基于APP线上自主学习模式的关节超声诊断的精准教学探索

基础医学与临床 ›› 2021, Vol. 41 ›› Issue (9): 1371-1375.

基于APP线上自主学习模式的关节超声诊断的精准教学探索

王铭, 赵辰阳, 韦瑶, 桂阳, 赵瑞娜, 王若蛟, 杨萌^*

中国医学科学院北京协和医学院北京协和医院超声医学科,北京 100730

收稿日期:2020-10-13 修回日期:2021-04-06 出版日期:2021-09-05 发布日期:2021-09-02
通讯作者: *amengameng@hotmail.com
基金资助:
国家自然科学基金(61971447);北京市自然科学基金杰出青年科学基金(18JQG060);国际科技合作计划(2015DFA30440);北京市科技新星交叉合作科技项目(xxjc201812);北京市科技新星项目(Z131107000413063); 北京协和医学院2020年中央高校教育教学改革专项基金(2020zlgc0120)

Evaluation of precision teaching based on APP for online self-learning in joint diagnostic ultrasound

WANG Ming, ZHAO Chen-yang, WEI Yao, GUI Yang, ZHAO Rui-na, WANG Ruo-jiao, YANG Meng^*

Department of Ultrasound Medicine,Peking Union Medical College Hospital,CAMS ＆ PUMC,Beijing 100730,China

Received:2020-10-13 Revised:2021-04-06 Online:2021-09-05 Published:2021-09-02
Contact: *amengameng@hotmail.com

摘要/Abstract

摘要： 目的探讨应用程序(APP)线上自主学习模式在关节超声诊断精准教学中的应用价值。方法依据12名超声医师诊断经验不同分为3组。首先通过APP培训课程自主学习“关节超声诊断评分标准”,随后进入考核平台,对140个手部类风湿关节炎进行评分。用诊断符合率及组内相关系数(ICC)对考核结果进行分析(%/ICC);用调查问卷收集学员的教学反馈意见。结果 3组超声医师的诊断一致性较好(65.2%～67.7%≥0.8),其中滑膜炎血流分级及腱鞘炎有无判断考核结果最好(74.40%～81.70%/0.91～0.94; 87.50%～93.80%/0.97～0.98),而滑膜炎灰阶超声分级误判较高(45.10%～47.80%/0.58～0.74),骨侵蚀的ICC较差(66.70%～77.80%/0.44～0.58)。在手部关节中,第3掌指关节(MCP3)与第2/3远端指间关节(PIP2/3)病变诊断符合率较低(61.1%～71.3%;57.4%～63.9%),腕关节诊断符合率差异较大(64%～80%)。受训学员普遍喜欢上述教学方法(75%),认为提高了学习效率与兴趣(91.7%),但在超声评分标准阐述更加明确化,考核图片更加清晰化,以及合理运用动态视频教学等方面仍有待优化完善。结论基于APP的线上自主学习模式可作为关节超声诊断学习的有效手段,精细化分析考核结果及学员教学反馈有助于优化教学方法,从而实现关节超声诊断的精准教学。

关键词: 超声波检查术, 关节超声诊断, 超声评分, 自主学习, 精准教学

Abstract: Objective To evaluate the use of online self-learning application(APP) for precision teaching in joint diagnostic ultrasound. Methods Twelve sonographers were divided into three groups(4 in each) based on their experience in ultrasound diagnosis. At first, all of them were approached to the training courses in self-learning APP to study “the joint diagnostic ultrasound scoring system”. After that, they were admitted to “the ultrasound images assessment platform” in-APP to perform the ultrasound score on 140 small joints with inflammatory rheumatic diseases. The overall agreement rate(%) and intraclass correlation coefficients(ICC) values were calculated to analyze the assessment results among the three groups(%/ICC). A questionnaire survey was also administered at the end of the study via the APP to determine the ease of use of self-learning APP. Results A good interobserver agreement was reached among the three groups(65.2%～67.7%/0.49～0.97). In detail, the best interobserver results were found for the detection of Power Doppler Ultrasound(PDUS) synovitis(74.40%～81.70%/0.91～0.94) and tenosynovitis/paratenonitis in all joints(87.50%～93.80%/0.97～0.98). Good ICC values was found for the detection of Grayscale Ultrasound(GSUS) synovitis, but the agreement rate in this region was poor(45.10%～47.80%/0.58～0.74). For the presence or absence of erosions, moderate agreement rate was calculated, however, the ICC values among the three groups were poor(66.70%～77.80%/0.44～0.58). Regarding agreements in the finger joint regions, lower agreement results were found in both of MCP3(61.1%～71.3%) and PIP2/3 joints(57.4%～63.9%), and a variable agreement rates were found for wrist joints (64%～80%). The majority of survey respondents indicated favorable receptivity to the online self-learning APP(75%) including finding it helpful to improve the learning efficiency and interests (91.7%). Furthermore, a more accurate definition about the joint ultrasound score, standardization of image acquisition and adequate dynamic ultrasonography were advised to further improve interobserver agreements. Conclusions The online self-learning APP can be used as an effective tool in joint ultrasound training. A detailed analysis of the assessment results based on the feedback information from the trainees can help to further optimize and improve the teaching process to realize the precision teaching in joint diagnostic ultrasound.

Key words: ultrasonography, joint diagnostic ultrasound, ultrasound score, self-learning, precision teaching

中图分类号:

G643

王铭, 赵辰阳, 韦瑶, 桂阳, 赵瑞娜, 王若蛟, 杨萌. 基于APP线上自主学习模式的关节超声诊断的精准教学探索[J]. 基础医学与临床, 2021, 41(9): 1371-1375.

WANG Ming, ZHAO Chen-yang, WEI Yao, GUI Yang, ZHAO Rui-na, WANG Ruo-jiao, YANG Meng. Evaluation of precision teaching based on APP for online self-learning in joint diagnostic ultrasound[J]. Basic & Clinical Medicine, 2021, 41(9): 1371-1375.

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