OBJECTIVE:To develop anesthesiology residents' proficiency in ultrasound for managing hemodynamically unstable patients using an augmented reality-aided multimodal competency-based curriculum (rescue ultrasound [RUS] curriculum). DESIGN:This prospective study used a quasi-experimental design, involving a nonrandomized, pre-post intervention assessment of the novel competency-based RUS curriculum. SETTING:This study was conducted at a university hospital. PARTICIPANTS:This single-center prospective study involved 10 attending anesthesiologists for baseline ultrasound data, 8 residents completing traditional training, and 15 residents completing the novel RUS curriculum. INTERVENTIONS:This study enrolled third-year categorical anesthesia (CA-3) residents to evaluate the impact of a novel RUS curriculum. Competency benchmarks were defined using objective performance metrics derived from motion metrics data, with expert results as a reference. The study utilized task trainers and augmented reality (HoloLens) to teach RUS skills, and clinical transferability of the curriculum's impact was evaluated through a standardized scenario with a simulated hemodynamically unstable patient. The time taken to request ultrasound was compared between the RUS-trained residents and the non-RUS-trained residents using the Mann-Whitney U test. MEASUREMENT AND RESULTS:Curriculum-trained residents averaged 72.3 seconds (standard deviation = 23.2) for ultrasound calls, compared with 294.9 seconds (standard deviation = 110.6) for nontrained residents. The motion metrics-derived data (path length, acceleration, and time) of curriculum-trained residents were comparable with those of experts. CONCLUSION:An augmented reality-aided multimodal RUS curriculum was developed as a training modality. After completion of training, residents integrated ultrasound into clinical practice at an earlier stage of hemodynamic instability and developed RUS skills that were comparable with experts' performance.

Inspired by recent advances in digital fabrication, artists and scientists have demonstrated that physical data encodings (i.e., data physicalizations) can increase engagement with data, foster collaboration, and in some cases, improve data legibility and analysis relative to digital alternatives. However, prior empirical studies have only investigated abstract data encoded in physical form (e.g., laser cut bar charts) and not continuously sampled spatial data fields relevant to climate and medical science (e.g., heights, temperatures, densities, and velocities sampled on a spatial grid). This paper presents the design and results of the first study to characterize human performance in 3D spatial data analysis tasks across analogous physical and digital visualizations. Participants analyzed continuous spatial elevation data with three visualization modalities: (1) 2D digital visualization; (2) perspective-tracked, stereoscopic “fishtank” virtual reality; and (3) 3D printed data physicalization. Their tasks included tracing paths downhill, looking up spatial locations and comparing their relative heights, and identifying and reporting the minimum and maximum heights within certain spatial regions. As hypothesized, in most cases, participants performed the tasks just as well or better in the physical modality (based on time and error metrics). Additional results include an analysis of open-ended feedback from participants and discussion of implications for further research on the value of data physicalization. All data and supplemental materials are available at https://osf.io/7xdq4/.

IntroductionEndotracheal intubation (ETI) is a procedure that varies in difficulty because of patient characteristics and clinical conditions. Existing physical simulators do not encompass these variations. The Virtual Airway Skills Trainer for Endotracheal Intubation (VAST-ETI) was developed to provide different patient characteristics and high-fidelity haptic feedback to improve training. MethodsWe demonstrate the effectiveness of VAST-ETI as a training and evaluation tool for ETI. Construct validation was evaluated by scoring the performance of experts (N = 15) and novices (N = 15) on the simulator to ensure its ability to distinguish technical proficiency. Convergent and predictive validity were evaluated by performing a learning curve study, in which a group of novices (N = 7) were trained for 2 weeks using VAST-ETI and then compared with a control group (N = 9). ResultsThe VAST-ETI was able to distinguish between expert and novice based on mean simulator scores (t[88] = -6.61, P < 0.0005). When used during repeated practice, individuals demonstrated a significant increase in their score on VAST-ETI over the learning period (F[11,220] = 7206, P < 0.001); however when compared with a control group, there was not a significant interaction effect on the simulator score. There was a significant difference between the simulator-trained and control groups (t[12.85] = -2.258, P = 0.042) when tested in the operating room. ConclusionsOur results demonstrate the effectiveness of virtual simulation with haptic feedback for assessing performance and training of ETI. The simulator was not able to differentiate performance between more experienced trainees and experts because of limits in simulator difficulty.

OBJECTIVE:To describe the development and implementation of a comprehensive in situ simulation-based curriculum for anesthesia residents. DESIGN:This is a prospective study. SETTING:This study was conducted at a university hospital. PARTICIPANTS:This single-center prospective study included all 53 anesthesia residents enrolled in the anesthesia residency program. INTERVENTIONS:Introduction of a routine, high-fidelity, in situ simulation program that incorporates short sessions to train residents in the necessary skill sets and decision-making processes required in the operating room. MEASUREMENTS AND MAIN RESULTS:Our team conducted 182 individual 15-minute simulation sessions over 3 months during regular working hours. All 53 residents in our program actively participated in the simulations. Most residents engaged in at least 3 sessions, with an average participation rate of 3.4 per resident (range, 1-6 sessions). Residents completed an online anonymous survey, with a response rate of 71.7% (38 of 53 residents) over the 3-month period. The survey aimed to assess their overall impression and perceived contribution of this project to their training. CONCLUSIONS:Our proposed teaching method can bridge the gap in resident training and enhance their critical reasoning to manage diverse clinical situations they may not experience during their residency.

OBJECTIVES:This study assess the feasibility of integrating virtual reality (VR) simulation into the central venous catheter (CVC) placement training curriculum. DESIGN:The study consists of 3 parts: (1) Evaluating current manikin-based training for CVC placement through surveys for senior first-year anesthesia residents and cardiac anesthesia faculty who supervise resident performing the procedure; (2) Interventional study training novice trainees with VR simulator and assessing their reaction satisfaction; and (3) pilot study integrating VR training sessions into CVC training curriculum for first-year anesthesia residents. SETTING:Conducted at a single academic-affiliated medical center from December 2022 to August 2023. PARTICIPANTS:Junior first-year anesthesia residents. INTERVENTIONS:VR training sessions for CVC placements using the Vantari VR system. MEASUREMENTS AND MAIN RESULTS:Primary outcome: novice trainees' satisfaction with VR training for CVC procedure. Satisfaction of resident and faculty with standard manikin-based training was also collected. Faculty expressed concerns about residents' confidence and perceived knowledge in performing CVC placement independently. Novice trainees showed high satisfaction and perceived usefulness with VR training, particularly in understanding procedural steps and developing spatial awareness. Pilot integration of VR training into the curriculum demonstrated comparable training times and emphasized structured stepwise training modules to ensure completion of vital procedural steps. CONCLUSIONS:This study underscores the potential of VR simulation as a complementary training tool for CVC placement rather than a substitution of standard manikin training. VR is offering immersive experiences and addressing limitations of traditional manikin-based training methods. The integration of VR into training curricula warrants further exploration to optimize procedural proficiency and patient safety in clinical practice.

Ensuring healthcare workers properly don and doff personal protective equipment is crucial in preventing the spread of contaminants. This study introduces a virtual reality (VR) simulator to enhance training in donning and doffing, aiming to complement or serve as an alternative to conventional methods. The VR simulation incorporates advanced features such as microfacet bidirectional reflective distribution, full-body avatar animations with inverse kinematics, and cloth simulation with Extended Position-Based Dynamics for increased immersion. Performance tests demonstrate real-time functionality even on low-end setups, with high-end systems consistently supporting 120Hz. A user study with 43 participants reveals that the VR group outperformed the non- VR group by 26.88% in donning and 26.16% in doffing tasks, with statistically significant results. Experienced VR users within the group exhibited notable advantages in various metrics. Overall, participants rated the VR simulation as effective (4.47) and realistic (4.13) on a five-point scale.

New artificial intelligence tools have been developed that have implications for medical usage. Large language models (LLMs), such as the widely used ChatGPT developed by OpenAI, have not been explored in the context of anesthesiology education. Understanding the reliability of various publicly available LLMs for medical specialties could offer insight into their understanding of the physiology, pharmacology, and practical applications of anesthesiology. An exploratory prospective review was conducted using 3 commercially available LLMs--OpenAI's ChatGPT GPT-3.5 version (GPT-3.5), OpenAI's ChatGPT GPT-4 (GPT-4), and Google's Bard--on questions from a widely used anesthesia board examination review book. Of the 884 eligible questions, the overall correct answer rates were 47.9% for GPT-3.5, 69.4% for GPT-4, and 45.2% for Bard. GPT-4 exhibited significantly higher performance than both GPT-3.5 and Bard (p = 0.001 and p < 0.001, respectively). None of the LLMs met the criteria required to secure American Board of Anesthesiology certification, according to the 70% passing score approximation. GPT-4 significantly outperformed GPT-3.5 and Bard in terms of overall performance, but lacked consistency in providing explanations that aligned with scientific and medical consensus. Although GPT-4 shows promise, current LLMs are not sufficiently advanced to answer anesthesiology board examination questions with passing success. Further iterations and domain-specific training may enhance their utility in medical education.

Purpose Hierarchy is often cited as a cause of health care team failure; however, there are no validated measures of team hierarchy. Research on group processes in sociology provides a theoretical framework—status characteristics and expectation states (SCES)—that explains the mechanisms that produce the observable power and prestige order (status hierarchy) of the team. The authors use this formal theoretical framework to gather evidence of validity by adapting the method to measure the status hierarchy of medical teams. Method In this retrospective, secondary analysis, the authors analyzed archived videorecorded training exercises conducted between 2007 and 2010 of mixed-gender health care teams of first-year residents and nurses engaged in simulated, complex decision-making scenarios. Analyses were conducted in 2013 with data reanalyzed in July 2022. By adapting the SCES framework for the unique features of academic health care, they developed and refined a coding method from videos and transcripts. To examine validity, they consider the content, response process, internal structure, relation to other variables, and consequences of the framework. Results Having established an acceptable level of coding reliability for key variables for videos and transcripts, the authors demonstrate relation to other variables, specifically detailing how the coding scheme delineates 2 status characteristics—occupation and gender. The mean numbers of statement types by gender and occupation were largely as predicted. Directives, question directives, patient work, and knowledge claims were more likely to be coded during video than transcript coding, whereas questions, statements of fact, and compliance were more likely to be coded during transcript than video coding. However, the relative rates of each statement type by status remained largely consistent among the coding methods. Conclusions This study provides important insight into the mechanisms by which hierarchy impacts team decision making and develops the necessary framework and measurement tool to perform larger studies.

This article discusses an intelligent immersive virtual operating room to enable teams to train in a distributed fashion wearing head-mounted displays.

The ability to provide realistic haptic feedback is indispensable for virtual-reality (VR) based endoscopic colorectal surgery simulators. Despite its importance, force feedback is commonly simulated by simplified approximations with parameters manually tuned in preliminary evaluations due to the complexity of the dynamics of haptic interaction in colonoscopy interventions. Endoscopic submucosal dissection (ESD) is a particularly challenging intervention that requires advanced manual skills for endoscopic control. This work proposes a mechanical impedance model for haptic interactions in ESD formulated via an experimental methodology applied to endoscopic colorectal interventions in general. The developed model is shown to capture the variations in the interaction force during two operations performed at distinct locations on a porcine sample. Salient cues in the recorded haptic interaction data are presented, and changes in the impedance characteristics of the tool-tissue interaction between the steps of the operation are analyzed.

Distractions during surgical procedures are associated with team inefficiency and medical error. Little is published about the healthcare provider’s perception of distraction and its adverse impact in the operating room. We aim to explore the perception of the operating room team on multiple distractions during surgical procedures. A 26-question survey was administered to surgeons, anesthesia team members, nurses, and scrub technicians at our institution. Respondents were asked to identify and rank multiple distractions and indicate how each distraction might affect the flow of surgery. There was 160 responders for a response rate of 19.18

Collaborative virtual environments are being used in various applications ranging from online games to complex team training scenarios. The key to the success of such environments is the ability of the participants to form a shared mental model of the collaborative task being performed. Poor quality of service can deteriorate user performance and quality of experience, leading to a disruption of this mental model. While the effects of quality of service have been analyzed for traditional desktop environments, these effects remain unclear in collaborative virtual environments during user-to-user interactions. Here, we analyze the role of latency and packet bursts, two common problems in collaborative applications, on both simulator perception and actual task performance in a collaborative fire-fighting simulator. This exploratory study indicates that large latencies have a significant (p < 0.05) impact on the quality of experience, but not task performance. In contrast, packet bursts have a much larger impact on both the quality of experience and performance. Additionally, the network role, such as whether a user is a client or server, showed a significant (p < 0.05) impact on task performance in conditions impaired by packet bursts.

We present exploratory research of virtual reality techniques and mnemonic devices to assist in retrieving knowledge from scholarly articles. We used abstracts of scientific publications to represent knowledge in scholarly articles; participants were asked to read, remember, and retrieve knowledge from a set of abstracts. We conducted an experiment to compare participants' recall and recognition performance in three different conditions: a control condition without a pre-specified strategy to test baseline individual memory ability, a condition using an image-based variant of a mnemonic called a "memory palace," and a condition using a virtual reality-based variant of a memory palace. Our analyses show that using a virtual reality-based memory palace variant greatly increased the amount of knowledge retrieved and retained over the baseline, and it shows a moderate improvement over the other image-based memory palace variant. Anecdotal feedback from participants suggested that personalizing a memory palace variant would be appreciated. Our results support the value of virtual reality for some high-level cognitive tasks and help improve future applications of virtual reality and visualization.

Visualization research and practice that incorporates the arts make claims to being more effective in connecting with users on a human level. However, these claims are difficult to measure quantitatively. In this paper, we present a follow-on study to use close reading, a humanities method from literary studies, to evaluate visualizations created using artistic processes [Bares 2020]. Close reading is a method in literary studies that we’ve previously explored as a method for evaluating visualizations. To use close reading as an evaluation method, we guide participants through a series of steps designed to prompt them to interpret the visualization’s formal, informational, and contextual features. Here we elaborate on our motivations for using close reading as a method to evaluate visualizations, and enumerate the procedures we used in the study to evaluate a 2D visualization, including modifications made because of the COVID-19 pandemic. Key findings of this study include that close reading is an effective formative method to elicit information related to interpretation and critique; user subject position; and suspicion or skepticism. Information gained through close reading is valuable in the visualization design and iteration processes, both related to designing features and other formal elements more effectively, as well as in considering larger questions of context and framing.