Translational Extended Reality in Healthcare: From Clinical Validation to Real-World Implementation

Extended Reality (XR) technologies, including Virtual Reality, Augmented Reality, and Mixed Reality, are increasingly being evaluated and deployed across healthcare settings, from specialty clinics and rehabilitation programmes to home-based care. Emerging applications span mental health interventions, remote and emergency care delivery, patient and clinician education, digital twin-based treatment planning, and neurorehabilitation and motor recovery. In this Research Topic, translational XR refers to work that advances immersive technologies along the pathway from technical feasibility and laboratory validation towards clinically meaningful, scalable, and sustainable use in real-world healthcare. This includes the generation of robust evidence, integration into clinical workflows, and evaluation of outcomes for patients, clinicians, and healthcare systems.Through a curated collection of original research articles, systematic reviews, and critical perspectives, this Research Topic brings together researchers, industry experts, clinicians, and implementation scientists working across the spectrum of translational XR in healthcare. The collection welcomes research that examines how XR applications move beyond proof of concept towards clinical validation, implementation, and routine use. Contributions may address mental health, remote care delivery, clinician and patient education, digital twins, neurorehabilitation, and other healthcare applications, provided they engage with the clinical, technical, organisational, or implementation challenges involved in translation. The central question is no longer simply whether XR can produce compelling clinical experiences, but whether those experiences can become safe, evidence-based, accessible, interoperable, and sustainable components of routine healthcare.At the same time, we welcome work that critically evaluates clinical validation methodologies and implementation science approaches for XR. Relevant translational barriers include clinical workflow integration, clinician training and competency, interoperability with health systems and electronic health records, reimbursement and health economics, technical maintenance and versioning, implementation fidelity, patient engagement and long-term adherence, equity and cultural adaptation, regulatory pathways, accessibility, data privacy, and patient autonomy. Particular attention is encouraged for the evidence standards required to assess AI-enabled XR systems, including transparency, reliability, safety, generalisability, and the effects of algorithmic bias. Research should also consider how healthcare organisations can adopt, maintain, evaluate, and scale XR interventions across diverse clinical and community settings.By assembling this work, the Research Topic aims to foster interdisciplinary dialogue between human-computer interaction, clinical medicine, rehabilitation science, neuroscience, health services research, and implementation science. Accepted articles will form a structured, citable reference point for the field. They will synthesise current evidence, identify the conditions required for successful implementation, highlight open research questions, and propose a forward-looking agenda to accelerate the responsible adoption of XR technologies across real-world healthcare environments.Topics of interest for submission include, but are not limited to: • Clinical care and remote health: XR for acute interventions, emergency medicine, telehealth, home-based disease management, and care pathways that connect clinical and community settings. • Mental health and wellbeing: immersive applications for psychological therapy, stress reduction, behavioural support, and cognitive assistance, with attention to clinical validation, engagement, and long-term outcomes. • Rehabilitation and supportive care: translational XR in neurorehabilitation, motor recovery, chronic disease management, pain management, and assistive tools for daily living. • Training and education: XR platforms for medical and clinical staff training, procedural simulation, competency assessment, patient education, and health literacy. • Advanced system design: digital twins, wearable sensor integration, multimodal interaction, adaptive systems, and AI-driven personalisation in healthcare environments. • Clinical validation and implementation science: trial design, real-world evaluation, implementation frameworks, workflow integration, implementation fidelity, adoption, scalability, sustainability, and health services research. • Translation, ethics, and governance: regulatory pathways, interoperability with electronic health records and health systems, reimbursement, health economics, technical maintenance, data privacy, patient autonomy, equity, cultural adaptation, and evidence standards for AI-enabled XR.This collection welcomes Original Research, Systematic Reviews, Mini Reviews, Perspectives, and Technology and Code articles. Topic editors: Federico Manuri, Aikaterini Bourazeri Source: https://www.frontiersin.org/research-topics/86408/translational-extended-reality-in-healthcare-from-clinical-validation-to-real-world-implementation