Background: Recently, the demand for mechanical ventilation (MV) has increased with the COVID-19 pandemic; however, the conventional approaches to MV training are resource intensive and require on-site training. Consequently, the need for independent learning platforms with remote assistance in institutions without resources has surged. Objective: This study aimed to determine the feasibility and effectiveness of an augmented reality (AR)–based self-learning platform for novices to set up a ventilator without on-site assistance. Methods: This prospective randomized controlled pilot study was conducted at Samsung Medical Center, Korea, from January to February 2022. Nurses with no prior experience of MV or AR were enrolled. We randomized the participants into 2 groups: manual and AR groups. Participants in the manual group used a printed manual and made a phone call for assistance, whereas participants in the AR group were guided by AR-based instructions and requested assistance with the head-mounted display. We compared the overall score of the procedure, required level of assistance, and user experience between the groups. Results: In total, 30 participants completed the entire procedure with or without remote assistance. Fewer participants requested assistance in the AR group compared to the manual group (7/15, 47.7% vs 14/15, 93.3%; P=.02). The number of steps that required assistance was also lower in the AR group compared to the manual group (n=13 vs n=33; P=.004). The AR group had a higher rating in predeveloped questions for confidence (median 3, IQR 2.50-4.00 vs median 2, IQR 2.00-3.00; P=.01), suitability of method (median 4, IQR 4.00-5.00 vs median 3, IQR 3.00-3.50; P=.01), and whether they intended to recommend AR systems to others (median 4, IQR 3.00-5.00 vs median 3, IQR 2.00-3.00; P=.002). Conclusions: AR-based instructions to set up a mechanical ventilator were feasible for novices who had no prior experience with MV or AR. Additionally, participants in the AR group required less assistance compared with those in the manual group, resulting in higher confidence after training. Trial Registration: ClinicalTrials.gov NCT05446896; https://beta.clinicaltrials.gov/study/NCT05446896

Background: In the wake of challenges brought by the COVID-19 pandemic to conventional medical education, the demand for innovative teaching methods has surged. Nurse training, with its focus on hands-on practice and self-directed learning, encountered significant hurdles with conventional approaches. Augmented reality (AR) offers a potential solution to addressing this issue. Objective: The aim of this study was to develop, introduce, and evaluate an AR-based educational program designed for nurses, focusing on its potential to facilitate hands-on practice and self-directed learning. Methods: An AR-based educational program for nursing was developed anchored by the Kern six-step framework. First, we identified challenges in conventional teaching methods through interviews and literature reviews. Interviews highlighted the need for hands-on practice and on-site self-directed learning with feedback from a remote site. The training goals of the platform were established by expert trainers and researchers, focusing on the utilization of a ventilator and extracorporeal membrane oxygenation system. Intensive care nurses were enrolled to evaluate AR education. We then assessed usability and acceptability of the AR training using the System Usability Scale and Technology Acceptance Model with intensive care nurses who agreed to test the new platform. Additionally, selected participants provided deeper insights through semistructured interviews. Results: This study highlights feasibility and key considerations for implementing an AR-based educational program for intensive care unit nurses, focusing on training objectives of the platform. Implemented over 2 months using Microsoft Dynamics 365 Guides and HoloLens 2, 28 participants were trained. Feedback gathered through interviews with the trainers and trainees indicated a positive reception. In particular, the trainees mentioned finding AR particularly useful for hands-on learning, appreciating its realism and the ability for repetitive practice. However, some challenges such as difficulty in adapting to the new technology were expressed. Overall, AR exhibits potential as a supplementary tool in nurse education. Conclusions: To our knowledge, this is the first study to substitute conventional methods with AR in this specific area of critical care nursing. These results indicate the multiple principal factors to take into consideration when adopting AR education in hospitals. AR is effective in promoting self-directed learning and hands-on practice, with participants displaying active engagement and enhanced skill acquisition. Trial Registration: ClinicalTrials.gov NCT05629663; https://clinicaltrials.gov/study/NCT05629663.

Background: COVID-19 pandemic has significantly impacted the field of medical training, necessitating innovative approaches to education and practice. During this period, the use of novel technologies like virtual reality (VR), augmented reality (AR), and mixed reality (MR) has become increasingly vital. These technologies offer the advantage of transcending the limitations of time and space, thus enabling medical professionals to access various personalized programs for both education and service delivery. This shift is particularly relevant in the realm of pediatric medicine, where traditional training and clinical methods face unique challenges.Purpose: The primary aim of this study is to explore the application of VR, AR, and MR technologies in pediatric medical settings, with a focus on both clinical applications and the training of pediatric medical professionals. We aim to comprehensively search and review studies that have utilized these technologies in the treatment of pediatric patients and the education of healthcare providers in this field.Methods: Peer-reviewed articles published in PubMed, the Cochrane Library, ScienceDirect, Google Scholar, and Scopus from January 1, 2018, to March 1, 2023, were comprehensively searched. The review was conducted according to the PRISMA (Preferred Reporting Items for Systematic review and Meta-Analyses) guidelines. Among the 89 studies, 63 investigated the clinical applications of VR (n=60) or AR (n=3) in pediatric patients, and 25 investigated the applications of VR (n=19), AR (n=5), or MR (n=1) for training medical professionals.Results: A total of 36 randomized controlled trials (RCTs) for clinical application (n=31) and medical training (n=5) were retrieved. Among the RCTs, 21 reported significant improvements in clinical applications (n=17) and medical training (n=4).Conclusion: Despite a few limitations in conducting research on innovative technology, such research has rapidly expanded, indicating that an increasing number of researchers are involved in pediatric research using these technologies.

Background: The health care sector faces a projected shortfall of 10 million workers by 2030. Artificial intelligence (AI) automation in areas such as patient education and initial therapy screening presents a strategic response to mitigate this shortage and reallocate medical staff to higher-priority tasks. However, current methods of evaluating early-stage health care AI chatbots are highly limited due to safety concerns and the amount of time and effort that goes into evaluating them. Objective: This study introduces a novel 3-bot method for efficiently testing and validating early-stage AI health care provider chatbots. To extensively test AI provider chatbots without involving real patients or researchers, various AI patient bots and an evaluator bot were developed. Methods: Provider bots interacted with AI patient bots embodying frustrated, anxious, or depressed personas. An evaluator bot reviewed interaction transcripts based on specific criteria. Human experts then reviewed each interaction transcript, and the evaluator bot’s results were compared to human evaluation results to ensure accuracy. Results: The patient-education bot’s evaluations by the AI evaluator and the human evaluator were nearly identical, with minimal variance, limiting the opportunity for further analysis. The screening bot’s evaluations also yielded similar results between the AI evaluator and human evaluator. Statistical analysis confirmed the reliability and accuracy of the AI evaluations. Conclusions: The innovative evaluation method ensures a safe, adaptable, and effective means to test and refine early versions of health care provider chatbots without risking patient safety or investing excessive researcher time and effort. Our patient-education evaluator bots could have benefitted from larger evaluation criteria, as we had extremely similar results from the AI and human evaluators, which could have arisen because of the small number of evaluation criteria. We were limited in the amount of prompting we could input into each bot due to the practical consideration that response time increases with larger and larger prompts. In the future, using techniques such as retrieval augmented generation will allow the system to receive more information and become more specific and accurate in evaluating the chatbots. This evaluation method will allow for rapid testing and validation of health care chatbots to automate basic medical tasks, freeing providers to address more complex tasks.

The outcomes of weaning processes are not well known in pediatric patients, and the International Conference Classification on weaning from mechanical ventilation showed limited application. We evaluate the relationship between the new Weaning according to a New Definition (WIND) classification and outcome in pediatric patients. We conducted a retrospective cohort study in a tertiary pediatric intensive care unit (ICU). We included patients under 18 years of age who received invasive mechanical ventilation for more than 24 h and excluded cases with other than the first ICU admissions, tracheostomy with home ventilation before admission, intubation or weaning processes conducted in other ICU, and weaning with extracorporeal membrane oxygenation. Weaning processes were classified into four groups according to weaning duration after the first separation attempt (SA): no-SA, short weaning (< 24 h), difficult weaning (24 h–7 days), and prolonged weaning (> 7 days). Mortality rates were compared across groups using the Kruskal–Wallis test, and risk factors for the no-SA group were analyzed by multivariate logistic regression tests with age, sex, severity score at admission, admission type, and underlying disease as variables. Among 313 patients, 224 were enrolled and had a median age of 2.1 (interquartile range 0.5–6.6) years. Spontaneous breathing tests were done in 70.1% of enrolled patients. The median duration of intubation to the first SA was 4 (range 0–36) days, and 92.8% patients underwent the first SA within 14 days. The mortality rate was 0% in the short (0/99) and difficult (0/53) weaning groups and 17.9% (5/28) in the prolonged weaning group (p < 0.001). The mortality rate of the no-SA group was 93.2% (41/44). Admission severity (hazard ratio 1.036, confidence interval 1.022–1.050) and underlying oncologic disease (hazard ratio 7.341, confidence interval 3.008–17.916) were independent risk factors for lack of SA. In conclusion, WIND classification is associated with ICU mortality in pediatric patients. Further studies of this association are required to improve protocols associated with the weaning process and clinical outcomes. Trial registration Retrospectively registered.

Background: Although the outcome of cardiopulmonary resuscitation (CPR) is still unsatisfactory, there are few studies about temporal trends of in‐hospital CPR incidence and mortality. We aimed to evaluate nationwide trends of in‐hospital CPR incidence and its associated risk factors and mortality in pediatric patients using a database of the Korean National Health Insurance between 2012 and 2018. Methods and Results: We excluded neonates and neonatal intensive care unit admissions. Incidence of in‐hospital pediatric CPR was 0.58 per 1000 admissions (3165 CPR/5 429 471 admissions), and the associated mortality was 50.4%. Change in CPR incidence according to year was not significant in an adjusted analysis ( P =0.234). However, CPR mortality increased significantly by 6.6% every year in an adjusted analysis ( P <0.001). Hospitals supporting pediatric critical care showed 37.7% lower odds of CPR incidence ( P <0.001) and 27.5% lower odds of mortality compared with other hospitals in the adjusted analysis ( P <0.001), and they did not show an increase in mortality ( P for trend=0.882). Conclusions: Temporal trends of in‐hospital CPR mortality worsened in Korea, and the trends differed according to subgroups. Study results highlight the need for ongoing evaluation of CPR trends and for further CPR outcome improvement among hospitalized children.