Conclusions
inferior sepsis, sepsis
SEPSIS, SECONDARY
An AI virtual doctor agent was embedded in a virtual environment to engage interprofessional team training of nursing students on sepsis care. The performance outcomes from simulation-based assessment did not suggest that the AI-powered VRS provided inferior sepsis care and interprofessional communication training when compared with a human-controlled VRS. This shed light on the effectiveness of AI-powered medical team players in supporting nursing students with interprofessional learning where the opportunity to form interprofessional teams with medical students is lacking. Our findings suggested the need for further innovative development in AI-powered VRS to promote social connectedness with learners and support AI-driven learning analytics for assessment. Given the varied learning outcomes between AI-powered and human-controlled VRS approaches, our study recommended blending them along with face-to-face simulation to optimize students’ performance in sepsis care and interprofessional communication.We would like to thank the nursing students for their participation in this study. We also thank the staff of the National University of Singapore Information Technology and Centre for Healthcare Simulation for supporting this study. Lastly, we would like to thank the Elite Editing for providing editing services to this manuscript. This study was supported by the Ministry of Education Tertiary Education Research Fund, Singapore (MOE2020-TRF-042).Conflicts of Interest: None declared.
This randomized study was only retrospectively registered, explained by authors as according to ICMJE recommendations, the primary and secondary outcomes of this RCT did not fall under the definition of health outcomes. The editor granted an exception from ICMJE rules mandating prospective registration of randomized trials because the risk of bias appears low and the study was considered formative, guiding the development of the application. However, readers are advised to carefully assess the validity of any potential explicit or implicit claims related to primary outcomes or effectiveness, as retrospective registration does not prevent authors from changing their outcome measures retrospectively.CONSORT Flow Diagram.CONSORT-EHEALTH (Consolidated Standards of Reporting Trials of Electronic and Mobile Health Applications and Online Telehealth; V1.6.1) checklist.