SEPSIS COLLAB: A Virtual Reality Training Simulation For Sepsis Treatment

Williams-Bhatti, Ayesha and Carruthers, D and Wilson, Andrew (2023) SEPSIS COLLAB: A Virtual Reality Training Simulation For Sepsis Treatment. In: IEEE VR 2023 - 2nd Workshop on XR for Healthcare and Wellbeing - (XR Health) 2023, 25th - 29th March 2023, Shanghai (Online).

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Abstract

Sepsis is a main cause of death, by infection in the world. Despite modern treatments, mortality and morbidity could be reduced by improved training of the clinical teams. SEPSIS COLLAB (developed using Unity game engine and C# programming language for Meta Quest 2) is a unique virtual reality simulation for training both doctors and nurses to treat sepsis. It was evaluated with the help of 110 volunteers, in terms of usability (System Usability Scale) and knowledge acquisition. The latter used pre-/post-tests based on clinical treatment guidelines. Participants were divided into a control group (doctors n:35 and nurses n:20) who did not use SEPSIS COLLAB and a test group (doctors n:35 and nurses n:20) who did. The consensus regarding the usability of SEPSIS COLLAB was rated as excellent. Analysis showed significant improvement in the post-test results of the test group compared to their pre-test. There was no significant difference in the pre- or post-test scores of the control group. The test group performed significantly better in the post-test than the control group. These findings show SEPSIS COLLAB has potential to provide positive educational benefits to medical teams in their treatment of sepsis and act as a complement to traditional in-person training.

Item Type:	Conference or Workshop Item (Paper)
Identification Number:	https://doi.org/10.1109/VRW58643.2023.00033
Dates:	Date Event 21 January 2023 Accepted 1 May 2023 Published Online
Uncontrolled Keywords:	Training, Solid modeling, Three-dimensional displays, Hospitals, Knowledge acquisition, Virtual reality, User interfaces
Subjects:	CAH00 - multidisciplinary > CAH00-00 - multidisciplinary > CAH00-00-00 - multidisciplinary CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science CAH11 - computing > CAH11-01 - computing > CAH11-01-06 - computer games and animation CAH11 - computing > CAH11-01 - computing > CAH11-01-08 - others in computing CAH22 - education and teaching > CAH22-01 - education and teaching > CAH22-01-01 - education
Divisions:	Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Depositing User:	Ayesha Williams-Bhatti
Date Deposited:	06 Mar 2023 14:34
Last Modified:	09 May 2023 15:01
URI:	https://www.open-access.bcu.ac.uk/id/eprint/14224

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