Article(id=1322937069949038870, tenantId=1146029695717560320, journalId=1220038315760373764, issueId=1322936785516503921, articleNumber=null, orderNo=null, doi=10.12102/j.issn.1009-6493.2026.11.026, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1756742400000, receivedDateStr=2025-09-02, revisedDate=1778169600000, revisedDateStr=2026-05-08, acceptedDate=null, acceptedDateStr=null, onlineDate=1793342376457, onlineDateStr=2026-10-30, pubDate=1781020800000, pubDateStr=2026-06-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793342376457, onlineIssueDateStr=2026-10-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793342376457, creator=13701087609, updateTime=1793342376457, updator=13701087609, issue=Issue{id=1322936785516503921, tenantId=1146029695717560320, journalId=1220038315760373764, year='2026', volume='40', issue='11', pageStart='1809', pageEnd='2000', issueExtLink='null', onlineDate='null', pubDate='1781020800000', pubDateStr='2026-06-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793342308644, creator='13701087609', updateTime=1793343121351, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322940194344796237, tenantId=1146029695717560320, journalId=1220038315760373764, issueId=1322936785516503921, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322940194344796238, tenantId=1146029695717560320, journalId=1220038315760373764, issueId=1322936785516503921, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1991, endPage=1995, ext={EN=ArticleExt(id=1322937070372663575, articleId=1322937069949038870, tenantId=1146029695717560320, journalId=1220038315760373764, language=EN, title=Research progress on the application of complexity science in nursing education, columnId=1220689485315101342, journalTitle=Chinese Nursing Research, columnName=Review Articles, runingTitle=null, highlight=null, articleAbstract=

This paper outlined the core characteristics of complexity science and complex adaptive systems,as well as their applicability within nursing education systems.It elaborated on the specific applications and practical outcomes of complexity science in nursing education from four dimensions:curriculum restructuring,innovative teaching strategies,technology-enabled empowerment,and systemic analysis.Finally,the paper summarized the current major challenges,including difficulties in translating theory into teaching practice,outdated evaluation systems,and insufficient complex thinking skills among educators.It proposed future efforts to advance high-fidelity simulation technologies,developed dynamic assessment frameworks,and promoted the establishment of self-organizing learning communities among teachers,thereby facilitating a deeper transition of nursing education toward a complexity-oriented paradigm.

, authors=Jinlong LIU, Qinqin LIU, Wanchen QU, Wei ZHANG, authorsList=Jinlong LIU, Qinqin LIU, Wanchen QU, Wei ZHANG, authorCompany=null, correspAuthors=Wei ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322937071165387032, articleId=1322937069949038870, tenantId=1146029695717560320, journalId=1220038315760373764, language=CN, title=复杂科学在护理教育中应用的研究进展, columnId=1220689485482873504, journalTitle=护理研究, columnName=科研综述, runingTitle=null, highlight=null, articleAbstract=

概述复杂科学与复杂适应系统的核心特征及其在护理教育系统中的适用性,并从课程重构、教学策略创新、技术赋能与系统解析4个维度阐述复杂科学在护理教育中的应用与实践成效,总结当前面临的主要挑战,包括理论向教学实践转化困难、评价体系滞后与教师复杂思维能力不足等,并提出未来应着力发展高仿真模拟技术、构建动态评估体系、推动教师自组织学习共同体建设,以促进护理教育向复杂性范式的深度转型。

, authors=刘金龙, 刘琴琴, 曲婉晨, 张薇*, *, authorsList=刘金龙, 刘琴琴, 曲婉晨, 张薇, authorCompany=null, correspAuthors=张薇, authorNote=

刘金龙,助教,硕士研究生

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张薇,E-mail:
ZHANG Wei, E-mail:
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复杂科学在护理教育中应用的研究进展
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刘金龙 , 刘琴琴 , 曲婉晨 , 张薇 *, *
护理研究 | 科研综述 2026,40(11): 1991-1995
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护理研究 |科研综述 2026 , 40 (11) : 1991 -1995
复杂科学在护理教育中应用的研究进展
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刘金龙, 刘琴琴, 曲婉晨, 张薇*, *
作者信息
  • 1海军军医大学护理系,上海 200433
通讯作者:
张薇,E-mail:
ZHANG Wei, E-mail:
作者简介:

刘金龙,助教,硕士研究生

Research progress on the application of complexity science in nursing education
Jinlong LIU, Qinqin LIU, Wanchen QU, Wei ZHANG
Affiliations
  • 1School of Nursing, Naval Medical University, Shanghai 200433 China
出版时间: 2026-06-10 doi: 10.12102/j.issn.1009-6493.2026.11.026
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概述复杂科学与复杂适应系统的核心特征及其在护理教育系统中的适用性,并从课程重构、教学策略创新、技术赋能与系统解析4个维度阐述复杂科学在护理教育中的应用与实践成效,总结当前面临的主要挑战,包括理论向教学实践转化困难、评价体系滞后与教师复杂思维能力不足等,并提出未来应着力发展高仿真模拟技术、构建动态评估体系、推动教师自组织学习共同体建设,以促进护理教育向复杂性范式的深度转型。

复杂科学  /  复杂适应系统  /  护理教育  /  综述

This paper outlined the core characteristics of complexity science and complex adaptive systems,as well as their applicability within nursing education systems.It elaborated on the specific applications and practical outcomes of complexity science in nursing education from four dimensions:curriculum restructuring,innovative teaching strategies,technology-enabled empowerment,and systemic analysis.Finally,the paper summarized the current major challenges,including difficulties in translating theory into teaching practice,outdated evaluation systems,and insufficient complex thinking skills among educators.It proposed future efforts to advance high-fidelity simulation technologies,developed dynamic assessment frameworks,and promoted the establishment of self-organizing learning communities among teachers,thereby facilitating a deeper transition of nursing education toward a complexity-oriented paradigm.

complexity science  /  complex adaptive systems  /  nursing education  /  review
刘金龙, 刘琴琴, 曲婉晨, 张薇. 复杂科学在护理教育中应用的研究进展. 护理研究, 2026 , 40 (11) : 1991 -1995 . DOI: 10.12102/j.issn.1009-6493.2026.11.026
Jinlong LIU, Qinqin LIU, Wanchen QU, Wei ZHANG. Research progress on the application of complexity science in nursing education[J]. Chinese Nursing Research, 2026 , 40 (11) : 1991 -1995 . DOI: 10.12102/j.issn.1009-6493.2026.11.026
现代医疗环境正经历深刻变革,护理教育面临前所未有的复杂性挑战[1]。人口老龄化、疾病谱慢性化、健康需求多元化以及医疗技术的快速迭代,对护士的核心能力提出了更高要求[2]。护士不仅需掌握扎实的临床技能与理论知识,更需在动态、不确定、多因素交织的复杂临床场景中,展现胜任力,如临床推理、系统思维、自主学习能力等[3]。然而,传统护理教育多基于线性思维模式,强调分科知识与标准化技能训练,在应对个体差异大、病情变化快、团队互动复杂等现实场景时,存在明显局限[4]。在此背景下,复杂科学(complexity science)的理论与方法为护理教育提供了新的范式。目前,复杂科学在国内外护理教育中已有初步应用,但其应用经验、核心挑战与发展方向尚缺乏系统梳理。因此,本研究旨在综述复杂科学在护理教育中的应用现状,分析关键问题,并展望未来,为护理教育的复杂转型提供参考。
复杂科学是研究复杂系统结构、行为与动力学的交叉学科,兴起于20世纪末。其关注由大量相互作用主体所构成的系统如何涌现出集体行为、自适应性与演化规律。复杂科学并非单一理论,而是一个包含多种理论与方法的学科群,其核心在于超越线性还原论,采用整体论与系统思维探究世界的复杂性[5]。
复杂系统广泛存在于自然、社会与技术领域,如生态系统、互联网、经济市场与医疗卫生系统等。它们通常具有以下特征[6-7]:1)非线性。主体间的相互作用不呈简单叠加关系,微小变化可能通过反馈放大,导致难以预料的结果。2)涌现性。系统整体表现出主体所没有的新属性或行为,源于主体间的非线性互动。3)自组织性。系统在无中央控制的情况下,通过局部互动自发形成宏观有序结构。4)适应性。个体能根据环境变化调整行为,推动系统演化。5)动态网络化结构。系统以网络形式存在,连接多样且动态变化。
复杂适应系统理论由美国学者Holland[8]提出,是复杂科学的重要分支,强调系统的复杂性源于适应性主体之间的互动与学习。主体能感知环境、与其他主体交流,并根据反馈调整行为规则,从而推动系统宏观层面的演化[9]。为研究这类由微观互动涌现宏观复杂性的系统,复杂适应系统采用“自下而上”的建模思路(如基于主体建模),通过模拟微观互动研究宏观现象的涌现[10]。
护理教育系统本身就是一个典型的复杂系统[11],主要体现在:1)系统由适应性主体(如学生、教师、临床导师、管理人员、病人等)构成;2)处于动态变化的环境(如医疗技术、社会需求、卫生政策、知识体系等外部环境持续变化)中;3)展现出明显的涌现特性,如教育质量、团队协作文化、学生的临床胜任力等均为系统整体涌现的结果;4)蕴含丰富的非线性关系,如教学干预的效果往往不呈简单线性关系。因此,应用复杂科学的理念与方法审视和革新护理教育,具有内在的理论适切性和实践必要性,为理解其动态本质、设计干预措施、评估综合成效提供了新视角。
为应对复杂医疗环境,越来越多学者将复杂科学原则融入课程设计,推动教学目标从“知识达标”转向“能力生成”的转变。例如,Rosenau等[12]将复杂科学的原则整合进护理课程,将课程视为一个复杂适应系统,构建非线性、动态调整的学习路径,突出临床推理、知识转化、伦理决策等高阶能力培养。教学实施以“整合性学习”为核心,打破学科壁垒,通过模块化课程、叙事教学、模拟实践、反思训练及实践导师制等方式,促进学生将理论、实践与多样情景深度融合,最终形成应对真实护理实践的综合能力。Lis等[13]在研究生课程中引入关系本位照护、创造性探究与系统领导力培养,借助案例研讨、模拟实践、反思性学习与质量改进项目等多种策略,促进学生自我组织、适应变化及创新行为的涌现,结果显示,该类课程不仅帮助学生理解医疗系统的复杂本质,也增强了其在不确定环境中推动变革的能力。Starnes-Ott等[14]将复杂适应系统理论系统应用于护理麻醉教育向护理实践型博士(doctor of nursing practice,DNP)转型过程,课程整合了美国护理学院协会护理实践型博士核心能力与认证委员会标准,引入系统思维、团队协作及领导力研讨,并通过案例研究、模拟演练与临床研讨帮助学生理解从临床微观到政策宏观的系统关联,学生通过开展护理实践型博士质量改进项目,实践利益相关者分析与流程映射,深入领会系统变革的复杂性,结果发现,此类课程可有效促进学生从“技术执行者”向“系统领导者”转型,提升了应对复杂系统挑战的能力。
为贴近真实临床环境的高度不确定性与非线性特征,复杂科学原则被引入情景模拟教学设计中。例如,Dunn等[15]开发了一套模拟方案,要求学生同时扮演护士与病人角色,通过角色互换构建高度真实的临床情景,融入病情非线性演变、模糊指征和动态人际互动等复杂要素。学习者在安全环境中体验“混沌边缘”,锻炼临床决策与实时适应能力。该模拟刻意保留不可预测性与动态变化,打破传统模拟教学中过度预设的结构,更真实地复现临床工作的复杂性。Pollard等[16]则通过低仿真模拟教学,让学生在无预设结构的任务中自主应对不确定性,体会团队动态中的非线性与自适应过程。结合反馈、复盘与递归学习机制,引导学生从个体与团队层面反思行为与系统影响,增强其在复杂情景中的角色认知和关系管理能力。
PBL强调以学生为中心,围绕现实中的非结构化问题展开小组探究。Hodges[17]将复杂性原则(如非线性、自组织和涌现)融入PBL教学,在一门面向35名护理学生的社区临床护理课程中,遵循“简单规则与宽松边界”的理念,赋予学生更多自主权。学生在教师引导下以小组形式自我组织、协商任务,通过动态互动理解社区健康系统。通过多元评估发现,该模式有效提升了学生的系统思维、团队协作、自适应学习能力,以及应对不确定性的心理韧性与专业认同感。
为克服传统护理教育中内容灌输、结构线性、学生被动等局限,复杂科学理念被引入在线学习环境设计。Mitchell等[18]开发的Daagu在线学习平台正是基于复杂科学理念形成的一个支持跨学科讨论、多模态资源共享与动态课程生成的互动环境。平台鼓励学生自主探索,根据兴趣发起讨论并上传资源,逐步共同建构课程内容;教师角色转变为学习促进者,通过提问、引入扰动、促进观点联结激发深度反思与集体对话;平台还借助可视化工具展示讨论网络与知识演进,强化学生的系统思维。研究显示,相较于传统电子学习系统,该设计显著提高了学生的参与度和批判性思维能力。
基于主体建模通过模拟多个自主主体之间的交互,揭示系统层面的复杂行为与动态模式,尤其适用于具有适应性与决策能力的情景。Dubivi等[19]基于主体建模开发的“PILL-Cells”模型用于护理药理学教学,帮助学生理解糖尿病治疗中动态、非线性的生化过程与药物机制。该模型在NetLogo平台上模拟胰腺、肌肉和肝脏细胞在葡萄糖调节中的行为;学生可通过调整药物剂量和病人行为(如运动或禁食),直观观察从分子、细胞器到细胞层面的微观互动如何“涌现”为宏观的生理或病理状态(如血糖变化)。结合引导式工作单,学生进行自主探索与机制解释,强化对药物路径和跨层级系统关系的理解。实证结果表明,使用该模型的学生不仅在概念知识(尤其是药物作用机制方面)和期末考试成绩上优于传统讲座组,还表现出更强的系统思维与跨层级推理能力。
护理教育系统本身具有典型复杂系统特征。学者运用复杂科学理论分析其内部的涌现现象与适应机制。Mulready-Shick等[20]将专用教育单元(dedicated education unit,DEU)视为复杂适应系统,分析其如何通过各类主体(临床指导员、临床教师协调员、普通护士、管理与教育合作伙伴、学生)的非线性互动与自适应行为推动系统演进。研究通过对34名参与者(包括12名专用教育单元临床指导护士、12名普通护士、3名临床教师协调员和7名中层管理与教育合作伙伴)进行多轮访谈,识别出“反复沟通”“共同解决问题”“角色适应”等涌现主题,揭示专用教育单元在复杂临床教育环境中的持续演进机制。Donnelly等[21]以复杂科学为框架,借助“模式匹配”方法分析临床实习这一复杂适应系统中学生、教师、病人、机构、课程安排等多重要素的非线性互动。研究提出实习数量、类型与地点影响学习结果(护理学生技能形成、知识整合与专业身份建立)等假设,并通过实证比对,揭示变量间复杂的关系模式,超越传统线性因果解释,为理解临床实习提供新路径。
复杂科学提供多层级分析框架,助力理解护理教育从个体到系统整体的动态机制。Garcia等[22]认为人格并非孤立特质的集合,而是一个复杂适应系统,基于此研究了218名护理学生的人格特质(气质与性格)与倦怠、健康及幸福感之间的非线性关系。通过潜在剖面分析,识别出“有组织/可靠型”与“情绪化/不可靠型”两种人格组合,表明心理健康受整个人格系统协调性的影响,而非单一特质独立作用。Bogren等[23]在对尼泊尔助产士专业化进程中多元行动者(如政府、学术组织、协会与国际捐助者等)间互动机制的研究中,运用复杂适应系统原则(如自适应行为、涌现性和系统依赖),通过半结构化访谈,识别出在资源竞争背景下面临的障碍因素(如利益分歧、专业竞争)与促进因素(如共同目标、协作意愿),强调多边协同对系统变革的关键作用。Lam Nogueira[24]以澳门护理教育转型为例,分析其从医院培训向高等教育体系的演进,研究基于“必要多样性法则”,提出系统需通过引入国际师资、推进课程认证与英语教学等方式维持对外部环境的适应性,并总结出加强课程评估、整合在线资源等韧性增强策略,验证了护理教育系统作为复杂适应系统的自组织、连接与共演等特性,也为小型地区护理教育系统发展提供实践路径。
复杂科学为护理教育的转型提供了坚实的理论支撑,但其高度抽象的概念(如非线性、涌现性)与教学实践所需的可操作性之间存在显著差距。例如,现有复杂情景模拟在真实性和交互层次上仍有局限,难以充分再现真实医疗场景中多层次嵌套的复杂性[25];基于主体建模等教学策略虽在护理教学中已有运用[19],但其因高计算资源需求限制难以推广。
因此,未来应着重弥合复杂科学理论与护理教学实践之间的转化鸿沟。可行路径:首先,可对复杂科学概念进行教学化解构与可视化呈现,通过诸如阶梯式仿真教学项目等逐步增加不确定性与复杂性,进而将非线性、涌现性等抽象原理转化为可操作的教学模块。其次,可融合虚拟现实(VR)/增强现实(AR)等技术构建高保真复杂临床情景,提升系统反馈的真实性,推动模拟教学技术的深度融合与迭代升级。再次,可探索低成本、易推广的复杂科学教学策略,如优化基于主体建模等计算模拟方法,开发轻量化教学平台,降低硬件依赖与使用门槛。最后,可结合叙事教学、案例推理等教学方法,以弥补纯技术路径在情感、伦理等维度模拟的不足。
目前,复杂科学在护理教学评价中的应用较少。学生能力的发展本质是一个动态、非线性的涌现过程,现有的评估体系往往侧重衡量“是否达到最低能力标准”,却难以有效捕捉“能力在复杂情景中动态发展”的关键维度。一方面,传统量化方法(如线性回归)在揭示教学过程中存在的非线性因果关系和动态涌现现象方面存在明显局限[26];另一方面,质性方法虽能够深入探索系统内部的动态机制,却受限于样本规模较小和研究者的主观解释,影响结论的普适性与稳健性[27]。未来应构建多维、动态评估体系,开发能够实时捕捉行为与认知过程的评估技术,系统量化护生在面对突发情景时所表现的认知转换灵活性、策略调节轨迹以及跨场景系统思维深度,从而科学、全面地验证护理教育在复杂临床能力培养方面的实际效果。
教师是推动护理教育向复杂科学范式转型的关键。当前许多教师仍困于传统线性教学范式,对复杂概念理解不足[28],角色转变中也容易出现职业认同焦虑[29]。研究指出,为有效突破这一瓶颈,未来应构建教师复杂思维发展支持体系[30]。教师培育项目本身就是一个具有复杂系统特征的学习生态,即以自组织的教师学习共同体,立足于真实教育情景中的复杂性挑战,提倡开放分享、迭代反思与动态调整[31]。只有将教师专业发展过程真正嵌入复杂系统的运作逻辑之中,才能切实培养其应对教育复杂性的核心素养,最终推动其实现从知识传授者到思维引导者的深层角色转变。
复杂科学为理解和重塑护理教育提供了强大的理论视角与实践工具,推动其从传统的线性、还原式范式走向更具动态性、适应性和整合性的新范式。目前,该理论在课程设计、教学策略、技术应用与系统分析等多方面的具体进展,表明其在促进学生系统思维、临床应变与协同创新等核心能力发展方面具有显著潜力。然而,当前仍面临理论转化、效果评价与师资转型等现实挑战。未来需进一步推动复杂科学与教育实践的深度融合,发展适配的技术工具与评价体系,构建支持教师角色转变的专业学习生态,从而最终实现护理教育系统对复杂健康照护环境的有效适应与持续演进。

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doi: 10.12102/j.issn.1009-6493.2026.11.026
  • 接收时间:2025-09-02
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  • 出版时间:2026-06-10
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  • 收稿日期:2025-09-02
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    1海军军医大学护理系,上海 200433

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2种不同金属材料的力学参数
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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