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App-based serious gaming for training of chest tube insertion: study protocol for a randomized controlled trial

Overview of attention for article published in Trials, February 2017
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Title
App-based serious gaming for training of chest tube insertion: study protocol for a randomized controlled trial
Published in
Trials, February 2017
DOI 10.1186/s13063-017-1799-5
Pubmed ID
Authors

Mirco Friedrich, Christian Bergdolt, Patrick Haubruck, Thomas Bruckner, Karl-Friedrich Kowalewski, Beat Peter Müller-Stich, Michael C. Tanner, Felix Nickel

Abstract

Chest tube insertion is a standard intervention for management of various injuries of the thorax. Quick and accurate execution facilitates efficient therapy without further complications. Here, we propose a new training concept comprised of e-learning elements as well as continuous rating using an objective structured assessment of technical skills (OSATS) tool. The study protocol is presented for a randomized trial to evaluate e-learning with app-based serious gaming for chest drain insertion. The proposed randomized trial will be carried out at the Department of Orthopedics and Traumatology at Heidelberg University in the context of regular curricular teaching for medical students (n = 90, 3rd to 6th year). The intervention group will use e-learning with the serious gaming app Touch Surgery (TM) for chest drain insertion, whereas the control group uses serious gaming for an unrelated procedure. Primary endpoint is operative performance of chest drain insertion in a porcine cadaveric model according to OSATS. The randomized trial will help determine the value of e-learning with the serious gaming app Touch Surgery (TM) for chest drain insertion by using the OSATS score. The study will improve surgical training for trauma situations. Trial Registration Number, DRKS00009994 . Registered on 27 May 2016.

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The data shown below were compiled from readership statistics for 157 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 157 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 21 13%
Researcher 17 11%
Student > Ph. D. Student 15 10%
Other 12 8%
Student > Master 12 8%
Other 27 17%
Unknown 53 34%
Readers by discipline Count As %
Medicine and Dentistry 45 29%
Nursing and Health Professions 12 8%
Psychology 10 6%
Social Sciences 6 4%
Agricultural and Biological Sciences 3 2%
Other 20 13%
Unknown 61 39%