":"10.1016/j.jnr.2025.08.012","DOIUrl":"10.1016/j.jnr.2025.08.012","url":null,"abstract":"<div><h3>Background</h3><div>Artificial intelligence (AI) is rapidly transforming clinical decision-making and healthcare delivery, yet state-level legislation addressing AI integration in patient care often lacks alignment with nursing-specific regulatory frameworks.</div></div><div><h3>Purpose</h3><div>This policy analysis examines enacted and proposed AI-related legislation across the United States, with specific attention on implications for nursing practice, licensure, and professional accountability.</div></div><div><h3>Methods/Results</h3><div>Using a structured review and thematic categorization of state legislation, eight major policy domains were identified, such as “AI in Clinical Decision-Making,” “Nursing Scope-of-Practice or Autonomy Protections,” and “AI Governance via Task Forces or Commissions.” While development of state-level AI policy is gaining momentum, few legislative efforts explicitly define nursing roles, responsibilities, or protections within AI-integrated environments. Furthermore, the majority of proposals addressing nursing autonomy are pending rather than enacted.</div></div><div><h3>Conclusion</h3><div>These findings highlight a growing regulatory gap that may expose nurses to increased liability, ambiguous role expectations, and reduced clinical authority in AI-augmented care settings. Key AI policy and regulatory priorities for the nursing profession focus on competencies in nursing education, updated licensure frameworks, and structured approaches for boards of nursing to assess disciplinary concerns arising from AI use. Foundational insights for nursing organizations seeking to proactively engage with AI policy development and ensure safe, ethical nursing practice in the digital era are provided.</div></div>","PeriodicalId":46153,"journal":{"name":"Journal of Nursing Regulation","volume":"16 3","pages":"Pages 207-215"},"PeriodicalIF":6.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145271213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prevalence of artificial intelligence use and instruction in nursing education: A national study of prelicensure nursing programs in the United States 人工智能在护理教育中的应用和指导的普及：一项关于美国护理资格预审项目的全国性研究

IF 6.3 4区医学 Q1 NURSING

Journal of Nursing Regulation

Pub Date : 2025-10-01 DOI: 10.1016/j.jnr.2025.08.003

Brendan Martin PhD , Michaela Reid BS

Background

There is ample evidence that the integration of artificial intelligence (AI) tools into nursing practice is becoming more commonplace, but there are fewer national resources indicating to what degree prelicensure nursing programs employ these technologies and incorporate related topics into their curriculum.

Purpose

The current survey study sought to determine the prevalence of registered nurse (RN) and licensed practical nurse (LPN) education programs’ use of generative AI technologies, and the extent to which they embed AI and other digital health topics into their instructional content.

Methods

A national survey was conducted of all RN and LPN program administrators nationwide for which we had email contact information (N = 2744).

Results

Prelicensure RN programs (n = 122, 24 %) were more likely to use generative AI technology than LPN programs (n = 27, 12 %, p < 0.001), but more than three-quarters of both types of programs reported they do not use such tools or are not sure. In addition to the low usage of generative AI technology, few programs reported teaching advancements in AI and/or other digital health–related topics to their students (RN n = 87, 17 %; LPN n = 25, 11 %).

Conclusion

Nursing education programs that limit integration of AI into their curriculum risk potentially limiting students’ learning on evidence-based practice and may miss opportunities to promote critical reflection. The results of our study underscore the need to support nursing faculty to ensure prelicensure instructional content prepares nursing students for advancements in clinical practice.

有充分的证据表明，将人工智能（AI）工具整合到护理实践中正变得越来越普遍，但很少有国家资源表明，护理专业在多大程度上采用了这些技术，并将相关主题纳入了他们的课程。当前的调查研究旨在确定注册护士（RN）和执业护士（LPN）教育项目使用生成式人工智能技术的流行程度，以及他们在教学内容中嵌入人工智能和其他数字健康主题的程度。方法对全国所有有电子邮件联系方式的注册护士和LPN项目管理人员（N = 2744）进行调查。结果sprelicensure RN项目（n = 122,24 %）比LPN项目（n = 27,12 %, p < 0.001）更有可能使用生成式人工智能技术，但两种类型的项目中超过四分之三的人报告说他们没有使用这些工具或不确定。除了生成式人工智能技术的使用率较低外，很少有项目向学生报告人工智能和/或其他数字健康相关主题的教学进展（RN n = 87,17%; LPN n = 25,11%）。结论：限制人工智能融入课程的护理教育项目可能会限制学生对循证实践的学习，并可能失去促进批判性反思的机会。我们的研究结果强调需要支持护理教师，以确保执照前的教学内容准备护理学生在临床实践中的进步。

{"title":"Prevalence of artificial intelligence use and instruction in nursing education: A national study of prelicensure nursing programs in the United States","authors":"Brendan Martin PhD , Michaela Reid BS","doi":"10.1016/j.jnr.2025.08.003","DOIUrl":"10.1016/j.jnr.2025.08.003","url":null,"abstract":"<div><h3>Background</h3><div>There is ample evidence that the integration of artificial intelligence (AI) tools into nursing practice is becoming more commonplace, but there are fewer national resources indicating to what degree prelicensure nursing programs employ these technologies and incorporate related topics into their curriculum.</div></div><div><h3>Purpose</h3><div>The current survey study sought to determine the prevalence of registered nurse (RN) and licensed practical nurse (LPN) education programs’ use of generative AI technologies, and the extent to which they embed AI and other digital health topics into their instructional content.</div></div><div><h3>Methods</h3><div>A national survey was conducted of all RN and LPN program administrators nationwide for which we had email contact information (<em>N</em> = 2744).</div></div><div><h3>Results</h3><div>Prelicensure RN programs (<em>n</em> = 122, 24 %) were more likely to use generative AI technology than LPN programs (<em>n</em> = 27, 12 %, <em>p</em> < 0.001), but more than three-quarters of both types of programs reported they do not use such tools or are not sure. In addition to the low usage of generative AI technology, few programs reported teaching advancements in AI and/or other digital health–related topics to their students (RN <em>n</em> = 87, 17 %; LPN <em>n</em> = 25, 11 %).</div></div><div><h3>Conclusion</h3><div>Nursing education programs that limit integration of AI into their curriculum risk potentially limiting students’ learning on evidence-based practice and may miss opportunities to promote critical reflection. The results of our study underscore the need to support nursing faculty to ensure prelicensure instructional content prepares nursing students for advancements in clinical practice.</div></div>","PeriodicalId":46153,"journal":{"name":"Journal of Nursing Regulation","volume":"16 3","pages":"Pages 216-222"},"PeriodicalIF":6.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145271214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Technology and the nursing needs of tomorrow: Innovation and regulation 未来的技术和护理需求：创新和监管

IF 6.3 4区医学 Q1 NURSING

Journal of Nursing Regulation

Pub Date : 2025-10-01 DOI: 10.1016/j.jnr.2025.08.017

Carol Anne Timmings (Interim Editor in Chief)

引用次数: 0

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