远程交互教学在超声气道管理的图像识别和学习意图上的效果评价

田园; 郎珈馨; 张越伦; 于春华

doi:10.3760/cma.j.cn116021-20240329-01921

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远程交互教学在超声气道管理的图像识别和学习意图上的效果评价

协和麻醉毕业后教育探索专栏 | 更新时间：2024-12-26

- 远程交互教学在超声气道管理的图像识别和学习意图上的效果评价
- Effectiveness of distance interactive learning in image recognition and learning intentions for ultrasound airway management
- 中华医学教育探索杂志 2024年23卷第12期页码：1613-1617
- 作者机构：
  
  1.中国医学科学院　北京协和医学院　北京协和医院麻醉科，北京　100730
  2.中国医学科学院　北京协和医学院　北京协和医院医学科学研究中心，北京　100730
- 作者简介：
  
  郎珈馨，Email：langjx09@163.com
- 基金信息：
  
  中央高水平医院临床科研业务费(2022-PUMCH-A-148)
- DOI：10.3760/cma.j.cn116021-20240329-01921
  中图分类号： R445.1
- 纸质出版日期：2024-12-20，
  
  收稿日期：2024-03-29，
- 稿件说明：
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田园, 郎珈馨, 张越伦, 等. 远程交互教学在超声气道管理的图像识别和学习意图上的效果评价[J]. 中华医学教育探索杂志, 2024, 23(12): 1613-1617.

TIAN YUAN, LANG JIAXIN, ZHANG YUELUN, et al. Effectiveness of distance interactive learning in image recognition and learning intentions for ultrasound airway management. [J]. Chinese journal of medical education research, 2024, 23(12): 1613-1617.
田园, 郎珈馨, 张越伦, 等. 远程交互教学在超声气道管理的图像识别和学习意图上的效果评价[J]. 中华医学教育探索杂志, 2024, 23(12): 1613-1617. DOI： 10.3760/cma.j.cn116021-20240329-01921.

TIAN YUAN, LANG JIAXIN, ZHANG YUELUN, et al. Effectiveness of distance interactive learning in image recognition and learning intentions for ultrasound airway management. [J]. Chinese journal of medical education research, 2024, 23(12): 1613-1617. DOI： 10.3760/cma.j.cn116021-20240329-01921.

摘要

目的

比较超声气道管理的远程交互教学前后，图像识别能力和学习意图的差异，以从客观和主观上评价教学效果。

方法

招募北京协和医院麻醉科工作的61名医师作为研究对象，通过远程交互教学进行培训，并使用问卷调查来评价教学前后在客观图像识别能力和主观学习意图方面的差异。采用配对

检验和Wilcoxon配对秩和检验进行统计分析。

结果

共有48名麻醉医师完成了教学及评估。教学前后，麻醉医师对超声气道相关解剖结构识别的准确率从（45.98±18.57）%提高到（88.38±7.92）%，误诊率由（60.68±29.83）%降低到（8.53±4.34）%，差异均具有统计学意义（

=14.74，

0.001；

=-6.00，

0.001）。教学前后气管插管的超声识别准确率从（42.50±19.62）%提升至（66.25±23.40）%，差异具有统计学意义（

=-4.08，

0.001）。教学前后超声气道管理综合评估的准确率从（45.61±17.00）%显著提高到（85.80±7.69）%，误诊率则由（59.41±29.05）%显著降低至（8.46±4.27）%，差异均具有统计学意义（

=14.48，

0.001；

=-6.00，

0.001）。然而，教学后，尽管麻醉医师在临床应用情景、超声切面与体表标志、超声图像特征等方面的学习意图有所下降，但在操作方法的学习意图方面并未观察到明显变化。

结论

远程交互教学有助于麻醉医师超声气道相关图像识别能力的提升，并满足特定学习需求。

Abstract

Objective

To investigate the changes in image recognition ability and learning intentions after distance interactive learning

and to assess the teaching effect objectively and subjectively.

Methods

A total of 61 physicians working in Department of Anesthesiology

Peking Union Medical College Hospital

were enrolled as subjects and received training with the distance interactive learning method

and a questionnaire survey was conducted to assess the changes in objective image recognition ability and subjective learning intentions after teaching. The paired

-test a

nd the Wilcoxon paired rank test were used to perform statistical analyses.

Results

A total of 48 anesthesiologists completed the learning and assessments. After training

there was a significant increase in the accuracy rate of recognizing the anatomical structures of the airway on ultrasound images from (45.98±18.57)% to (88.38±7.92)% (

=14.74

0.001)

and there was a significant reduction in misdiagnosis rate from (60.68±29.83)% to (8.53±4.34)% (

=-6.00

0.001). After teaching

the accuracy rate of identifying tracheal intubation on ultrasound images increased from (42.50±19.62)% to (66.25±23.40)% (

=-4.08

0.001). After teaching

the accuracy rate of comprehensive ultrasound airway assessment increased from (45.61±17.00)% to (85.80±7.69)% (

=14.48

0.001)

and the misdiagnosis rate decreased from (59.41±29.05)% to (8.46±4.27)% (

=-6.00

0.001). After teaching

although there were reductions in the learning intentions for clinical application scenarios

ultrasound section and body surface landmarks

and ultrasound image features

there were no significant changes in the learning intentions for operation techniques.

Conclusions

Distance interactive training helps anesthesiologists to improve their ability for recognition of ultrasound airway images and can meet their specific learning intentions.

关键词

超声气道管理远程教学交互教学影响因素

Keywords

UltrasoundAirway managementDistance learningInteractive learningInfluencing factor

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