Trial reportJournal of medical Internet research2023
Artificial Intelligence Versus Human-Controlled Doctor in Virtual Reality Simulation for Sepsis Team Training: Randomized Controlled Study.
Trial report in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05953441 (Artificial Intelligence Versus Human-controlled Doctor in Virtual Reality Simulation for Sepsis Team Training), which is not on this map. Cited by 24 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Artificial Intelligence Versus Human-controlled Doctor in Virtual Reality Simulation for Sepsis Team Training: Randomized Controlled Trial
Who cites it
24 citing papers in PubMed, 3 syntheses or guidelines pooled it, 62 citations in OpenAlex.
- The Effectiveness of Artificial Intelligence in Undergraduate Health Professions Education: Systematic Review and Meta-Analysis of Randomized Controlled Trials.JMIR medical education · 2026Pooled it
- The effectiveness of GAI-assisted teaching methods in medical education: a systematic review and meta-analysis.Frontiers in public health · 2026Pooled it
- A systematic review of the impact of artificial intelligence on educational outcomes in health professions education.BMC medical education · 2025Pooled it
- Feasibility and acceptability of a virtual learning module for navigating angry conversations in clinical encounters.BMC medical education · 2025Trial
- Effects of AI on Nursing Education: Protocol for a Systematic Review and Meta-Analysis.JMIR research protocols · 2026Article
- AI integration in healthcare simulation debriefing: support or substitute?Advances in simulation (London, England) · 2026Article
- Role of artificial intelligence and point of care ultrasound in management of critically ill patients.World journal of critical care medicine · 2026Review
- Scaling Multimodal Agentic AI in Medical Education: Multisite Cross-Sectional Study of Simulation Effectiveness in Primary Care.JMIR formative research · 2026Article
- Wearable Biosensing and Machine Learning for Data-Driven Training and Coaching Support.Biosensors · 2026Review
- Artificial Intelligence in Nursing Education: A Bibliometric Analysis.Nursing research and practice · 2026Article
- Artificial intelligence in anesthesiology education: transformative applications, challenges, and future perspectives.Frontiers in medicine · 2026Review
- The Roles of Artificial Intelligence in Interprofessional Healthcare Education: A Systematic Scoping Review.Journal of multidisciplinary healthcare · 2026Review
- Towards user-centered interactive medical image segmentation in VR with an assistive AI agent.Virtual reality · 2026Article
- Different Delivery Modalities of Virtual Reality Training in Emergency Medicine: Systematic Review.JMIR XR and spatial computing · 2026Review
- Usability and adoption in a randomized trial of GutGPT a GenAI tool for gastrointestinal bleeding.NPJ digital medicine · 2025Article
- Research on the experience of utilizing artificial intelligence in nursing learning from the perspective of nursing students - a qualitative study.BMC nursing · 2025Article
- Medical simulation: an essential tool for training, diagnosis, and treatment in the 21st century.BMC medical education · 2025Review
- Exploring the experiences and perceptions of nursing students in utilizing artificial intelligence: a descriptive phenomenological study.BMC nursing · 2025Article
- Navigating the integration of artificial intelligence in Nursing: Opportunities, challenges, and strategic actions.International journal of nursing sciences · 2025Article
- Key Concepts in Machine Learning and Clinical Applications in the Cardiac Intensive Care Unit.Current cardiology reports · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInterprofessional communication is needed to enhance the early recognition and management of patients with sepsis. Preparing medical and nursing students using virtual reality simulation has been shown to be an effective learning approach for sepsis team training. However, its scalability is constrained by unequal cohort sizes between medical and nursing students. An artificial intelligence (AI) medical team member can be implemented in a virtual reality simulation to engage nursing students in sepsis team training.
objectiveThis study aimed to evaluate the effectiveness of an AI-powered doctor versus a human-controlled doctor in training nursing students for sepsis care and interprofessional communication.
methodsA randomized controlled trial study was conducted with 64 nursing students who were randomly assigned to undertake sepsis team training with an AI-powered doctor (AI-powered group) or with medical students using virtual reality simulation (human-controlled group). Participants from both groups were tested on their sepsis and communication performance through simulation-based assessments (posttest). Participants' sepsis knowledge and self-efficacy in interprofessional communication were also evaluated before and after the study interventions.
resultsA total of 32 nursing students from each group completed the simulation-based assessment, sepsis and communication knowledge test, and self-efficacy questionnaire. Compared with the baseline scores, both the AI-powered and human-controlled groups demonstrated significant improvements in communication knowledge (P=.001) and self-efficacy in interprofessional communication (P<.001) in posttest scores. For sepsis care knowledge, a significant improvement in sepsis care knowledge from the baseline was observed in the AI-powered group (P<.001) but not in the human-controlled group (P=.16). Although no significant differences were found in sepsis care performance between the groups (AI-powered group: mean 13.63, SD 4.23, vs human-controlled group: mean 12.75, SD 3.85, P=.39), the AI-powered group (mean 9.06, SD 1.78) had statistically significantly higher sepsis posttest knowledge scores (P=.009) than the human-controlled group (mean 7.75, SD 2.08). No significant differences were found in interprofessional communication performance between the 2 groups (AI-powered group: mean 29.34, SD 8.37, vs human-controlled group: mean 27.06, SD 5.69, P=.21). However, the human-controlled group (mean 69.6, SD 14.4) reported a significantly higher level of self-efficacy in interprofessional communication (P=.008) than the AI-powered group (mean 60.1, SD 13.3).
conclusionsOur study suggested that AI-powered doctors are not inferior to human-controlled virtual reality simulations with respect to sepsis care and interprofessional communication performance, which supports the viability of implementing AI-powered doctors to achieve scalability in sepsis team training. Our findings also suggested that future innovations should focus on the sociability of AI-powered doctors to enhance users' interprofessional communication training. Perhaps in the nearer term, future studies should examine how to best blend AI-powered training with human-controlled virtual reality simulation to optimize clinical performance in sepsis care and interprofessional communication.
trial registrationClinicalTrials.gov NCT05953441; https://clinicaltrials.gov/study/NCT05953441.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.