围术期危机模拟培训中医护临床决策现状与智慧教学技术需求

谭嘉裕; 郭隽英; 冯霞; 龚凤球; 杨璐; 杨达雅; 刘家欣

doi:10.3760/cma.j.cn116021-20260109-02249

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围术期危机模拟培训中医护临床决策现状与智慧教学技术需求

数智护理教育专题 | 更新时间：2026-05-02

- 围术期危机模拟培训中医护临床决策现状与智慧教学技术需求
- Current status of clinical decision-making and needs for intelligent teaching technologies in perioperative crisis simulation training of anesthesia nurses and anesthesiologists
- 中华医学教育探索杂志 2026年25卷第4期页码：410-416
- 作者机构：
  
  1.中山大学附属第一医院麻醉科，广州 510080
  2.中山大学附属第一医院手术麻醉中心，广州 510080
  3.中山大学附属第一医院心血管医学部心内一科，广州 510080
  4.中山大学附属第一医院医学教师发展中心，广州 510080
- 作者简介：
  
  刘家欣，Email：liujiax@mail.sysu.edu.cn
- 基金信息：
  
  2022年广东省继续教育质量提升工程建设类项目(JXJYGC2022GX265);中山大学2026年教学质量工程与教学改革项目（教务[2026]36号-369项）
- DOI：10.3760/cma.j.cn116021-20260109-02249
  中图分类号： R-05
- 收稿：2026-01-09，
  
  纸质出版：2026-04-20
- 稿件说明：
移动端阅览
谭嘉裕, 郭隽英, 冯霞, 等. 围术期危机模拟培训中医护临床决策现状与智慧教学技术需求[J]. 中华医学教育探索杂志, 2026, 25(4): 410-416.

Tan Jiayu, Guo Junying, Feng Xia, et al. Current status of clinical decision-making and needs for intelligent teaching technologies in perioperative crisis simulation training of anesthesia nurses and anesthesiologists[J]. Chinese Journal of Medical Education Research, 2026, 25(4): 410-416.
谭嘉裕, 郭隽英, 冯霞, 等. 围术期危机模拟培训中医护临床决策现状与智慧教学技术需求[J]. 中华医学教育探索杂志, 2026, 25(4): 410-416. DOI： 10.3760/cma.j.cn116021-20260109-02249.

Tan Jiayu, Guo Junying, Feng Xia, et al. Current status of clinical decision-making and needs for intelligent teaching technologies in perioperative crisis simulation training of anesthesia nurses and anesthesiologists[J]. Chinese Journal of Medical Education Research, 2026, 25(4): 410-416. DOI： 10.3760/cma.j.cn116021-20260109-02249.

摘要

目的

探讨麻醉科/手术室护士与麻醉医生在围术期危机模拟培训中的临床决策差异，分析其智慧教学技术偏好特征及影响因素，为优化智慧教学技术应用提供依据。

方法

采用便利抽样法，于2022年10月至2025年8月，问卷调查参与本中心围术期危机模拟培训的432名护士与医生。使用SPSS 28.0进行卡方检验和多因素 Logistic回归分析。

结果

回收有效问卷400份，有效率92.59%。受访者中220人（55.00%）有智慧教学偏好。护士临床决策更依赖“上级医师指示”（

²=8.53，

=0.004），因“时间紧迫性”（

²=7.18，

=0.007）和“团队协作不畅”（

²=12.73，

0.001）产生的压力高于医生，更关注“病例真实性”（

²=8.01，

=0.005）和“错误容忍度”（

²=10.29，

0.001）。麻醉医生更倾向依据“既往类似病例经验”（

²=5.70，

=0.017），更重视“教员反馈的及时性”（

²=23.77，

0.001）及“模拟设备与真实设备的兼容性”（

²=21.71，

0.001）。护士与医生在“团队人员建议”（

²=5.75，

=0.017）、“病例真实性”（

²=5.06，

=0.025）和“团队角色分工与协作”（

²＝6.60，

=0.010）项的教学技术偏好差异具有统计学意义。护士智慧教学技术偏好多因素分析显示，主管护理师组较低（

=0.49， 95%

=0.25~0.94，

=0.030）。

结论

护士与医生的围术期危机决策和教学技术偏好存在一定差异，职称是影响护士智慧教学技术偏好的重要因素。将智慧教学技术融入模拟培训，有助于制定个性化教学策略。

Abstract

Objective

To investigate differences in clinical decision-making between anesthesia/operating room nurses and anesthesiologists during perioperative crisis simulation training

analyze their preferences for intelligent teaching technologies and associated influencing factors

and provide a basis for optimizing the application of intelligent teaching technologies.

Methods

Using a convenience sampling method

a questionnaire survey was conducted from October 2022 to August 2025 among 432 nurses and anesthesiologists who participated in perioperative crisis simulation training at our center. Chi-square tests and multivariable logistic regression analyses were performed using SPSS 28.0.

Results

A total of 400 valid questionnaires were collected

yielding a response rate of 92.59%. Among the respondents

220 (55.00%) reported a preference for intelligent teaching technologies. Nurses relied more on instructions from senior physicians in clinical decision-making (

=8.53

=0.004) and experienced greater pressure related to time constraints (

=7.18

=0.007) and ineffective team collaboration (

=12.73

0.001) compared to anesthesiologists. Nurses also placed greater emphasis on case realism (

=8.01

=0.005) and error tolerance (

=10.29

0.001). Anesthesiologists were more inclined to base decisions on experience with similar previous cases (

=5.70

=0.017) and attached greater importance to timeliness of instructor feedback (

=23.77

=0.001) and compatibility between simulation equipment and real clinical devices (

=21.71

0.001). Significant differences in teaching technology preferences between nurses and anesthesiologists were observed regarding team members' suggestions (

=5.75

=0.017)

case realism (

=5.06

=0.025)

and team role allocation and collaboration (

=6.60

=0.010). Multivariable analysis of nurse preference for intelligent teaching technologies showed a lower preference among charge nurses (odds ratio=0.49

95%

=0.25-0.94

=0.030).

Conclusions

Differences exist between nurses and anesthesiologists in perioperative crisis decision-making and preferences for teaching technologies

with professional title identified as a key factor influencing nurse preference for intelligent teaching technologies. Integrating intelligent teaching technologies into simulation training may facilitate the development of personalized teaching strategies.

关键词

Keywords

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