ArticleJMIR human factors2026
Overview of a User-Centered, Mixed-Methods Process for Designing Interconnected and Focused Mobile Applications on Patient Care Environment (InterFACE): Augmented-Reality Decision Support System for Pediatric Resuscitation.
Article in JMIR human factors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Augmented Reality-Guided Decision Support in Simulated Pediatric Cardiac Arrest: A Randomized Clinical Trial.JAMA network open · 2026Trial
- Distribution of visual attention amongst clinicians using an augmented reality-based decision support system during simulated cardiac arrest - A descriptive study.Resuscitation plus · 2026Article
- Evaluating a Shared Decision Support Tool for Pediatric Cardiopulmonary Arrest: Mixed Methods Usability Study.JMIR human factors · 2026Article
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Pediatric cardiopulmonary resuscitation (CPR) is a highly complex and time-critical process that demands precise team coordination and strict adherence to pediatric advanced life support (PALS) guidelines. In real-world practice, adherence often deteriorates due to cognitive overload, fragmented communication, and disruption of information flow under stress. Although digital cognitive aids have shown potential to improve adherence, existing tools are often limited to single tasks, lack team-wide integration, or fail to adapt in real time to dynamic clinical environments. Objective: This study aimed to design and evaluate InterFACE (Interconnected and Focused Mobile Applications on Patient Care Environment), an integrated, augmented reality (AR)-enabled digital health system developed to support real-time PALS adherence and enhance team coordination during pediatric resuscitation. Methods: A structured, mixed methods, user-centered design process was used. Persona development and spatial analysis characterized the needs and positions of key resuscitation roles. A 3-round Delphi process with experts identified critical information elements for display. Iterative user experience (UX) prototyping was performed, followed by simulation-based evaluations of three system components: (1) TeamScreen, a wall-mounted team display providing a shared overview of the resuscitation process; (2) Guiding Pad (developed by Pierre Louis Rebours and Marc Ibrahim), a tablet-based app for documentation and algorithm navigation; and (3) AR head-mounted displays (HMDs) for team leaders and medication nurses, delivering role-specific, context-aware guidance. Usability was assessed with standardized instruments, including the System Usability Scale (SUS), Technology Acceptance Model (TAM), and User Experience Questionnaire (UEQ). Results: The Delphi study achieved consensus on 20 core information elements, distributed across the 3 interfaces. Usability testing demonstrated high acceptance across all modalities. The Guiding Pad supported effective navigation of resuscitation algorithms with a 78%-100% task completion rate. The TeamScreen achieved an overall task success rate of 81%, improving situational awareness despite some confusion in high-density regions. AR HMDs received favorable evaluations, with SUS scores rated "Good" to "Excellent," and UEQ ratings indicating high intuitiveness, stimulation, and attractiveness. Participants consistently described InterFACE as intuitive, useful for real-time decision-making, and supportive of team synchronization. Reported challenges included interface complexity, incomplete integration with patient monitors, and potential cognitive load from simultaneous information streams. Conclusions: InterFACE represents a significant advancement in digital cognitive aids by combining shared displays, tablets, and AR guidance into a synchronized, role-specific ecosystem. The system shows promise in enhancing adherence to PALS, reducing cognitive load, and improving team coordination in simulated pediatric resuscitations. While results demonstrate strong usability and acceptance, further research is needed to evaluate clinical effectiveness in real-world settings, including randomized controlled trials, integration with hospital information systems via Fast Healthcare Interoperability Resources (FHIR) standards, and potential artificial intelligence-driven decision support to optimize adaptability and long-term skill retention.
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