There have been several innovative approaches employed in anesthesiology education to improve the experiences of learners and teachers over time. Simulation-based mastery learning, flipped classroom offerings, spaced learning, and multimodal approaches to teaching and feedback have helped elevate education within our specialty (Anesthesiology 2019;131:908-28). The incorporation of online learning and learning management systems, hastened by the COVID-19 pandemic, has changed the landscape of education and paved the way for individualized, competency-based education (Anesth Analg 2021;132:585-93). The ACGME’s Milestone Project, now in its second iteration, continues the march toward a future where education is no longer time-based, but rather individualized and focused on identifying specific learner needs and achievements (Anesth Analg 2021;133:353-61). Furthermore, as we recognize the value of equity and inclusion within education, it has become imperative to provide training opportunities that are comparable for all learners, even as we extend the reach of our training programs globally.

Two pressing needs have emerged amid all this progress:

  1. Better tools to objectively quantify trainee performance.
  2. Provision of educational opportunities that are identical across space and time while remaining adaptable to learner level and needs.

Virtual reality (VR) training represents an exciting new technology that can be applied to education within our specialty. Here, we will briefly define VR and then discuss how it can address both critical needs. We will conclude with some directions for future collaborative work. This is not intended to be a comprehensive review of the technology and specifically does not include the promising field of augmented reality, which is evolving in parallel but is likely to converge in a future state of the technologies.

VR is an immerse technology that creates an entire virtual world that is filmed or computer-generated using 360 degrees content systems. The aim is to create a complete interaction of the projected environment, with the user entirely suppressing the real world (Anesth Analg 2022;135:23-08). VR is a relatively old technology that has played a role in industrial, military, and aviation sectors since the 1970s (J Mol Biol 2019;431:1315-21). Its use has expanded to other fields given its increased affordability and the development and improvement of its necessary parts.

There are two types of VR: one is based on different computer screens to create an immersive field (such as the ones used by professional pilots and car drivers) and one is based on a head mount display that creates a stereoscopic three-dimensional (3D) image by projecting a pair of two-dimensional (2D) images in each lens. These images are projected in the correspondent eye with a slight difference in perspective to create the 3D effect. They also require a frame rate of at least 90 per second and a field of view that varies between 9-210 degrees to increase the immersion feel (Cell Rep Med 2021;2:100348). Additional components are head and eye tracking, headsets, joystick controllers, trackpads, or buttons. All these parts are managed by a computer board that can be integrated into the head mount display itself or on a separate computer connected via cable or wireless, depending on the model being used.

VR enhances skill development and learning by providing an immersive environment for better engagement and learning outcomes, including complex scenario simulations. It offers cost-effectiveness, with shared equipment and flexibility in space and time for collaborative training. Additionally, VR enables customized learning goals with progress tracking and real-time feedback for skill improvement (Anesth Analg 2022;135:230-8; JAMA Netw Open 2020;3:e2031217).

While immersive virtual environments offer realistic simulations, they might not completely mirror the intricacies of real-life situations. Despite technological progress, it remains a challenge to accurately replicate tactile feedback, immediate human interactions, and unforeseeable circumstances in virtual environments (J Plast Reconstr Aesthet Surg 2021;74:2372-8; Med Eng Phys 2016;38:59-71). Given these limitations, it is essential to carefully assess, monitor, and tackle these challenges for their effective incorporation into medical education and health care practices.

VR trainers can be designed to collect performance data and score action steps in real time without the need for human raters (Computers & Education 2020;151:103871). Feedback and evaluation can be provided immediately, at the end of a procedure or event, and across multiple sessions and/or users. Immediate feedback within modules can take several forms across different senses. Auditory feedback in the form of positive or negative sounds can re-enforce or correct behaviors without requiring words. Verbal overlay of specific errors can also be used but can add additional cognitive load. Tactile feedback may be incorporated, as controllers can vibrate in specific ways for correct or incorrect movements, further alerting users to whether they are successfully completing a task. Visual cues to users can include a task list embedded in a scenario or procedure that prompts with green or red flags to indicate success or failure at each step. In some cases, times to completion or other analytics can be displayed in this immediate, “heads up” fashion. At the end of a procedure or task, a report card can be provided to the learner that includes both global performance ratings and specific sub-area performance, complete with quantitative data to support ratings and foster future performance improvement (Figure 1). VR scenarios can be tied into a learning ecosystem where learners and instructors can log in to check “back end” analytics dashboards and performance reporting. These reports can show data from single-user sessions or aggregate data from multiple sessions to highlight performance strengths, weaknesses, and progression over time (Figures 2A, 2B). One other strength is the ability to aggregate data across users for a “big data” approach to curriculum and procedural assessments (Figure 3). This ability to get immediate understanding of curricular or performance issues in an objective, visual way far outstrips laborious aggregation of data from traditional teaching approaches.

Figure 1: Example of analytics displayed at the end of a procedure. A similar, but simplified, display can be provided for the user during the procedure, which serves to remind the user of the steps and shows their performance in real time. Performance bars change dynamically as a portion of the procedure is completed. Color coding (red for fail) and qualitative assessments (“good”) aid in immediate understanding of concepts. Image courtesy of Vantari VR (Seattle, Washington).

Figure 1: Example of analytics displayed at the end of a procedure. A similar, but simplified, display can be provided for the user during the procedure, which serves to remind the user of the steps and shows their performance in real time. Performance bars change dynamically as a portion of the procedure is completed. Color coding (red for fail) and qualitative assessments (“good”) aid in immediate understanding of concepts. Image courtesy of Vantari VR (Seattle, Washington).

Figure 2A: Analytics dashboards can display results of individual steps for a single procedure as below. In this example, the user or instructor can visualize what steps were most time-intensive or not completed successfully. In this example, step 12, removing syringe, was failed nine times and would be worth reviewing with the student to ensure understanding. Results can also be compiled over multiple attempts. Image courtesy of Vantari VR (Seattle, Washington).

Figure 2A: Analytics dashboards can display results of individual steps for a single procedure as below. In this example, the user or instructor can visualize what steps were most time-intensive or not completed successfully. In this example, step 12, removing syringe, was failed nine times and would be worth reviewing with the student to ensure understanding. Results can also be compiled over multiple attempts. Image courtesy of Vantari VR (Seattle, Washington).

Figure 2B: Analytics dashboards can also demonstrate user peformance over time with different graphical displays. Along the top of this example display, best time, success average, and average time are displayed. The middle panel shows graphically both session trends (left) and individual step trends (right) over time to demonstrate skill progression or regression. Session data along the bottom can demonstrate the percentage completion for each session, allowing for quick visualization of progress over time. Image courtesy of Vantari VR (Seattle, Washington).

Figure 2B: Analytics dashboards can also demonstrate user peformance over time with different graphical displays. Along the top of this example display, best time, success average, and average time are displayed. The middle panel shows graphically both session trends (left) and individual step trends (right) over time to demonstrate skill progression or regression. Session data along the bottom can demonstrate the percentage completion for each session, allowing for quick visualization of progress over time. Image courtesy of Vantari VR (Seattle, Washington).

Figure 3: Analytics allow visualization of performance across an entire training cohort. In this example, each row is an individual participant. The blurred first column represents the names of individual course participants. The number of succesful steps is displayed numerically in the second column. Each correct step is in green, with the incorrect step highlighted in red. Red outline filled with green indicates successful remediation, while red filled with white indicates a step failure. Total procedural time is listed to the right. This data can be scanned rapidly to determine which steps are the most difficult and require further teaching. They can also be reviewed for course compliance, as the last two particpants spent less than one minute on the module and two others were not able to successfully complete the module and may require assistance. Image courtesy of Vantari VR (Seattle, Washington).

Figure 3: Analytics allow visualization of performance across an entire training cohort. In this example, each row is an individual participant. The blurred first column represents the names of individual course participants. The number of succesful steps is displayed numerically in the second column. Each correct step is in green, with the incorrect step highlighted in red. Red outline filled with green indicates successful remediation, while red filled with white indicates a step failure. Total procedural time is listed to the right. This data can be scanned rapidly to determine which steps are the most difficult and require further teaching. They can also be reviewed for course compliance, as the last two particpants spent less than one minute on the module and two others were not able to successfully complete the module and may require assistance. Image courtesy of Vantari VR (Seattle, Washington).

In an era where education must take place across distances and times, VR offers an ideal platform for delivering uniform educational experiences for learners. Because virtual modules can be programmed to perform identically for each user, education can take place either synchronously across a range of locations or asynchronously. In addition to evaluations, as presented above, high-quality, formative feedback can also be provided immediately within a virtual experience. Learning assistance can take the form of built-in proctoring/guidance or remote proctoring. Learners can also watch each other perform to provide near peer teaching and feedback; multi-player experiences can also provide performance cues and enhance collaborative learning and a uniform experience, even if not in the same physical location.

VR is a tool uniquely suited to addressing the need for high-quality evaluation and learning experiences regardless of location or time needs. While it has tremendous potential, uptake should be guided by best evidence and demonstration of educational merits. We are committed to conducting rigorous, multidisciplinary, multicenter research to investigate VR. An international multidisciplinary consortium of training programs is coalescing with the aim of inclusively and collaboratively studying this technology in our profession. We believe that our specialty is ideally suited at the intersection of procedural and cognitive disciplines to shape these efforts.

“Feedback and evaluation can be provided immediately, at the end of a procedure or event, and across multiple sessions and/or users. Immediate feedback within modules can take several forms across different senses.”

Issues under investigation include the best approaches to implementation and feasibility of use. We aim to establish use cases and best practices and document the utility of this technology. The study of outcomes, both initial and long term for learners and patients, is an essential consideration for ensuring responsible adoption of this technology. We invite others to join us in this endeavor so that we can advance education in our specialty in a responsible manner.