Utility of mobile learning in Electrocardiography. Issue 2 (22nd February 2021)
- Record Type:
- Journal Article
- Title:
- Utility of mobile learning in Electrocardiography. Issue 2 (22nd February 2021)
- Main Title:
- Utility of mobile learning in Electrocardiography
- Authors:
- Viljoen, Charle André
Millar, Rob Scott
Hoevelmann, Julian
Muller, Elani
Hähnle, Lina
Manning, Kathryn
Naude, Jonathan
Sliwa, Karen
Burch, Vanessa Celeste - Abstract:
- Abstract: Aims: 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. Methods and results: 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%, P = 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%, P < 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 ECGAbstract: Aims: 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. Methods and results: 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%, P = 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%, P < 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, P < 0.001). Mobile learning gains were not sustained after 2 weeks. Conclusion: Whilst mobile learning contributes to increased ECG diagnostic accuracy, the benefits were not sustained over time. Graphical Abstract: … (more)
- Is Part Of:
- European heart journal. Volume 2:Issue 2(2021)
- Journal:
- European heart journal
- Issue:
- Volume 2:Issue 2(2021)
- Issue Display:
- Volume 2, Issue 2 (2021)
- Year:
- 2021
- Volume:
- 2
- Issue:
- 2
- Issue Sort Value:
- 2021-0002-0002-0000
- Page Start:
- 202
- Page End:
- 214
- Publication Date:
- 2021-02-22
- Subjects:
- App -- Electrocardiography -- ECG -- Internet -- Mobile learning -- Medical education
Medical informatics -- Periodicals
Medical technology -- Periodicals
Cardiovascular system -- Periodicals
616.100284 - Journal URLs:
- https://academic.oup.com/ehjdh ↗
- DOI:
- 10.1093/ehjdh/ztab027 ↗
- Languages:
- English
- ISSNs:
- 2634-3916
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 23080.xml