Effect of Virtual Reality Training on Novice Intensive Care Unit Nurses: A Randomized Controlled Pilot Study

Effect of Virtual Reality Training on Novice Intensive Care Unit Nurses: A Randomized Controlled Pilot Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effect of Virtual Reality Training on Novice Intensive Care Unit Nurses: A Randomized Controlled Pilot Study Banu Terzi, Halenur Şahin, Gülcan Emir, Gülzade Uysal, Duygu Sönmez Düzkaya, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8585355/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: It is very important for nurses, who are an indispensable member of the health care team in the intensive care unit, to be equipped with high-level knowledge and skills in patient care management to improve the quality of patient life. Purpose: This study aimed to develop virtual reality software for intensive care patient care management and examine the effect of this software on novice recruited intensive care nurses. Methods: The randomized controlled study was conducted with a total of 47 nurses. The data of the study were collected with “Nurse Introductory Information Form”, “Knowledge Level Questionnaire”, “Clinical Practice Skills Observation Form”, “Problem Solving Inventory”, “Clinical Decision Making Scale in Nursing” and “State Anxiety Inventory” Results: The mean knowledge scores of the nurses in the control group 1 week and 1 month after the intervention were found to be higher than the pre-intervention measurements (p<0.05). In both groups, the level of problem solving 1 month after the intervention was higher than the measurements before and 1 week after the intervention (p<0.05). Conclusion: Innovative training methods such as virtual reality contributed positively to the short-term problem-solving skills of nurses, but longer-term or repeated applications may be required to measure clinical decision-making and knowledge levels. Clinical trial number: NCT05982288 (Date: 08/07/2023) Clinical decision-making intensive care nurse problem-solving state anxiety virtual reality Figures Figure 1 Figure 2 INTRODUCTION Intensive care units (ICUs) represent one of the most demanding environments in healthcare, where nurses must rapidly interpret patient data, operate complex equipment, and make critical decisions under pressure. Novice ICU nurses often experience high levels of stress, difficulty translating theoretical knowledge into practice, and reduced confidence in problem-solving and clinical decision-making—factors that can jeopardize patient safety and care quality (1). Traditional methods such as lectures, checklists, preceptorships, and mannequin-based simulations, while foundational, often fail to recreate the dynamic nature of ICU scenarios. These approaches can be limited by resource constraints, sporadic availability, and difficulty portraying real-time complexity. As such, newly hired ICU nurses may lack repeated, realistic exposure to high-stakes situations (2). Virtual reality (VR) offers a compelling alternative. VR enables immersive, interactive simulations that replicate ICU environments in a safe, controlled manner. Learners can practice repetitive scenarios, receive immediate feedback, and develop cognitive and psychomotor skills without risking patient harm. Meta-analyses in nursing education demonstrate significant improvements in theoretical knowledge, practical skills, skill retention, and satisfaction (3). A broader systematic review and meta-analysis also reported substantial gains in knowledge, skills, and confidence with VR interventions (3). Additionally, immersive VR has been recognized by nursing educators as an emerging and effective tool in clinical education (4). Despite these promising outcomes, most studies to date have focused on nursing students rather than practicing professionals—particularly unfamiliar ICU nurses. Recent efforts include a randomized controlled trial using VR for emergency and urgent care training among nurses and students, which showed superior knowledge acquisition and satisfaction compared with traditional learning (5). In another notable study, a 360-degree VR program targeting mechanical ventilation competence among ICU nurses demonstrated significant improvements in clinical reasoning and self-efficacy (6). These findings suggest VR's potential applicability in real-world ICU contexts, yet randomized controlled trials specifically assessing novice ICU nurses remain few. There remains a critical gap in evidence regarding the effectiveness VR in enhancing core clinical competencies—knowledge, clinical performance, problem-solving, and decision-making—in newly appointed ICU nurses. A rigorous randomized controlled design is necessary to evaluate the added value of VR over standard orientation processes. To address this, our study employs a randomized controlled design to evaluate the impact of VR-based training on novice ICU nurses across four domains: (1) theoretical knowledge of ICU protocols, (2) clinical performance accuracy in simulated tasks, (3) problem-solving ability in evolving scenarios, and (4) clinical decision-making aligned with evidence-based practice. The intervention group received VR training in addition to standard orientation, and the control group completed standard orientation alone. We hypothesized that VR training would result in significantly greater improvements across all four domains, and that these gains would be more durable than those of conventional training alone. Demonstrating such benefits could inform ICU onboarding curricula, support the integration of VR into competency development, and ultimately contribute to safer, more prepared critical care teams. Our study aimed to advance the field of immersive learning in nursing by delivering high-quality evidence tailored to the needs of novice ICU professionals. Research Hypotheses H 1 : VR software increases nurses' knowledge level. H 2 : VR software increases nurses' problem-solving skills. H 3 : VR software increases nurses' clinical decision-making skills. H 4 : VR software increases nurses' clinical practice skills. H 5 : VR software reduces nurses' state anxiety levels. Design and Methods This study was designed as a parallel-group randomized controlled trial with a 1:1 allocation ratio and a pretest–posttest design, conducted within a superiority framework.We used the CONSORT reporting guideline (1) to draft this manuscript, and the CONSORT reporting checklist (2) when editing, included in Supplement A (7). The CONSORT flow chart of the study is shown in Figure 1. Setting and Sample The trial was conducted in the ICUs’ nursing education rooms of a two public hospital in southern Türkiye. The intervention and data collection procedures were implemented on-site at the nursing education rooms. The study population consisted of newly hired nurses in the ICUs of two state hospitals located in southern Turkey (N=150). The study sample was determined using G*Power power analysis. When determining the sample size of the study, the scientific study titled “Effect of high-fidelity simulation on clinical decision-making among nursing students” by Ayed et al. (8) was used as a basis to determine the sample size for the effect size based on literature reviews. Ayed et al. (8) reported that the mean total score on the Clinical Decision-Making Scale was 148.7 ± 14.10 in the experimental group and 158.5 ± 12.60 in the control group (8). Based on these data, the power analysis (G*Power 3.1.9.2) resulted in an effect size = 0.73, 95% confidence interval, 80% power, requiring a total of 62 nurses, with at least 31 in each group. Considering the possibility of dropouts and confounders during the research process, the number in the groups was increased by 10% (9). The sample of the study was determined as a total of 68 nurses, with 34 nurses in each study group. The study was completed with 47 nurses, including 25 nurses in the study group and 22 nurses in the control group. A post-power analysis was performed after data collection. The sample size for the study was determined to as 𝑑= 0.1756, and the probability of error α was accepted as 0.05. Power (1-𝛽 error probability) was targeted at 0.80, which represents an 80% probability of obtaining a correct result. The sample distribution between the groups was planned to be equal (N2/N1=1), and the actual power value obtained with this analysis was calculated as 0.8006. This provides a result very close to the predetermined target power. These findings indicate that the target power was achieved with the specified sample size and effect size. Participants The study was conducted with nurses who had recently started working in the tertiary ICUs of two hospitals. The criteria for inclusion in the study were: recent graduation from nursing school, recent start of employment in the ICU, no previous experience working in the ICU, and willingness to participate in the study. The criteria for exclusion from the study were: having recently started working in the ICU and subsequently changing job location, leaving the job at any stage of the study, and being a member of a profession other than nursing (e.g., midwife, paramedic). This study was conducted as an educational intervention involving nursing students. Patients and the public were not involved in the design, conduct, reporting, or dissemination of the study. Randomization and Blinding Nurses meeting the sample selection criteria were randomly and equally distributed into two groups (experimental group, control group) using a computer program, ensuring simple randomization (10). Participants were randomly assigned to the intervention or control group using a simple randomization method with a 1:1 allocation ratio. The random sequence was generated prior to participant enrollment. No stratification or block randomization was applied, as no such restrictions were specified in the registered protocol (NCT05982288). Allocation concealment was ensured by assigning participants to groups after baseline assessments were completed. Allocation concealment was achieved by implementing the randomization sequence after completion of baseline assessments. Group assignments were generated and applied by an independent researcher who was not involved in participant recruitment, intervention delivery, or outcome assessment. The allocation sequence was concealed from participants and instructors until the point of assignment. In this study, a single-blind method was used to prevent interaction between nurses. Participant enrollment was conducted by the course instructor, who did not have access to the random allocation sequence. Group assignment was performed by an independent researcher responsible for implementing the randomization procedure. The personnel involved in participant enrollment, intervention delivery, and outcome assessment were blinded to the allocation sequence. Blinding of participants and instructors was not possible due to the educational nature of the intervention. Outcome assessors were blinded to group allocation. Both groups received identical course content and practice time, differing only in instructional approach. Data Collection Tools and Methods The data for the study were collected using a Sociodemographic Information Form, the Knowledge Level Questionnaire, Clinical Practice Skills Observation Form, Problem-Solving Inventory, Clinical Decision-Making Scale in Nursing, and State Anxiety Inventory (Table 1) (2). Implementation of the Study The study was conducted in four stages: Stage 1: An adult ICU patient case scenario (Table 2) and an ICU patient care management algorithm (Figure 2) based on Kolcaba's Comfort Theory specific to this scenario, along with training modules, were prepared. Expert opinions were obtained from five specialists in the field (one ICU specialist physician, three ICU nurses, and one nurse academic experienced in ICU nursing) for the prepared scenario and algorithms. Following the expert opinions, the content of the scenario and algorithm was revised (2). Stage 2: The modules related to the scenarios and algorithms prepared in the first phase were integrated into the VR software by a computer programmer through a service procurement within the scope of project support and transferred to the VR headset. The VR software was developed using C# Unity technology. Three-dimensional modeling of objects such as characters, environments, floors, machinery, and equipment was performed using the Blender program (2). Detailed medical equipment and intensive care environments were modeled using the Blender program. Substance Painter was used for the textures, enabling the creation of realistic and accurate surface materials. Animations demonstrating medical scenarios and equipment use were created in Blender. The models were added in 3D to the Unity game editor, and C# was used as the programming language. Stage 3: Nurses who were new to the ICU and met the inclusion criteria received a total of 16 hours of theoretical training over 2 days in a face-to-face setting, delivered by the researchers. PowerPoint presentations were used in the theoretical training, and the content of the training was based on Kolcaba's Comfort Theory, the ICU patient care management algorithm (Figure 2), and the training module topics (2). After the training, the nurses were randomly assigned to the intervention and control groups. To prevent interaction between the groups, nurses in the intervention and control groups were monitored in the ICUs of two different hospitals during the study period. Stage 4: Practical training was conducted immediately after theoretical training: Control group: Nurses in the control group received routine orientation training in the ICU. Routine orientation training is conducted by the nurse in charge and experienced mentor nurses in the ICU. Nurses new to the ICU work under the supervision of experienced mentors for 5 days from 8 a.m. to 4 p.m. and take on the care management of only one ICU patient whose condition is stable. During this process, the charge nurse also provides orientation training in accordance with the orientation training schedule, covering the ICU environment, the tools and equipment used in the unit, routine care and treatment practices, the functioning of the unit, and duties and responsibilities. The week after the 5-day training, the new nurses begin to take on the responsibility of caring for an ICU patient on their own, working 24-hour shifts with a 2:1 patient-to-nurse ratio. Study group: In addition to the routine ICU orientation training, nurses in the study group were given 15-minute individual training sessions in a virtual environment using VR glasses on patient care management. In accordance with the scenario presented in the VR glasses, nurses applied each module of the scenario and each step of the procedures in the modules individually. A 10-minute pre-briefing on the use of the VR headset was provided before the application. The application was conducted in an empty conference room with area definition in the VR headset. Mentoring was provided by two researchers during the application. After the application, the experiences of each VR headset user were shared in a debriefing session. After each VR application, the VR headset was cleaned and prepared for reuse. The VR headset was recharged every 4 hours. The training in the VR environment was completed in 2 days. All interventions were delivered by the same instructors to ensure consistency. The duration and content of the training were standardized across groups, with the exception of the technology-enhanced components provided to the intervention group. Data analysis Data analysis was performed using the IBM SPSS Statistics version 26 (IBM Inc., Armonk, NY, USA) software. In the analysis of data, number, percentage, and mean were obtained, then frequency and percentage distributions were calculated. The relationship between variables measured at the categorical level was evaluated using Pearson’s Chi-square test. Differences between groups regarding measurements were analyzed using the Mann-Whitney U test, and the difference between measurements was evaluated using the Friedman test. The Bonferroni test was used to determine which group the difference originated from. The significance level was accepted as 0.05. A statistically significant difference was accepted when p was 0.05. Ethics Approval and Consent to Participate The Declaration of Helsinki was followed in the study and the willingness and voluntariness of the nurses to participate in the study were taken into account. Written permissions were obtained from Akdeniz University Medical Sciences Ethics Committee (16/04/2023, permission no. KAEK-250) and Antalya Provincial Health Directorate, Antalya Kepez State Hospital and Antalya City Hospital, where the study was conducted. Written informed consent was obtained from all participants after they were fully informed about the purpose, procedures, potential risks, and benefits of the study. After the study was completed in accordance with ethical principles, the nurses in the control group were also trained in the care management of intensive care patients using VR. Trial Registration Clinical trial number: NCT05982288 (Date: 08/07/2023). The study was conducted in accordance with the protocol (2) registered on ClinicalTrials.gov (NCT05982288), and no important changes were made to the trial protocol, pre-specified outcomes, or planned analyses after the study commenced. RESULTS The findings of the study are examined in two sections: 1. Nurses’ characteristics Some descriptive characteristics of the nurses participating in the study are given in Table 3. It was determined that the nurses showed a homogeneous distribution in terms of age, sex, marital status, and educational status variables. 2. Nurses’ knowledge, problem-solving, clinical decision-making, clinical application skills, and state anxiety levels The comparison of the knowledge score averages of the nurses is presented in Table 4. When the measurements between the groups were examined, the difference between the pre-test and the post-test values of the nurses in the study and control groups 1 week and 1 month after the application was not statistically significant (p>0.05). When the measurements within the groups were examined, it was found that the average knowledge scores of the nurses in the study group were similar in consecutive measurements (p>0.05). The average knowledge scores of the nurses in the control group 1 week and 1 month after the application were found to be higher than the measurements before the application (p<0.05; 1<2,3) (Table 4). The comparison of the average problem-solving inventory scores of the nurses is presented in Table 4. The difference between the average PSI scores of pre-test, and 1 week, and 1 month after the application between the groups was not statistically significant (p>0.05). When the within-group measurements were examined, the mean problem-solving inventory scores in the study and control groups 1 month after the application were found to be higher than the measurements before and 1 week after the application (p1,2) (Table 4). The comparison of the mean scores of the nurses on the clinical decision-making scale in nursing is examined in Table 4. When the measurements between the groups were examined, the difference between the pre-test and post-test values of the nurses in the study and control groups 1 month after the application was not statistically significant (p>0.05). However, the measurements of the nurses in the study group 1 week after the application were higher than those in the control group (p0.05). The mean clinical decision-making scores of the nurses in the control group 1 month after the application were found to be higher than the measurements before and 1 week after the application (p1,2) (Table 4). The comparison of the mean state anxiety inventory scores of the nurses is examined in Table 4. When the measurements between the groups were examined, the difference between the pre-test and the post-test values of the nurses in the study and control groups 1 week and 1 month after the application was not statistically significant (p>0.05). When the measurements within the groups were evaluated, the differences between the consecutive measurements in the study and control groups were not statistically significant (p>0.05) (Table 4). The comparison of the mean scores clinical practice skills of the nurses is examined in Table 4. The difference between the mean clinical practice skill scores of the nurses in the study and control groups was not statistically significant (p>0.05) (Table 4). DISCUSSION This study evaluated the effect of VR software on the education of newly recruited intensive care nurses. The research findings revealed significant results regarding the problem-solving skills, clinical decision-making, knowledge levels, and clinical practice skills of the nurses. In terms of knowledge scores, it was observed that the knowledge scores of the nurses in the control group increased significantly 1 week and 1 month after the application. This shows that traditional education methods can be effective in gaining knowledge in the short term. However, the fact that the change in knowledge scores in the study group was not significant may indicate that longer-term and repeated applications may be necessary for the transfer of knowledge of new technologies such as VR. This result does not support the H 1 hypothesis. Contrary to our study, a systematic review reported that VR increased knowledge and skills in nursing education and that there was evidence from related randomized control trials (RCTs) (3). Although prior meta-analyses indicated that VR could improve learner knowledge in nursing education, our study showed no superior knowledge gains in the VR group compared with standard orientation; rather, the control group showed modest post-test increases. This discrepancy may stem from differences in VR content (emphasis on applied decision-making rather than declarative knowledge), measurement sensitivity, or workplace learning influences experienced by controls. Similar heterogeneity in knowledge outcomes has been reported in recent reviews, underscoring the need to align VR learning objectives with assessment tools. According to the research findings, the problem-solving inventory scores of the nurses in the study group increased 1 week and 1 month after the application, and this increase was found to be statistically significant especially 1 month after the application, supporting the H 2 hypothesis. Similarly, there are some RCT and quasi-experimental studies showing that VR and virtual simulations improve clinical reasoning and problem-solving (17). Positive effects of 360° VR programs on clinical reasoning and self-efficacy have been reported (6, 18). In the our study, both groups demonstrated improved problem-solving at 1 month, suggesting that orientation plus clinical exposure contributes meaningfully to this competency. Although prior studies have shown VR can accelerate clinical reasoning, our findings indicate that standard training pathways may also yield gains over time; the incremental benefit of VR may depend on scenario design, feedback mechanisms, and exposure time. Future work should compare enriched VR (with structured debrief) versus routine orientation to isolate specific active components. It was determined that the clinical decision-making skills of the nurses in the study group were higher than those of the nurses in the control group 1 week after the application. With this result, hypothesis H 3 was supported. The literature indicates that generative/immersive VR systems improve clinical decision-making skills (17, 18). The transient superiority of the VR group at 1 week suggests that immersive practice can accelerate initial gains in clinical decision-making. The subsequent rise in control group scores by 1 month points to the powerful role of on-the-job learning and experience. These dynamics mirror recent RCTs showing immediate decision-making benefits from VR that may require reinforcement to persist—highlighting the importance of blended VR-clinical curricula. According to the research findings, no significant difference was found between the clinical practice skill scores of nurses in the study and control groups. Therefore, although the H 4 hypothesis was not supported, simulations and VR software should be used regularly and supported with clinical environments to improve nurses' clinical practice skills. VR applications have been reported to have positive effects on technical skills and clinical performance; however, the magnitude of these effects varies depending on the study (3, 19). Furthermore, although AR/VR has been shown to increase learning efficiency in certain specific procedures (CPR, ventilator management, crash cart), results regarding general clinical skills have been found to be heterogeneous (20). Although systematic reviews support the effectiveness of VR for certain procedural skills, we found no between-group differences in overall clinical performance. This may reflect differences in VR content fidelity, exposure time, and outcome measurements. Targeted VR modules for high-priority procedures with objective performance metrics could yield clearer benefits. According to the research findings, there was no significant difference in the level of state anxiety between the two groups. Accordingly, the H 5 hypothesis was not supported. Some studies reported positive results regarding the reduction of anxiety during training through simulation and VR (21, 22), but the findings were heterogeneous. Although a reduction in anxiety has been reported among students, the effects among professionals (nurses) are mixed; some studies mention short-term relief, whereas others have shown no significant change (22). We observed no significant changes in state anxiety across the groups. This aligns with mixed evidence: although VR can reduce situational anxiety in student samples, its effect on practicing nurses’ workplace-related anxiety is inconsistent. Tailoring VR scenarios to include stress-inoculation elements and pairing simulation with reflective debriefing may be necessary to impact anxiety meaningfully. Limitation The fact that the study was conducted at only two hospitals and that most of the nurses assigned to the ICU were already experienced are the most significant limitations that reduced the sample size. Another limitation was that, due to time constraints, the VR application could only be performed once by the working group. Recommendations or Implications for Practice and/or Further Research VR-based training should be implemented repeatedly to continuously improve nurses' problem-solving and clinical decision-making skills. Nurses' practice skills should be increased by combining VR simulations with clinical environments (e.g., intensive care, emergency care). VR technologies should be integrated into traditional theoretical training to increase nurses' knowledge levels. More comprehensive and larger sample groups should be conducted, especially on the care management of intensive care patients based on VR. CONCLUSION In the study, it was found that VR software in intensive care patient care management improved problem-solving, clinical decision-making, and knowledge levels in the education of intensive care nurses and also provided high satisfaction. However, the lack of a significant difference in clinical practice skills indicates that more practical experience is needed to develop these skills. Our findings indicate that VR can contribute to short-term, goal-oriented gains (e.g., decision-making, approach to problem-solving), but traditional orientation and clinical experience also have a strong learning effect. For more meaningful results, repeated VR applications and structured debriefing can be combined. Multi-dimensional performance measurement tools can be used in the evaluation. Declarations Data availability statement: Data sharing can be done with permission from the corresponding author. Ethics statement: The Declaration of Helsinki was followed in the study and the willingness and voluntariness of the nurses to participate in the study were taken into account. Written permissions were obtained from Akdeniz University Medical Sciences Ethics Committee (16/04/2023, permission no. KAEK-250) and Antalya Provincial Health Directorate, Antalya Kepez State Hospital and Antalya City Hospital where the study was conducted. Written informed consent was obtained from all participants after they were fully informed about the purpose, procedures, potential risks, and benefits of the study. After the study was completed in accordance with ethical principles, the nurses in the control group were also trained on the care management of intensive care patients using virtual reality software. Acknowledgement: We would like to thank Nurse Cennet Özer for creating the scenarios for the study and shooting the videos, and İsa Şahin for her technical support during the use of the virtual reality glasses. Funding: This study was supported by TUSEB (TÜSEB-2022-A9-28103). Declaration of competing interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Consent for publication: Not Applicable Clinical trial registration: Protocol ID: VR_BANUTERZI07; Clinical Trials,gov ID: NCT05982288 (Date: 08/07/2023) Patient Consent Statement: Not applicable Data Availability Statement: T)he data that support the findings of this study are available from the corresponding author upon reasonable request. Author Contributions: BT, DSD, GU, and NY developed the protocol. BT, HŞ, GE, DSD, NY and MC applicated the study. GU made analysis, BT drafted the manuscript. All authors contributed to and revised the final manuscript. References Kanschik D, Bruno RR, Wolff G, Kelm M, Jung C. Virtual and augmented reality in intensive care medicine: a systematic review. Ann. Intensive Care. 2023;13:81. doi: 10.1186/s13613-023-01176-z. Terzi B, Düzkaya DS, Uysal G, Yalnız N. A study protocol to develop virtual reality software in the care management of patients in intensive care. Nurs Crit Care. 2025;30(4):e13231. doi: 10.1111/nicc.13231. 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Yoon H, Lee E, Kim CJ, Shin Y. Virtual reality simulation-based clinical procedure skills training for nursing college students: a quasi-experimental study. Healthcare (Basel) . 2024;12(11):1109. doi: 10.3390/healthcare12111109. Tables Tables 1 to 4 are available in the supplementary files section Additional Declarations No competing interests reported. Supplementary Files SupplementAconsortchecklist.docx Tables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Terzi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYBACAxiDjb2BmYGHAYQYGCQIajkA0sJzAEWLAWEtDBIJzBD1hLSYs589Jv2h4p49n+TjxwZvKu7IyDcwH7zNw/AnH5cWy568NIkDZ4qZ2aTTjBPnnHnGw9jAlmzNw2Bg2YDLYQdyzCQOtiWwsUknGB/mbTvMA3SemTRQC06XGZx/A9TyL4GHTfL458O8/w7zsDHwf8Ov5QbIloYECTYJHuNk3obDPDwMPGx4tVjOeGNsceZYggEbT06x4Zxjh3kkmNmMLecYGOPUYs6fY3ijoibBXr79+GaJNzWHgYzmhzfeVMjhDmVMwAx2MAkaRsEoGAWjYBRgAAAiOkhq4Qpp9QAAAABJRU5ErkJggg==","orcid":"","institution":"Akdeniz University","correspondingAuthor":true,"prefix":"","firstName":"Banu","middleName":"","lastName":"Terzi","suffix":""},{"id":592959024,"identity":"61050941-7df2-49fe-b9aa-dd7c1fdfa90e","order_by":1,"name":"Halenur Şahin","email":"","orcid":"","institution":"Antalya City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Halenur","middleName":"","lastName":"Şahin","suffix":""},{"id":592959025,"identity":"33eb094d-24a5-4aa8-8828-da81c6be93df","order_by":2,"name":"Gülcan Emir","email":"","orcid":"","institution":"Antalya Kepez State Hospital","correspondingAuthor":false,"prefix":"","firstName":"Gülcan","middleName":"","lastName":"Emir","suffix":""},{"id":592959026,"identity":"0662a74c-6fe3-4d1a-b0bb-e230c7c48953","order_by":3,"name":"Gülzade Uysal","email":"","orcid":"","institution":"Sakarya University of Applied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Gülzade","middleName":"","lastName":"Uysal","suffix":""},{"id":592959027,"identity":"48e637b0-587a-4a9a-a4ff-d5c605a4e503","order_by":4,"name":"Duygu Sönmez Düzkaya","email":"","orcid":"","institution":"Tarsus University","correspondingAuthor":false,"prefix":"","firstName":"Duygu","middleName":"Sönmez","lastName":"Düzkaya","suffix":""},{"id":592959028,"identity":"ceb02547-88a9-4e2e-acf8-7241aa884762","order_by":5,"name":"Nazik Yalnız","email":"","orcid":"","institution":"Akdeniz University","correspondingAuthor":false,"prefix":"","firstName":"Nazik","middleName":"","lastName":"Yalnız","suffix":""},{"id":592959029,"identity":"eb249c46-afec-4f36-8f10-068408e94206","order_by":6,"name":"Melike Cengiz","email":"","orcid":"","institution":"Akdeniz University","correspondingAuthor":false,"prefix":"","firstName":"Melike","middleName":"","lastName":"Cengiz","suffix":""}],"badges":[],"createdAt":"2026-01-12 21:23:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8585355/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8585355/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103177149,"identity":"7e86da3f-03ac-4b7f-93ad-2082fef66a82","added_by":"auto","created_at":"2026-02-22 16:46:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":55476,"visible":true,"origin":"","legend":"\u003cp\u003eCONSORT flow chart\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8585355/v1/69753ba91f5ef0b42a01fb7f.png"},{"id":103177146,"identity":"9d05ba19-5946-4436-8bf4-354e80afd823","added_by":"auto","created_at":"2026-02-22 16:46:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":90592,"visible":true,"origin":"","legend":"\u003cp\u003eCare management algorithm of intensive care patient according to Kolcaba's Comfort Theory\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8585355/v1/79fd4fae1cf3a7e36b455673.png"},{"id":104699349,"identity":"5b5403ff-9093-414c-88d8-ebb2c27b9c9d","added_by":"auto","created_at":"2026-03-16 08:13:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":812041,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8585355/v1/91094a43-e432-4a5f-93f3-31d893080435.pdf"},{"id":103177148,"identity":"afe767a2-0e38-48d7-ad67-20eb40b0b2a4","added_by":"auto","created_at":"2026-02-22 16:46:47","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":223079,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementAconsortchecklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-8585355/v1/03198af8c847970853b30ef6.docx"},{"id":103177147,"identity":"808f5cfc-554e-456e-9b56-275768c8e2e6","added_by":"auto","created_at":"2026-02-22 16:46:47","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":35273,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-8585355/v1/c6b51e0888f9aee16ad17c0b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEffect of Virtual Reality Training on Novice Intensive Care Unit Nurses: A Randomized Controlled Pilot Study\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eIntensive care units (ICUs) represent one of the most demanding environments in healthcare, where nurses must rapidly interpret patient data, operate complex equipment, and make critical decisions under pressure. Novice ICU nurses often experience high levels of stress, difficulty translating theoretical knowledge into practice, and reduced confidence in problem-solving and clinical decision-making\u0026mdash;factors that can jeopardize patient safety and care quality (1).\u003c/p\u003e\n\u003cp\u003eTraditional methods such as lectures, checklists, preceptorships, and mannequin-based simulations, while foundational, often fail to recreate the dynamic nature of ICU scenarios. These approaches can be limited by resource constraints, sporadic availability, and difficulty portraying real-time complexity. As such, newly hired ICU nurses may lack repeated, realistic exposure to high-stakes situations (2).\u003c/p\u003e\n\u003cp\u003eVirtual reality (VR) offers a compelling alternative. VR enables immersive, interactive simulations that replicate ICU environments in a safe, controlled manner. Learners can practice repetitive scenarios, receive immediate feedback, and develop cognitive and psychomotor skills without risking patient harm. Meta-analyses in nursing education demonstrate significant improvements in theoretical knowledge, practical skills, skill retention, and satisfaction (3). A broader systematic review and meta-analysis also reported substantial gains in knowledge, skills, and confidence with VR interventions (3). Additionally, immersive VR has been recognized by nursing educators as an emerging and effective tool in clinical education (4).\u003c/p\u003e\n\u003cp\u003eDespite these promising outcomes, most studies to date have focused on nursing students rather than practicing professionals\u0026mdash;particularly unfamiliar ICU nurses. Recent efforts include a randomized controlled trial using VR for emergency and urgent care training among nurses and students, which showed superior knowledge acquisition and satisfaction compared with traditional learning (5). In another notable study, a 360-degree VR program targeting mechanical ventilation competence among ICU nurses demonstrated significant improvements in clinical reasoning and self-efficacy (6). These findings suggest VR\u0026apos;s potential applicability in real-world ICU contexts, yet randomized controlled trials specifically assessing novice ICU nurses remain few.\u003c/p\u003e\n\u003cp\u003eThere remains a critical gap in evidence regarding the effectiveness VR in enhancing core clinical competencies\u0026mdash;knowledge, clinical performance, problem-solving, and decision-making\u0026mdash;in newly appointed ICU nurses. A rigorous randomized controlled design is necessary to evaluate the added value of VR over standard orientation processes.\u003c/p\u003e\n\u003cp\u003eTo address this, our study employs a randomized controlled design to evaluate the impact of VR-based training on novice ICU nurses across four domains: (1) theoretical knowledge of ICU protocols, (2) clinical performance accuracy in simulated tasks, (3) problem-solving ability in evolving scenarios, and (4) clinical decision-making aligned with evidence-based practice. The intervention group received VR training in addition to standard orientation, and the control group completed standard orientation alone.\u003c/p\u003e\n\u003cp\u003eWe hypothesized that VR training would result in significantly greater improvements across all four domains, and that these gains would be more durable than those of conventional training alone. Demonstrating such benefits could inform ICU onboarding curricula, support the integration of VR into competency development, and ultimately contribute to safer, more prepared critical care teams. Our study aimed to advance the field of immersive learning in nursing by delivering high-quality evidence tailored to the needs of novice ICU professionals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch Hypotheses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH\u003csub\u003e1\u003c/sub\u003e: VR software increases nurses\u0026apos; knowledge level.\u003c/p\u003e\n\u003cp\u003eH\u003csub\u003e2\u003c/sub\u003e: VR software increases nurses\u0026apos; problem-solving skills.\u003c/p\u003e\n\u003cp\u003eH\u003csub\u003e3\u003c/sub\u003e: VR software increases nurses\u0026apos; clinical decision-making skills.\u003c/p\u003e\n\u003cp\u003eH\u003csub\u003e4\u003c/sub\u003e: VR software increases nurses\u0026apos; clinical practice skills.\u003c/p\u003e\n\u003cp\u003eH\u003csub\u003e5\u003c/sub\u003e: VR software reduces nurses\u0026apos; state anxiety levels.\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Design and Methods ","content":"\u003cp\u003eThis study was designed as a parallel-group randomized controlled trial with a 1:1 allocation ratio and a pretest\u0026ndash;posttest design, conducted within a superiority framework.We used the CONSORT reporting guideline (1) to draft this manuscript, and the CONSORT reporting checklist (2) when editing, included in Supplement A (7). The CONSORT flow chart of the study is shown in Figure 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSetting and Sample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe trial was conducted in the ICUs\u0026rsquo; nursing education rooms of a two public hospital in southern T\u0026uuml;rkiye. The intervention and data collection procedures were implemented on-site at the nursing education rooms.\u003c/p\u003e\n\u003cp\u003eThe study population consisted of newly hired nurses in the ICUs of two state hospitals located in southern Turkey (N=150). The study sample was determined using G*Power power analysis. When determining the sample size of the study, the scientific study titled \u0026ldquo;Effect of high-fidelity simulation on clinical decision-making among nursing students\u0026rdquo; by Ayed et al. (8) was used as a basis to determine the sample size for the effect size based on literature reviews. Ayed et al. (8) reported that the mean total score on the Clinical Decision-Making Scale was 148.7 \u0026plusmn; 14.10 in the experimental group and 158.5 \u0026plusmn; 12.60 in the control group (8). Based on these data, the power analysis (G*Power 3.1.9.2) resulted in an effect size = 0.73, 95% confidence interval, 80% power, requiring a total of 62 nurses, with at least 31 in each group. Considering the possibility of dropouts and confounders during the research process, the number in the groups was increased by 10% (9). \u0026nbsp;The sample of the study was determined as a total of 68 nurses, with 34 nurses in each study group. The study was completed with 47 nurses, including 25 nurses in the study group and 22 nurses in the control group. A post-power analysis was performed after data collection. The sample size for the study was determined to as\u0026nbsp;𝑑= 0.1756, and the probability of error \u0026alpha; was accepted as 0.05. Power (1-𝛽\u0026nbsp;error probability) was targeted at 0.80, which represents an 80% probability of obtaining a correct result. The sample distribution between the groups was planned to be equal (N2/N1=1), and the actual power value obtained with this analysis was calculated as 0.8006. This provides a result very close to the predetermined target power. These findings indicate that the target power was achieved with the specified sample size and effect size.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted with nurses who had recently started working in the tertiary ICUs of two hospitals. The criteria for inclusion in the study were: recent graduation from nursing school, recent start of employment in the ICU, no previous experience working in the ICU, and willingness to participate in the study. The criteria for exclusion from the study were: having recently started working in the ICU and subsequently changing job location, leaving the job at any stage of the study, and being a member of a profession other than nursing (e.g., midwife, paramedic). This study was conducted as an educational intervention involving nursing students. Patients and the public were not involved in the design, conduct, reporting, or dissemination of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRandomization and Blinding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNurses meeting the sample selection criteria were randomly and equally distributed into two groups (experimental group, control group) using a computer program, ensuring simple randomization (10). Participants were randomly assigned to the intervention or control group using a simple randomization method with a 1:1 allocation ratio. The random sequence was generated prior to participant enrollment. No stratification or block randomization was applied, as no such restrictions were specified in the registered protocol (NCT05982288). Allocation concealment was ensured by assigning participants to groups after baseline assessments were completed. Allocation concealment was achieved by implementing the randomization sequence after completion of baseline assessments. Group assignments were generated and applied by an independent researcher who was not involved in participant recruitment, intervention delivery, or outcome assessment. The allocation sequence was concealed from participants and instructors until the point of assignment.\u003c/p\u003e\n\u003cp\u003eIn this study, a single-blind method was used to prevent interaction between nurses. Participant enrollment was conducted by the course instructor, who did not have access to the random allocation sequence. Group assignment was performed by an independent researcher responsible for implementing the randomization procedure. The personnel involved in participant enrollment, intervention delivery, and outcome assessment were blinded to the allocation sequence. Blinding of participants and instructors was not possible due to the educational nature of the intervention. Outcome assessors were blinded to group allocation. Both groups received identical course content and practice time, differing only in instructional approach.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection Tools and Methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data for the study were collected using a Sociodemographic Information Form, the Knowledge Level Questionnaire, Clinical Practice Skills Observation Form, Problem-Solving Inventory, Clinical Decision-Making Scale in Nursing, and State Anxiety Inventory (Table 1) (2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplementation of the Study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in four stages:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStage 1:\u0026nbsp;\u003c/strong\u003eAn adult ICU patient case scenario (Table 2) and an ICU patient care management algorithm (Figure 2) based on Kolcaba\u0026apos;s Comfort Theory specific to this scenario, along with training modules, were prepared. Expert opinions were obtained from five specialists in the field (one ICU specialist physician, three ICU nurses, and one nurse academic experienced in ICU nursing) for the prepared scenario and algorithms. Following the expert opinions, the content of the scenario and algorithm was revised (2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStage 2:\u0026nbsp;\u003c/strong\u003eThe modules related to the scenarios and algorithms prepared in the first phase were integrated into the VR software by a computer programmer through a service procurement within the scope of project support and transferred to the VR headset. The VR software was developed using C# Unity technology. Three-dimensional modeling of objects such as characters, environments, floors, machinery, and equipment was performed using the Blender program (2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDetailed medical equipment and intensive care environments were modeled using the Blender program. Substance Painter was used for the textures, enabling the creation of realistic and accurate surface materials. Animations demonstrating medical scenarios and equipment use were created in Blender. The models were added in 3D to the Unity game editor, and C# was used as the programming language.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStage 3:\u0026nbsp;\u003c/strong\u003eNurses who were new to the ICU and met the inclusion criteria received a total of 16 hours of theoretical training over 2 days in a face-to-face setting, delivered by the researchers. PowerPoint presentations were used in the theoretical training, and the content of the training was based on Kolcaba\u0026apos;s Comfort Theory, the ICU patient care management algorithm (Figure 2), and the training module topics (2). After the training, the nurses were randomly assigned to the intervention and control groups. To prevent interaction between the groups, nurses in the intervention and control groups were monitored in the ICUs of two different hospitals during the study period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStage 4:\u0026nbsp;\u003c/strong\u003ePractical training was conducted immediately after theoretical training:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eControl group:\u003c/em\u003e\u003c/strong\u003e Nurses in the control group received routine orientation training in the ICU. Routine orientation training is conducted by the nurse in charge and experienced mentor nurses in the ICU. Nurses new to the ICU work under the supervision of experienced mentors for 5 days from 8 a.m. to 4 p.m. and take on the care management of only one ICU patient whose condition is stable. During this process, the charge nurse also provides orientation training in accordance with the orientation training schedule, covering the ICU environment, the tools and equipment used in the unit, routine care and treatment practices, the functioning of the unit, and duties and responsibilities. The week after the 5-day training, the new nurses begin to take on the responsibility of caring for an ICU patient on their own, working 24-hour shifts with a 2:1 patient-to-nurse ratio.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy group:\u003c/em\u003e\u003c/strong\u003e In addition to the routine ICU orientation training, nurses in the study group were given 15-minute individual training sessions in a virtual environment using VR glasses on patient care management. In accordance with the scenario presented in the VR glasses, nurses applied each module of the scenario and each step of the procedures in the modules individually. A 10-minute pre-briefing on the use of the VR headset was provided before the application. The application was conducted in an empty conference room with area definition in the VR headset. Mentoring was provided by two researchers during the application. After the application, the experiences of each VR headset user were shared in a debriefing session. After each VR application, the VR headset was cleaned and prepared for reuse. The VR headset was recharged every 4 hours. The training in the VR environment was completed in 2 days.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll interventions were delivered by the same instructors to ensure consistency. The duration and content of the training were standardized across groups, with the exception of the technology-enhanced components provided to the intervention group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData analysis was performed using the IBM SPSS Statistics version 26 (IBM Inc., Armonk, NY, USA) software. In the analysis of data, number, percentage, and mean were obtained, then frequency and percentage distributions were calculated. The relationship between variables measured at the categorical level was evaluated using Pearson\u0026rsquo;s Chi-square test. Differences between groups regarding measurements were analyzed using the Mann-Whitney U test, and the difference between measurements was evaluated using the Friedman test. The Bonferroni test was used to determine which group the difference originated from. The significance level was accepted as 0.05. A statistically significant difference was accepted when p was \u0026lt;0.05, and no statistically significant difference was obtained when p was \u0026gt;0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Declaration of Helsinki was followed in the study and the willingness and voluntariness of the nurses to participate in the study were taken into account. Written permissions were obtained from Akdeniz University Medical Sciences Ethics Committee (16/04/2023, permission no. KAEK-250) and Antalya Provincial Health Directorate, Antalya Kepez State Hospital and Antalya City Hospital, where the study was conducted. Written informed consent was obtained from all participants after they were fully informed about the purpose, procedures, potential risks, and benefits of the study. After the study was completed in accordance with ethical principles, the nurses in the control group were also trained in the care management of intensive care patients using VR.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial Registration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u003c/strong\u003e NCT05982288 (Date: 08/07/2023). The study was conducted in accordance with the protocol (2) registered on ClinicalTrials.gov (NCT05982288), and no important changes were made to the trial protocol, pre-specified outcomes, or planned analyses after the study commenced.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe findings of the study are examined in two sections:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1. Nurses\u0026rsquo; characteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSome descriptive characteristics of the nurses participating in the study are given in Table 3. It was determined that the nurses showed a homogeneous distribution in terms of age, sex, marital status, and educational status variables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. Nurses\u0026rsquo; knowledge, problem-solving, clinical decision-making, clinical application skills, and state anxiety levels\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe comparison of the knowledge score averages of the nurses is presented in Table 4. When the measurements between the groups were examined, the difference between the pre-test and the post-test values of the nurses in the study and control groups 1 week and 1 month after the application was not statistically significant (p\u0026gt;0.05). When the measurements within the groups were examined, it was found that the average knowledge scores of the nurses in the study group were similar in consecutive measurements (p\u0026gt;0.05). The average knowledge scores of the nurses in the control group 1 week and 1 month after the application were found to be higher than the measurements before the application (p\u0026lt;0.05; 1\u0026lt;2,3) (Table 4). The comparison of the average problem-solving inventory scores of the nurses is presented in Table 4. The difference between the average PSI scores of pre-test, and 1 week, and 1 month after the application between the groups was not statistically significant (p\u0026gt;0.05). When the within-group measurements were examined, the mean problem-solving inventory scores in the study and control groups 1 month after the application were found to be higher than the measurements before and 1 week after the application (p\u0026lt;0.05; 3\u0026gt;1,2) (Table 4).\u003c/p\u003e\n\u003cp\u003eThe comparison of the mean scores of the nurses on the clinical decision-making scale in nursing is examined in Table 4. When the measurements between the groups were examined, the difference between the pre-test and post-test values of the nurses in the study and control groups 1 month after the application was not statistically significant (p\u0026gt;0.05). However, the measurements of the nurses in the study group 1 week after the application were higher than those in the control group (p\u0026lt;0.05). When the measurements within the groups were examined, it was found that the mean clinical decision-making scores of the nurses in the study group were similar in consecutive measurements (p\u0026gt;0.05). The mean clinical decision-making scores of the nurses in the control group 1 month after the application were found to be higher than the measurements before and 1 week after the application (p\u0026lt;0.05; 3\u0026gt;1,2) (Table 4).\u003c/p\u003e\n\u003cp\u003eThe comparison of the mean state anxiety inventory scores of the nurses is examined in Table 4. When the measurements between the groups were examined, the difference between the pre-test and the post-test values of the nurses in the study and control groups 1 week and 1 month after the application was not statistically significant (p\u0026gt;0.05). When the measurements within the groups were evaluated, the differences between the consecutive measurements in the study and control groups were not statistically significant (p\u0026gt;0.05) (Table 4).\u003c/p\u003e\n\u003cp\u003eThe comparison of the mean scores clinical practice skills of the nurses is examined in Table 4. The difference between the mean clinical practice skill scores of the nurses in the study and control groups was not statistically significant (p\u0026gt;0.05) (Table 4).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study evaluated the effect of VR software on the education of newly recruited intensive care nurses. The research findings revealed significant results regarding the problem-solving skills, clinical decision-making, knowledge levels, and clinical practice skills of the nurses. In terms of knowledge scores, it was observed that the knowledge scores of the nurses in the control group increased significantly 1 week and 1 month after the application. This shows that traditional education methods can be effective in gaining knowledge in the short term. However, the fact that the change in knowledge scores in the study group was not significant may indicate that longer-term and repeated applications may be necessary for the transfer of knowledge of new technologies such as VR. This result does not support the H\u003csub\u003e1\u003c/sub\u003e hypothesis. Contrary to our study, a systematic review reported that VR increased knowledge and skills in nursing education and that there was evidence from related randomized control trials (RCTs) (3). Although prior meta-analyses indicated that VR could improve learner knowledge in nursing education, our study showed no superior knowledge gains in the VR group compared with standard orientation; rather, the control group showed modest post-test increases. This discrepancy may stem from differences in VR content (emphasis on applied decision-making rather than declarative knowledge), measurement sensitivity, or workplace learning influences experienced by controls. Similar heterogeneity in knowledge outcomes has been reported in recent reviews, underscoring the need to align VR learning objectives with assessment tools.\u003c/p\u003e\n\u003cp\u003eAccording to the research findings, the problem-solving inventory scores of the nurses in the study group increased 1 week and 1 month after the application, and this increase was found to be statistically significant especially 1 month after the application, supporting the H\u003csub\u003e2\u003c/sub\u003e hypothesis. Similarly, there are some RCT and quasi-experimental studies showing that VR and virtual simulations improve clinical reasoning and problem-solving (17).\u003c/p\u003e\n\u003cp\u003ePositive effects of 360\u0026deg; VR programs on clinical reasoning and self-efficacy have been reported (6, 18). In the our study, both groups demonstrated improved problem-solving at 1 month, suggesting that orientation plus clinical exposure contributes meaningfully to this competency. Although prior studies have shown VR can accelerate clinical reasoning, our findings indicate that standard training pathways may also yield gains over time; the incremental benefit of VR may depend on scenario design, feedback mechanisms, and exposure time. Future work should compare enriched VR (with structured debrief) versus routine orientation to isolate specific active components.\u003c/p\u003e\n\u003cp\u003eIt was determined that the clinical decision-making skills of the nurses in the study group were higher than those of the nurses in the control group 1 week after the application. With this result, hypothesis H\u003csub\u003e3\u003c/sub\u003e was supported. The literature indicates that generative/immersive VR systems improve clinical decision-making skills (17, 18). The transient superiority of the VR group at 1 week suggests that immersive practice can accelerate initial gains in clinical decision-making. The subsequent rise in control group scores by 1 month points to the powerful role of on-the-job learning and experience. These dynamics mirror recent RCTs showing immediate decision-making benefits from VR that may require reinforcement to persist\u0026mdash;highlighting the importance of blended VR-clinical curricula.\u003c/p\u003e\n\u003cp\u003eAccording to the research findings, no significant difference was found between the clinical practice skill scores of nurses in the study and control groups. Therefore, although the H\u003csub\u003e4\u0026nbsp;\u003c/sub\u003ehypothesis was not supported, simulations and VR software should be used regularly and supported with clinical environments to improve nurses\u0026apos; clinical practice skills.\u003c/p\u003e\n\u003cp\u003eVR applications have been reported to have positive effects on technical skills and clinical performance; however, the magnitude of these effects varies depending on the study (3, 19).\u003csup\u003e\u0026nbsp;\u003c/sup\u003eFurthermore, although AR/VR has been shown to increase learning efficiency in certain specific procedures (CPR, ventilator management, crash cart), results regarding general clinical skills have been found to be heterogeneous (20). Although systematic reviews support the effectiveness of VR for certain procedural skills, we found no between-group differences in overall clinical performance. This may reflect differences in VR content fidelity, exposure time, and outcome measurements. Targeted VR modules for high-priority procedures with objective performance metrics could yield clearer benefits.\u003c/p\u003e\n\u003cp\u003eAccording to the research findings, there was no significant difference in the level of state anxiety between the two groups. Accordingly, the H\u003csub\u003e5\u003c/sub\u003e hypothesis was not supported.\u003c/p\u003e\n\u003cp\u003eSome studies reported positive results regarding the reduction of anxiety during training through simulation and VR (21, 22), but the findings were heterogeneous. Although a reduction in anxiety has been reported among students, the effects among professionals (nurses) are mixed; some studies mention short-term relief, whereas others have shown no significant change (22). We observed no significant changes in state anxiety across the groups. This aligns with mixed evidence: although VR can reduce situational anxiety in student samples, its effect on practicing nurses\u0026rsquo; workplace-related anxiety is inconsistent. Tailoring VR scenarios to include stress-inoculation elements and pairing simulation with reflective debriefing may be necessary to impact anxiety meaningfully.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe fact that the study was conducted at only two hospitals and that most of the nurses assigned to the ICU were already experienced are the most significant limitations that reduced the sample size. Another limitation was that, due to time constraints, the VR application could only be performed once by the working group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRecommendations or Implications for Practice and/or Further Research\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVR-based training should be implemented repeatedly to continuously improve nurses\u0026apos; problem-solving and clinical decision-making skills. Nurses\u0026apos; practice skills should be increased by combining VR simulations with clinical environments (e.g., intensive care, emergency care). VR technologies should be integrated into traditional theoretical training to increase nurses\u0026apos; knowledge levels. More comprehensive and larger sample groups should be conducted, especially on the care management of intensive care patients based on VR.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn the study, it was found that VR software in intensive care patient care management improved problem-solving, clinical decision-making, and knowledge levels in the education of intensive care nurses and also provided high satisfaction. However, the lack of a significant difference in clinical practice skills indicates that more practical experience is needed to develop these skills.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings indicate that VR can contribute to short-term, goal-oriented gains (e.g., decision-making, approach to problem-solving), but traditional orientation and clinical experience also have a strong learning effect. For more meaningful results, repeated VR applications and structured debriefing can be combined. Multi-dimensional performance measurement tools can be used in the evaluation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement:\u003c/strong\u003e Data sharing can be done with permission from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics statement:\u0026nbsp;\u003c/strong\u003eThe Declaration of Helsinki was followed in the study and the willingness and voluntariness of the nurses to participate in the study were taken into account. Written permissions were obtained from Akdeniz University Medical Sciences Ethics Committee (16/04/2023, permission no. KAEK-250) and Antalya Provincial Health Directorate, Antalya Kepez State Hospital and Antalya City Hospital where the study was conducted. Written informed consent was obtained from all participants after they were fully informed about the purpose, procedures, potential risks, and benefits of the study. After the study was completed in accordance with ethical principles, the nurses in the control group were also trained on the care management of intensive care patients using virtual reality software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement:\u0026nbsp;\u003c/strong\u003eWe would like to thank Nurse Cennet Özer for creating the scenarios for the study and shooting the videos, and İsa Şahin for her technical support during the use of the virtual reality glasses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis study was supported by TUSEB (TÜSEB-2022-A9-28103).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial registration:\u0026nbsp;\u003c/strong\u003eProtocol ID: VR_BANUTERZI07; Clinical Trials,gov ID: NCT05982288 (Date: 08/07/2023)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient Consent Statement:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u0026nbsp;\u003c/strong\u003eT)he data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBT, DSD, GU, and NY developed the protocol. BT, HŞ, GE, DSD, NY and MC applicated the study. GU made analysis, BT drafted the manuscript. All authors contributed to and revised the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eKanschik D, Bruno RR, Wolff G, Kelm M, Jung C. Virtual and augmented reality in intensive care medicine: a systematic review. \u003cem\u003eAnn. Intensive Care.\u003c/em\u003e 2023;13:81. doi: 10.1186/s13613-023-01176-z.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eTerzi B, D\u0026uuml;zkaya DS, Uysal G, Yalnız N. A study protocol to develop virtual reality software in the care management of patients in intensive care. \u003cem\u003eNurs Crit Care.\u0026nbsp;\u003c/em\u003e2025;30(4):e13231. doi: 10.1111/nicc.13231.\u003c/li\u003e\n \u003cli\u003eLiu K, Zhang W, Li W, Wang T, Zheng Y. 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G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. \u003cem\u003eBehav Res Methods\u003c/em\u003e. 2007 May;39(2):175-91. doi: 10.3758/bf03193146.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eRandomization.org. Randomization plan generator [Internet]. [cited 2023 Feb 17]. Available from: https://www.randomization.org/\u003c/li\u003e\n \u003cli\u003eHeppner PP, Petersen CH. The development and implications of a personal problem-solving inventory. \u003cem\u003eJournal of Counseling Psychology\u003c/em\u003e. 1982;29(1):66-75. doi: 10.1037/0022-0167.29.1.66.\u003c/li\u003e\n \u003cli\u003eSavaşır I, Şahin NH. Cognitive-Behavioral Therapy Scales Commonly Used in the Assessment. Turkish Psychologists Association Publications, no.9, Ankara. 1997.\u003c/li\u003e\n \u003cli\u003eJenkins H. 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Nurses\u0026rsquo; knowledge and skills after use of an augmented reality app for advanced cardiac life support training: randomized controlled trial. \u003cem\u003eJ Med Internet Res\u003c/em\u003e. 2024;26:e57327. doi: 10.2196/57327.\u003c/li\u003e\n \u003cli\u003eTraister TAA. Virtual reality simulation\u0026rsquo;s ınfluence on nursing students\u0026rsquo; anxiety and communication skills with anxious patients: a pilot study. \u003cem\u003eClinical Simulation in Nursing\u003c/em\u003e. 2023;82:101433. doi: 10.1016/j.ecns.2023.101433.\u003c/li\u003e\n \u003cli\u003eYoon H, Lee E, Kim CJ, Shin Y. Virtual reality simulation-based clinical procedure skills training for nursing college students: a quasi-experimental study. \u003cem\u003eHealthcare (Basel)\u003c/em\u003e. 2024;12(11):1109. doi: 10.3390/healthcare12111109.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 4 are available in the supplementary files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Clinical decision-making, intensive care nurse, problem-solving, state anxiety, virtual reality","lastPublishedDoi":"10.21203/rs.3.rs-8585355/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8585355/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eIt is very important for nurses, who are an indispensable member of the health care team in the intensive care unit, to be equipped with high-level knowledge and skills in patient care management to improve the quality of patient life.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003eThis study aimed to develop virtual reality software for intensive care patient care management and examine the effect of this software on novice recruited intensive care nurses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e The randomized controlled study was conducted with a total of 47 nurses. The data of the study were collected with “Nurse Introductory Information Form”, “Knowledge Level Questionnaire”, “Clinical Practice Skills Observation Form”, “Problem Solving Inventory”, “Clinical Decision Making Scale in Nursing” and “State Anxiety Inventory”\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The mean knowledge scores of the nurses in the control group 1 week and 1 month after the intervention were found to be higher than the pre-intervention measurements (p\u0026lt;0.05). In both groups, the level of problem solving 1 month after the intervention was higher than the measurements before and 1 week after the intervention (p\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e Innovative training methods such as virtual reality contributed positively to the short-term problem-solving skills of nurses, but longer-term or repeated applications may be required to measure clinical decision-making and knowledge levels.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u003c/strong\u003e NCT05982288 (Date: 08/07/2023)\u003c/p\u003e","manuscriptTitle":"Effect of Virtual Reality Training on Novice Intensive Care Unit Nurses: A Randomized Controlled Pilot Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-22 16:46:42","doi":"10.21203/rs.3.rs-8585355/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"89f3bba8-e43c-466b-8866-b32c6e72c6f4","owner":[],"postedDate":"February 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-16T08:12:12+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-22 16:46:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8585355","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8585355","identity":"rs-8585355","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}