Currently accepted at: JMIR XR and Spatial Computing (JMXR)
Date Submitted: Mar 25, 2025
Open Peer Review Period: Apr 11, 2025 - Jun 6, 2025
Date Accepted: Jan 13, 2026
(closed for review but you can still tweet)
This paper has been accepted and is currently in production.
It will appear shortly on 10.2196/72013
The final accepted version (not copyedited yet) is in this tab.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Design, Development, and Usability Evaluation of a Role-Specific Augmented Reality Decision Support System for Cardiac Arrest Resuscitation
ABSTRACT
Background:
Cardiopulmonary arrest is a critical medical emergency that requires adherence to specific clinical guidelines to ensure optimal outcomes. Deviations from these guidelines, often due to task complexity, can negatively impact patient outcomes. Augmented reality (AR) has the potential for supporting resuscitation teams by providing real-time, role-specific decision support to improve adherence to clinical guidelines.
Objective:
This study aims to design, develop and evaluate a role-specific AR decision support system tailored for resuscitation team leaders and medication nurses. Our primary objective is to assess usability, user experience, and technology acceptance, determining the system's feasibility in a simulated clinical setting.
Methods:
We designed and refined the AR system using a 4-step iterative prototyping development approach, integrating feedback from domain experts. The system was tested in a simulated clinical environment with 10 experienced emergency healthcare professionals (5 physician team leaders and 5 medication nurses). Post-simulation surveys assessed usability, user experience, and technology acceptance.
Results:
The results revealed high usability, user experience, and technology acceptance for the role-specific AR decision support system, with favorable ratings from healthcare professionals. The team leader and medication nurse roles both received “above average” scores in usability, with the medication nurse role rated “excellent.” User experience metrics showed positive outcomes in attractiveness, pragmatic quality, and hedonic quality, indicating that users found the system both functional and engaging. High scores in perceived usefulness and ease of use suggest strong acceptance, underscoring the system's potential to improve clinical protocol adherence during cardiopulmonary arrest.
Conclusions:
The role-specific AR decision support system for resuscitation teams demonstrates strong feasibility and operational acceptance, suggesting its potential to improve adherence to guidelines during cardiopulmonary arrest.
Citation
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.