Medical Extended Reality in Perioperative Medicine: A Scoping Review of Intervention Development, Feasibility Evaluation, and Translational Readiness
TL;DR
Perioperative MXR shows promising signals of efficacy and feasibility based on reported study outcomes; however, these favorable trends should be interpreted cautiously given possible publication bias and the absence of a formal risk-of-bias assessment.
Abstract
Objective To characterize methodological features, intervention characteristics, and outcome trends of medical extended reality (MXR) applications for perioperative patients. Patients and Methods This scoping review was conducted in accordance with the JBI Manual for Evidence Synthesis. Searches were conducted in January 2025 and updated on August 12, 2025, across MEDLINE, Embase, Scopus, IEEE, Google Scholar, Cochrane Library, arXiv, and ProQuest Dissertations and Theses. Primary studies evaluating immersive MXR interventions in perioperative patients were included. Results Of 5883 records identified, 190 studies published between 2012 and 2026 were included. Most studies involved adult populations (69.5%), used virtual reality (95.8%), and delivered interventions preoperatively, most often targeting anxiety or pain. Studies were predominantly randomized controlled trials evaluating efficacy (48.4%), with few early developmental studies incorporating user-centered design (2.6%). Early-stage feasibility studies (47.9%) showed substantial methodological and outcome heterogeneity, with patient satisfaction (25.3%) and feasibility (18.4%) infrequently prioritized as primary outcomes. Studies commonly evaluated multiple intervention mechanisms, such as distraction and education, within single designs (35.3%), and some delivered interventions across multiple perioperative phases (10.5%). Few studies included MXR comparator conditions (6.8%). Conclusion Perioperative MXR shows promising signals of efficacy and feasibility based on reported study outcomes; however, these favorable trends should be interpreted cautiously given possible publication bias and the absence of a formal risk-of-bias assessment. Limited use of user-centered design, inconsistent and nonvalidated measurement of feasibility outcomes, and mechanistic ambiguity may constrain translation. Greater alignment with staged development frameworks and more rigorous feasibility evaluation are needed to support implementation. Preregistration: https://osf.io/nkwfy/wiki?wiki=yqanp.