Viljoen Charle André, Millar Rob Scott, Hoevelmann Julian, Muller Elani, Hähnle Lina, Manning Kathryn, Naude Jonathan, Sliwa Karen, Burch Vanessa Celeste
Division of Cardiology, New Main Building, Groote Schuur Hospital, University of Cape Town, Anzio Road, Observatory 7925, Cape Town, South Africa.
Department of Medicine, Old Main Building, Groote Schuur Hospital, University of Cape Town, Anzio Road, Observatory 7925, Cape Town, South Africa.
Eur Heart J Digit Health. 2021 Feb 22;2(2):202-214. doi: 10.1093/ehjdh/ztab027. eCollection 2021 Jun.
Mobile learning is attributed to the acquisition of knowledge derived from accessing information on a mobile device. Although increasingly implemented in medical education, research on its utility in Electrocardiography remains sparse. In this study, we explored the effect of mobile learning on the accuracy of electrocardiogram (ECG) analysis and interpretation.
The study comprised 181 participants (77 fourth- and 69 sixth-year medical students, and 35 residents). Participants were randomized to analyse ECGs with a mobile learning strategy [either searching the Internet or using an ECG reference application (app)] or not. For each ECG, they provided their initial diagnosis, key supporting features, and final diagnosis consecutively. Two weeks later, they analysed the same ECGs, without access to any mobile device. ECG interpretation was more accurate when participants used the ECG app (56%), as compared to searching the Internet (50.3%) or neither (43.5%, =0.001). Importantly, mobile learning supported participants in revising their initial incorrect ECG diagnosis (ECG app 18.7%, Internet search 13.6%, no mobile device 8.4%, <0.001). However, whilst this was true for students, there was no significant difference amongst residents. Internet searches were only useful if participants identified the correct ECG features. The app was beneficial when participants searched by ECG features, but not by diagnosis. Using the ECG reference app required less time than searching the Internet (7:44 ± 4:13 vs. 9:14 ± 4:34, < 0.001). Mobile learning gains were not sustained after 2 weeks.
Whilst mobile learning contributes to increased ECG diagnostic accuracy, the benefits were not sustained over time.
移动学习有助于通过在移动设备上获取信息来获取知识。尽管移动学习在医学教育中的应用越来越广泛,但关于其在心电图方面效用的研究仍然很少。在本研究中,我们探讨了移动学习对心电图(ECG)分析和解读准确性的影响。
该研究包括181名参与者(77名四年级和69名六年级医学生以及35名住院医师)。参与者被随机分为采用移动学习策略(搜索互联网或使用心电图参考应用程序(应用))分析心电图或不采用该策略。对于每一份心电图,他们依次提供初始诊断、关键支持特征和最终诊断。两周后,他们在无法使用任何移动设备的情况下分析相同的心电图。与搜索互联网(50.3%)或不使用移动设备(43.5%,P=0.001)相比,参与者使用心电图应用程序时心电图解读的准确性更高(56%)。重要的是,移动学习有助于参与者修正其最初错误的心电图诊断(心电图应用程序组为18.7%,互联网搜索组为13.6%,无移动设备组为8.4%,P<0.001)。然而,虽然学生群体是这样,但住院医师之间没有显著差异。只有当参与者识别出正确的心电图特征时,互联网搜索才有用。当参与者按心电图特征搜索时应用程序有益,但按诊断搜索则不然。使用心电图参考应用程序比搜索互联网所需时间更少(7:44±4:13对9:14±4:34,P<0.001)。两周后移动学习的效果未能持续。
虽然移动学习有助于提高心电图诊断准确性,但随着时间推移这些益处未能持续。