The aim of NEONATAL is to study the effectiveness of VR-based simulation training in NR as a supplement to traditional simulation training for improving NR performance among doctors and nurses in Denmark. By the end of the study, we aim to have established a replicable framework that is scalable to other European countries.

The specific research objectives of NEONATAL are as follows:

NEONATAL is a multicenter individually randomized, 2-arm, controlled superiority trial with parallel-group pretest-posttest design that was conducted from October 2025 to February 2026. Immersive VR-based simulation training as a supplement to traditional mannequin-based simulation training will be compared to exclusive traditional mannequin-based simulation training. We follow the SPIRIT (Standard Protocol Recommendations for Interventions Trials) guidelines (Checklist 1) [23].

The study will be conducted at pediatric departments at 4 hospitals located in Region East, Denmark:

Resident doctors and nurses from any of these hospitals with a clinical role involving neonatal care will be eligible for inclusion.

The inclusion criteria are as follows:

The exclusion criteria are as follows:

Eligible candidates will be contacted by email as well as through informational meetings at the departments and invited to participate in the study. Informed and written consent, along with permission to record and store all video data and voice recordings for the research project, will be obtained from all participants upon enrollment.

Participant recruitment was completed in December 2025.

A comprehensive evaluation strategy will assess clinical skills and clinical knowledge, as well as user experience, including cognitive, emotional, and motivational responses.

The intervention consists of training in the NR VR training module. The VR training scenarios are standardized and identical for resident doctors and nurses. NR is inherently team-based, and although specific clinical responsibilities may differ between professions in practice, both nurses and physicians are expected to understand and follow the ERC NLS algorithm and perform core NR tasks during emergencies. Therefore, the VR scenarios focus on shared NR competencies relevant to both professional groups. The VR training module is developed in an iterative co-production process involving clinicians, educators, and Khora XR developers to ensure that the module meets real-world needs and is user-friendly in a medical environment. The iterative process ensures that the application and its content meet the expectations and requirements of HCWs. The NR scenario is an adapted version of the existing VR module content used in our feasibility study in Tanzania, to meet European health care standards.

The immersive VR scenarios use interactive features such as voice, sound (for instance, heart sounds), animated videos, and haptic feedback. During the VR scenarios, participants actively perform key steps in NR through hands-on interaction with the virtual environment and equipment. Learners assess the newborn’s clinical condition, select and prepare appropriate equipment, position the head, initiate PPV, reassess vital signs, and progress through the resuscitation algorithm based on the newborn’s clinical response. Interaction points are integrated into the virtual delivery room, enabling participants to initiate the assessment and treatment of the virtual patient through direct interaction with equipment and objects using handheld VR controllers. This allows participants to practice both procedural sequences and clinical decision-making under simulated time pressure. Information about the patient’s clinical condition, including vital signs, is provided during assessment. When interventions are made, the virtual patient’s clinical condition changes dynamically based on predefined changes in the patient’s vital signs and clinical state for each intervention. Furthermore, immediate visual and auditory feedback is integrated into the scenarios to reinforce correct actions and support reflective learning. Participants are able to change position in the virtual delivery room using teleportation. The VR scenarios force participants to reflect and train the essential individual components of NR, such as management of the airway and ventilation, and to train the sequence in the overall algorithms. The Meta Quest 3 headset is used to deliver the scenario.

The intervention in this study group is a low-volume high-frequency training in NR using VR. The VR training will take place on a weekly basis in short, under half-an-hour sessions over the intervention time period. The frequency of their individual VR training sessions, including duration, will be recorded during the intervention period. The low-volume high-frequency training model is used to allow HCWs to attend the training without compromising the patient service delivery by removing HCWs from their posts for training. The intervention group will be given a short tutorial and introduction to the VR simulation at baseline, but the VR scenarios are self-explanatory and will not be accompanied by further training during the intervention.

Throughout the intervention period, participants allocated to the intervention group will also participate in the department’s usual traditional mannequin-based simulation trainings. This guarantees that they receive the same routine NR training as the control group, with the addition of VR simulation training as a supplementary component. Traditional mannequin-based NR simulation training is not standardized by the study protocol and varies between participating departments with regard to frequency, participant composition, and simulation setting according to local clinical educational practice.

All quantitative analyses will be conducted using R (R Foundation for Statistical Computing) software and will follow the intention-to-treat principle, with participants analyzed according to the randomized group. Missing data will be explored descriptively and handled using multiple imputation under a missing-at-random assumption, with complete-case analyses conducted as sensitivity analyses. All statistical tests will be 2-sided with α=0.05.

Descriptive statistics will summarize baseline characteristics by group, with continuous variables reported as median (IQR) and categorical variables as n/N (%). Prior VR experience and cybersickness scores will be described and explored as potential factors influencing participant engagement and study outcomes.

The primary outcome is NR clinical skills performance, assessed at baseline and endline using standardized checklist scores. All video-recorded scenarios will be independently rated by 2 blinded assessors; interrater reliability will be evaluated using the intraclass correlation coefficient (ICC), with ICC≥0.75 considered acceptable. If ICC <0.75, discrepancies will be resolved through consensus discussion or adjudication by a third rater. Final skill scores will be calculated as the mean of the 2 assessors’ scores unless adjudication is required. Between-group differences in end-line NR skill scores will be analyzed using linear mixed effects models with randomized group as a fixed effect, baseline score as a covariate, and hospital as a random intercept to account for clustering.

Time-to-critical NR actions (eg, time to initiation of PPV or cardiopulmonary resuscitation) will be analyzed using Cox proportional hazards models with hospital-level clustering, applying prespecified minimum clinically important time differences (eg, 30 s for PPV initiation) to support the interpretation of clinical relevance. Secondary continuous outcomes, including knowledge scores, will be analyzed using analogous mixed effects models. Outcomes collected only in the VR group (eg, cognitive workload, motivation, usability, and cybersickness) will be analyzed descriptively and, where measured longitudinally, using within-group comparisons. Given the exploratory nature of the secondary outcomes, we will not adjust for multiple testing, and the results will not be interpreted as confirmatory.

The study will adhere to the Declaration of Helsinki. Since this project requires HCWs and does not include direct interactions with neonates, ethical considerations primarily relate to the involvement of HCWs, the use of clinical settings, and the management of data collected during the study. The Danish Scientific Ethics Committee has granted an exemption to requiring ethical approval (F-25056089). The project has been reviewed and approved by PRIVACY, the Danish Data Protection Agency for the Capital Region of Denmark, which is responsible for GDPR (General Data Protection Regulation) compliance and legal oversight of personal data processing in research (p-2025‐19577). All activities will comply with Danish national laws and the ethical guidelines governing research in health care, including data protection laws.

Personal information from potential and enrolled participants will be collected and handled in accordance with applicable data protection regulations. Data will be collected and stored in a pseudonymized and secure manner. Only authorized study personnel will have access to identifiable information. During analysis, we will extract anonymized data from REDCap, which will be stored on a secure server. The video recordings will be transferred from local storage on the video camera to a secure storage. The videos will be deleted after the completion of data processing.

Participation will be voluntary, and only consenting resident doctors and neonatal nurses will participate in this project. Before any enrollment, the PI will inform the participants, by email as well as through informational meetings at the departments, about the purpose of the study, the nature of the VR training, and their rights, including the option to withdraw at any time. Written informed consent will be obtained from all participants upon enrollment. The consent form will be digital in REDCap and will outline the purpose of the study, how the data will be used, and measures to ensure confidentiality. Participant well-being is paramount, with support available should the simulation provoke emotional distress. Measures will be taken to ensure that participation does not interfere with patient care or disrupt clinical workflows.

The trial is registered on ISRCTN (identifier ISRCTN 43822066). Any protocol modifications will be documented and updated in the trial registry and communicated to relevant study personnel.

At the time of protocol submission, recruitment and baseline assessments have been completed. End-line assessments are scheduled for completion in February 2026. As our primary and secondary outcomes are entirely dependent on data collected at endline, the results cannot be generated until data collection is finalized. Data analysis is scheduled from March to July 2026, and the study results are expected to be published in autumn 2026. The details on the study timeline are provided in Table 2.

The NEONATAL study addresses an important gap in NR education by evaluating immersive VR simulation training as a supplement to traditional mannequin-based training. While the study is designed to assess effectiveness, feasibility, and usability, several methodological and practical considerations should be acknowledged.

First, the study was conducted within a limited geographic and organizational context, involving 4 hospitals in Region East, Denmark. Although these sites represent varying levels of neonatal care and clinical complexity, the findings may not be fully generalizable to other health care systems, particularly those with different organizational structures, staffing models, or resource constraints. However, the multicenter design and inclusion of both resident doctors and neonatal nurses enhance external validity.

Second, blinding is not feasible for participants or the PI delivering the intervention, which introduces a potential risk of performance and expectation bias. To mitigate this, the outcome assessment of clinical skills is based on video-recorded scenarios evaluated by blinded assessors using a validated checklist, thereby strengthening the internal validity of the primary outcome.

Third, the intervention focuses primarily on individual technical skills and algorithm adherence in NR. While VR enables immersive and repetitive practice of critical actions, it does not fully replicate team-based dynamics, leadership, or interprofessional communication, which are central to real-life resuscitation scenarios. As such, VR is positioned in this study as a supplement rather than a replacement for traditional team-based simulation training using mannequins.

Fourth, participants allocated to the intervention group receive supplementary VR-based training in addition to the department’s usual mannequin-based simulation training, whereas the control group receives usual training alone. Consequently, the study design does not fully distinguish the effects of the VR modality itself from the effects of increased training exposure. However, the study was intentionally designed as a pragmatic evaluation of VR as a scalable supplement to standard NR training, reflecting the intended real-world implementation of VR in clinical education.

Fifth, the follow-up period of 6 to 8 weeks limits the ability to assess long-term skill retention and transfer to clinical practice.

Sixth, although immersive VR training may offer advantages such as repeated self-directed practice, standardized scenario exposure, and flexible access to simulation training, the implementation of VR-based education still requires dedicated equipment, onboarding of users, and organizational support for integration into clinical training routines. However, the VR intervention in this study is designed as short, low-volume, high-frequency sessions using standalone VR headsets, which may reduce disruption to clinical workflows compared with more resource-intensive simulation approaches. Nevertheless, the feasibility and scalability of VR training may vary across health care settings and organizational contexts.

Finally, participation in the study is voluntary, which may introduce selection bias toward HCWs who are more motivated toward simulation-based learning or more comfortable with digital technologies and VR environments. Prior VR experience and cybersickness may also influence participant engagement and learning experiences.

A central ambition of NEONATAL is to ensure that immersive VR simulation training aligns with clinical needs and integrates seamlessly into existing health care workflows and training structures. The intervention is intentionally designed as a low-volume, high-frequency training model, allowing HCWs to engage in skills refreshment without disrupting patient care or requiring extensive instructor involvement.

While the initial testing phase is limited to Eastern Denmark, the VR modules are designed with scalability in mind. The content aligns with ERC guidelines and can be adapted to different languages, institutional protocols, and health care systems. User feedback, collected through quantitative measures and qualitative interviews, will directly inform the iterative refinement of the modules, ensuring continued clinical relevance and usability. The long-term vision of NEONATAL is to contribute to systemic and equitable improvements in neonatal emergency preparedness across Europe. By demonstrating effectiveness, feasibility, and usability in a real-world clinical setting, this study aims to position the NEONATAL VR platform as a robust, scalable, and market-ready solution for NR training. This approach supports rapid dissemination and implementation, particularly in settings where access to traditional simulation training is limited by time, cost, or staffing constraints.

The protocol, including the statistical analysis plan, is intended for publication in JMIR Research Protocols. The results of the study will be disseminated through multiple channels to maximize scientific, clinical, and societal impact. Primary findings will be published in peer-reviewed open access journals and presented at national and international conferences focusing on neonatology, medical education, simulation, and digital health. In addition, aggregated study findings will be shared with participating departments and hospital administrations to support local quality improvement initiatives.

Beyond academic dissemination, the project will engage with clinical educators, professional societies, and health care policymakers to promote the evidence-based integration of VR simulation into existing neonatal training frameworks. Insights from the feasibility and usability components will be used to inform implementation guidelines and best practices for VR-based training in routine clinical settings.

By combining evaluation with an implementation and dissemination strategy, the study aims to support the translation of immersive VR training into clinical practice.

Patients or members of the public will not be involved in the design, conduct, or reporting of this study, as the intervention targets health care professionals and focuses on clinical training.