The application of blended learning in basic life support training for retraining

doi:10.3760/cma.j.cn115259-20230804-00088

Abstract

Abstract: Objective To explore the application effects of blended learning inbasic life support training for retraining trainees. Methods An experimental control method was used. A total of522 retraining trainees from East Hospital Affiliated to Tongji University who participated in the basic life support training were selected as the subjects, all of whom were hospital physicians. 265 retraining trainees who participated in the training from March to April 2023 were set as the experimental group, using blended learning mode; and 257 retraining trainees who participated in the training from March to April 2021 were set as the control groupusing blended learning mode. The teaching effectiveness were evaluated through the skill assessments of two groups of trainees and a questionnaire survey of trainees participating in blended learning mode. χ²-test and t-test were used for data analysis. Results The first-time pass rate of skill assessment among the experimental group trainees was higher than that of the control group trainees [90.6% (240/265) vs. 84.4% (217/257)](P=0.034). The survey results showed that the average score of the experimental group's liking for using blended learning mode for retraining was (4.73±0.64) points, and the average score of confidence in using basic life support in practice after receiving the course was (4.78±0.62) points. In addition, 96.6% (256/265) of the experimental group believed that adopting a blended teaching mode would facilitate more flexible learning, while 95.5% (253/265) believed that it would help to systematically master basic life support knowledge and skills. Conclusions The blended learning mode helps to improve the retraining trainees' pass rate of skills assessments in the training of basic life support. It has the advantage of allowing students to learn more flexibly and systematically to master knowledge and skills, and to enhances their confidence in using basic life support skills.

Key words: Basic life support, Blended teaching, Retraining, Cardiopulmonary resuscitation

CLC Number:

Ma Ruolin, Gu Haojie, Liu Shengjun, Shan Qiyuan, Chen Chi, Sun Xiaoliang, Kang Baoli, Xu Wei, Ding Min. The application of blended learning in basic life support training for retraining[J]. Chinese Journal of Medical Education, 2024, 44(8): 611-614, DOI: 10.3760/cma.j.cn115259-20230804-00088.

References

[1] Merchant RM, Topjian AA, Panchal AR, et al. Part 1: Executive summary: 2020 American Heart Association guidelines for cardiopulmonary resuscitation and emergency cardiovascular care[J]. Circulation, 2020,142(16suppl2):S337-S357. DOI: 10.1161/CIR.0000000000000918.
[2] 马红梅, 陈湘玉, 文秀, 等. 高质量心肺复苏培训对提高医务人员基础生命支持精准性的效果评价[J].中国急救复苏与灾害医学杂志,2019,14(5):415-418. DOI: 10.3969/j.issn.1673-6966.2019.05.006.
[3] 郑康, 李辉, 马青变. 借鉴美国心脏协会基础生命支持课程推进我国医务人员的心肺复苏培训[J].中华医学教育杂志,2021,41(11):1046-1049. DOI: 10.3760/cma.j.cn115259-20210513-00633.
[4] 李崎, 林静, 刘进, 等. 集体反馈方法对医学生基本生命支持技能学习的影响[J].中华医学教育杂志,2012,32(6):909-911,931. DOI: 10.3760/cma.j.issn.1673-677X.2012.06.035.
[5] Ko YC, Lin HY, Chiang WC, et al. Comparing the effects of blended learning and traditional instruction on basic life support for laypersons: a randomized controlled trial[J]. J Formos Med Assoc, 2023,S0929-6646(23):435-437. DOI: 10.1016/j.jfma.2023.10.017.
[6] Abuejheisheh AJ, Alshraideh JA, Amro N, et al. Effectiveness of blended learning basic life support module on knowledge and skills: a systematic review of randomized controlled trials[J]. Heliyon, 2023,9(11):e21680. DOI: 10.1016/j.heliyon.2023.e21680.
[7] 苏成磊, 陈可, 仲轶, 等. 线上线下混合模式在本科生心肺复苏教学中的效果评价[J].中国急救复苏与灾害医学杂志,2023,18(2):261-263. DOI: 10.3969/j.issn.1673-6966.2023.02.031.
[8] 高连娣, 高思杰, 袁旭, 等. 基于信息化培训平台的视频教学方式在提高新入职护士心肺复苏质量中的效果评价[J].中国实用护理杂志,2021,37(33):2617-2622. DOI: 10.3760/cma.j.cn211501-20200928-04036.

[1]	Wang Qian, Yin Ling, Yu Yang, Yu Yonghao, Xie Keliang, Li Qing. Comparison of the effects of two simulation scenarios in advanced cardiac life support training for pre-clinical anesthesia [J]. Chinese Journal of Medical Education, 2026, 46(5): 337-342.
[2]	Wang Chunxia, Chen Yu, Xu Liyuan, Wei Guihua, Xu Qinrong, Xu Tingting, Li Zhangping. Application of virtual simulation scenario-based training in pre-hospital emergency care training for medical students [J]. Chinese Journal of Medical Education, 2026, 46(2): 112-117.
[3]	Sun Yujie, Yang Tingting, Zhang Yang. Application of practical learning method based on shared mental model theory in CPR training [J]. Chinese Journal of Medical Education, 2025, 45(8): 606-609.
[4]	Sun Yumei, Zhou Qiang, Ji Xuan, Zhao Guodong. Study on learning outcomes and its influencing factors in the blended courses based on the community of inquiry framework [J]. Chinese Journal of Medical Education, 2025, 45(6): 408-413.
[5]	Zhang Wenlong, Yuan Wei, Chen Wen, Gu Jing, Lai Yingsi. Design and practice of blended learning in advanced mathematics and linear algebra for graduate students majoring in epidemiology and health statistics [J]. Chinese Journal of Medical Education, 2025, 45(2): 141-145.
[6]	Ou Peng, Gong Cai, Liu Shiping, Tang Hanfen, Huang Fansu, Liu Shuang , Yuan Ting. Application of blended learning method in the teaching of clinical nutrition for resident physicians [J]. Chinese Journal of Medical Education, 2024, 44(8): 624-628.
[7]	Zheng Kang, Gao Yang, Liu Chen, Li Shu, Tian Ci, Ma Li, Ma Qingbian. Investigation of mixed-view standardized video for cardiopulmonary resuscitation training [J]. Chinese Journal of Medical Education, 2024, 44(6): 431-435.
[8]	Jiang Hui, Song Xiao, Zong Liang, Zhu Huadong, Liu Jihai, Shi Di. Resuscitation quality improvement program to improve the acquisition and retention of cardiopulmonary resuscitation skills for healthcare professionals in emergency department [J]. Chinese Journal of Medical Education, 2024, 44(12): 943-947.
[9]	Du Tian, Du Zefeng, Li Xiaoxian, Lin Min, Liu Zhuowei, Huang Wan, Li Tang. Research on video feedback teaching combined with peer-assisted learning to improve residents' cardiopulmonary resuscitation skills in short-term simulation training [J]. Chinese Journal of Medical Education, 2024, 44(11): 869-875.
[10]	Zhan Heqing, Yu Yuanbo, Han Huirui, Chen Yanying. Application of teaching strategies adjusting to learning styles of medical undergraduates in medical informatics course [J]. Chinese Journal of Medical Education, 2024, 44(10): 761-766.
[11]	Liu Chang, Li Guangpu, Chen Menghuan, Wang Peisong, Liu Dongwei, Li Shengyun. A deep learning based artificial intelligence real-time training and assessment system for cardiopulmonary resuscitation [J]. Chinese Journal of Medical Education, 2023, 43(6): 418-422.
[12]	Liu Yujing, Shen Qin, Xu Yu. Bibliometrics analysis of blended teaching in nursing education field based on Web of Science [J]. Chinese Journal of Medical Education, 2023, 43(5): 356-360.
[13]	ZuMuReTi·Yimin, Guo Yan, Wang Minnan, ReNa·Maimaiti. Application of the flipped classroom blended teaching method based on SPOC in the child health care course [J]. Chinese Journal of Medical Education, 2023, 43(2): 123-126.
[14]	Deng Kang, Lu Yaping, Sun Xinhua, Liu Mingjuan, Liu Jinzhi, Li Jie, Zhou Qinghe. Application of flipped classroom based on peer assisted learning in basic life support course for interns of clinical medicine [J]. Chinese Journal of Medical Education, 2023, 43(12): 925-928.
[15]	Qi Qianrong, Zhou Hanjing, Wu Debin, Wang Yaqin, Zhang Yi, Xie Qingzhen. Exploration and reflection on the application of blended teaching mode based on simulation laboratory in reproductive medicine teaching [J]. Chinese Journal of Medical Education, 2023, 43(10): 769-773.