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DOI: 10.1055/s-0042-1757334
Emergence of Online Teaching for Plastic Surgery and the Quest for Best Virtual Conferencing Platform: A Comparative Cohort Study
Funding None.

Abstract
Background As the coronavirus disease 2019 virus made its way throughout the world, there was a complete overhaul of our day-to-day personal and professional lives. All aspects of health care were affected including academics. During the pandemic, teaching opportunities for resident training were drastically reduced. Consequently, medical universities in many parts across the globe implemented online learning, in which students are taught remotely and via digital platforms. Given these developments, evaluating the existing mode of teaching via digital platforms as well as incorporation of new models is critical to improve and implement.
Methods We reviewed different online learning platforms used to continue regular academic teaching of the plastic surgery residency curriculum. This study compares the four popular Web conferencing platforms used for online learning and evaluated their suitability for providing plastic surgery education.
Results In this study with a response rate of 59.9%, we found a 64% agreement rate to online classes being more convenient than normal classroom teaching.
Conclusion Zoom was the most user-friendly, with a simple and intuitive interface that was ideal for online instruction. With a better understanding of factors related to online teaching and learning, we will be able to deliver quality education in residency programs in the future.
Keywords
residency training - online learning - e-learning - plastic surgery - online platform - Zoom - COVID-19Author Contributions
S.D. and R.T. conceptualized the study design and methodology. S.D. and A.S. have done literature search and drafting of manuscript. R.T. and M.S. have provided inputs, revised and edited the manuscript.
Publication History
Received: 16 April 2022
Accepted: 11 August 2022
Article published online:
01 February 2023
© 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)
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