Content area
Aim
To design and evaluate a multimodal learning approach with hybrid simulation, combining metaverse-based and real-world elements to strengthen the family-centered partnership competencies of neonatal intensive care unit (NICU) nurses.
BackgroundNICU nurses encounter considerable difficulties in establishing and sustaining strong collaborations with parents, which are crucial for caring for high-risk infants. Therefore, it is important for NICU nurses to develop higher-level partnership competencies to support family-centered care. This study describes the development, implementation and evaluation of a multimodal learning program with hybrid simulation intended to improve NICU nurses’ competency in promoting family-centered partnerships.
DesignThis study used a pre-post quasi-experimental design.
MethodsThis study involved 46 NICU nurses employed at a university hospital in South Korea, assigned to either an experimental or control group. The experimental group participated in a multimodal program combining metaverse-based and real-world simulation sessions aimed at enhancing nurse-parent partnerships, emotional intelligence, problem-solving skills and learning realism.
ResultsThe experimental group showed greater learning realism than the control group (t = 3.73, p = 0.001). However, there were no statistically significant differences between the groups regarding parent-nurse partnership competency, problem-solving skills, or emotional intelligence.
ConclusionsThis program has the innovative potential to enhance nurses’ learning experiences through mulitmdal learning with hybrid simulations combining metaverse. This approach could replace or strengthen existing education methods with comparable efficiency to traditional methods.
The World Health Organization reports that approximately 13.4 million infants were born prematurely in 2020, with preterm birth rates ranging from 4 % to 16 % ( World Health Organization., 2023). High-risk infants face complications like respiratory distress and malnutrition, requiring immediate neonatal intensive care and continuous health management (NICUs) ( Cao et al., 2021; Kim and Kim, 2019). Advancements in medical technology improved survival rates for these newborns, shifting care to include both acute treatment and long-term outcomes, such as emotional stability and attachment ( Cho and Oh, 2023). Parents play a crucial role in the long-term care of high-risk newborns, with support for their understanding and care being vital for managing health ( Yoon et al., 2019; Im and Park, 2024).
A family-centered approach addresses challenges by assessing family and parents’ needs, promoting attachment and providing coping strategies ( Bruns and McCollum, 2002; Lee, 2023; Trajkovski et al., 2016). This care model emphasizes parental involvement in treatment ( Franco Fuenmayor et al., 2024; Cho and Han, 2024) and is fundamental in pediatric nursing ( Bainter et al., 2020; Kuo et al., 2012). In family-centered care, parents and nurses share the goal of optimal health for the infant ( Cho and Oh, 2023). In align with this, partnership enhances parental understanding, reduces anxiety and improves coping ( Cho and Oh, 2023; Heo and Oh, 2019; Dahan et al., 2022). NICU nurses build relationships through understanding and collaboration, supporting early bonding ( Axelin et al., 2014; Maria et al., 2021).
Nurses encourage parental participation and optimal infant care ( Abukari and Schmollgruber, 2023; Toivonen et al., 2020). Their roles as educators and facilitators are crucial, requiring effective communication with parents and fostering parental involvement ( Cho and Han, 2024).
However, initiatives to develop family-centered partnership care competencies are limited, especially the integration of educational programs on emotional intelligence and communication ( Ayed et al., 2021; Cho and Han, 2024). Emotional intelligence is key to partnership formation in healthcare settings ( Mun and Yoo, 2020; Kim et al., 2023). The ability of a nurse to understand and manage their own emotions, as well as maintain a positive mindset, could form the foundation for developing effective parent-nurse partnerships ( Cho and Han, 2024). Enhancing nurses’ empathy through self-awareness is crucial for building therapeutic relationships ( Younas et al., 2020). Existing programs to develop interpersonal competencies show promise but often lack emphasis on experiential self-reflection and mindfulness, which are critical for managing emotions and addressing parents’ needs in the NICU ( Cho and Han, 2024; Egami and Highfield, 2023).
In addition, studies improving family-centered care competency for nurses employ interventions, including each lectures, online workshop, simulations, for better collaboration with parents ( Aloysius et al., 2018; Bry et al., 2016; Heidarzadeh et al., 2023). However, as NICU nursing education mainly relies on unified learning method lide lecture formats, online courses with group discussion. There is a need for diverse educational methods that enhance communication skills through realistic clinical scenarios ( Hasanpour et al., 2017).
Multimodal learning, which combines various instructional techniques, significantly improves the learning experience ( Wolf et al., 2017). Empirical studies indicate that integrating multimodal strategies enhances clinical decision-making and communication skills ( Liaw et al., 2024). Furthermore, incorporating hybrid simulation post-lecture improves pedagogy in nursing education ( Kim, 2023). Engaging multiple senses fosters knowledge retention and critical thinking, preparing learners for modern nursing challenges ( Bloomfield et al., 2013; Govender and Rajkoomar, 2021; Shridhar et al., 2019). Especially, hybrid simulation leverages diverse methods, enhancing learning efficacy by offering immersive experiences ( Lee et al., 2022). This method yields benefits over traditional education, bolstering learners’ communication skills and emotional intelligence ( Alconero-Camarero et al., 2018; Jin and Kang, 2024). Simulation-based training proves more effective in developing self-awareness and empathy compared with conventional lectures ( Ayed et al., 2021). Notably, in NICU nursing, simulation effectively enhances clinical problem-solving skills ( Ji, 2022). The convergent learning approach combines simulation, debriefing and reflective practices ( Kim, 2023) as an educational tool. Paired with metaverse simulation, it enhances learner immersion and interaction ( Çetinkaya Uslusoy et al., 2024), facilitating deeper engagement with emotional and sensory aspects leading family centered partnership ( Brown and Tortorella, 2020). This study defines hybrid simulation as linking offline and metaverse-based simulation to replicate realistic healthcare scenarios.
Nursing education has evolved due to the Fourth Industrial Revolution and COVID-19, advancing remote online education ( Garavand and Aslani, 2022; Moon, 2023; Ryu et al., 2024). Metaverse technologies provide immersive learning in realistic virtual spaces, boosting interactions between instructors and learners and revealing significant pedagogical potential ( Hong, 2021). Empirical evidence shows that such technologies enhance learner motivation and engagement ( Al Khateeb and Alotaibi, 2024).
The term “metaverse” merges “meta,” meaning transcendence and “universe,” referring to the real world. In education, the metaverse is a fused environment using Virtual Reality (VR), Augmented Reality and Mixed Reality with physical educational elements ( Zhang et al., 2022). Educational technologies increasingly advance towards immersive, personalized learning via Extended Reality and AI platforms like Chat GPT ( Guo et al., 2022; Sharma and Sharma et al., 2023). Current nursing education technologies provide high-fidelity digital simulations, enabling integrated theoretical and practical skill training ( Barut et al., 2024). These technologies improve access and cost-effectiveness, reducing geographical barriers and promoting collaborative learning ( Tekin and Çiçek Korkmaz, 2023).
Platforms like ZEPETO, Roblox, Gather Town and ifland cater to diverse learner needs ( Hong, 2021; Jeon et al., 2024). ZEPETO, by Naver Z, notably adds clinical based personalized 3D space to achieve practical learning objectives ( Kang and Moon, 2023), enhancing engagement through physical and conceptual fidelity ( Moon, 2023). ZEPETO goes beyond conventional gamification, focusing on educational goals over entertainment, contrasting traditional gaming ( Moon, 2023). Whereas other platforms implement classroom-like spaces, Zepeto has the advantage of being able to implement real-world clinical practice, including wards and intensive care units, thereby it enables instructors to interact through text chat, voice communication and emojis ( Cho et al., 2024).
Participants represented by avatars engage in challenges within a customized learning space ( Kim and Ahn., 2021). The platform’s gamification features, such as interactive challenges and rewards, motivate learners while meeting training goals. ZEPETO distinguishes itself from other metaverse platforms by emphasizing pedagogical design over virtual space exploration. It enables synchronous interaction among learners, resembling a multiplayer game, facilitating collaborative learning, problem-solving and teamwork. ZEPETO innovatively integrates gamification and metaverse technologies tailored for nursing education ( Cho et al., 2024), allowing social interactions and emotional exchanges within the virtual world and creating a sophisticated model of digital interaction ( Cho et al., 2024).
This research leverages a multimodal learning framework to promote transfer by engaging participants in complex tasks that mirror real-world clinical scenarios and exploring flexible applications of learned competencies ( Choi and Ahn, 2021). This method enhances learner interaction and fosters deep engagement with emotional and sensory aspects of simulated clinical environments ( Brown and Tortorella, 2020).
2 Research aimThis study aimed to develop a family-centered partnership enhancement program for NICU nurses and evaluate its effectiveness using a multimodal learning approach, including hybrid simulations .
2.1 Research hypothesesHypothesis 1
NICU nurses engaged in multimodal learning with hybrid simulation will establish stronger partnerships with parents compared with those who only attend online lectures.
Hypothesis 2
NICU nurses involved in multimodal learning through hybrid simulation will demonstrate greater emotional intelligence than their counterparts who participate in online lectures.
Hypothesis 3
NICU nurses who experience multimodal learning via hybrid simulation will exhibit enhanced problem-solving skills compared with those attending online lectures.
Hypothesis 4
NICU nurses undergoing multimodal learning with hybrid simulation will attain a higher degree of learning realism than those engaged solely in online lectures.
Hypothesis 5
NICU nurses participating in multimodal learning with hybrid simulation will report greater satisfaction with the program compared with those who rely solely on online lectures.
2.2 Conceptual frameworkThe Family-Centered Partnership Competency Enhancement Program for NICU nurses was built on situated learning theory by Lave and Wenger (1991). This approach helps learners reconstruct and apply knowledge through practical tasks relevant to real life, enhancing learning transfer and effective education ( Choi and Ahn, 2021; Lave and Wenger, 1991). The four components of this theory include: (1) Authentic Context; (2) Authentic Activity; (3) Expert Performance and Modeling; and (4) Collaboration. Following this framework, this study’s conceptual structure is as follows: An “authentic context’ was generated through a comprehensive scenario involving parents and nurses in high-risk neonatal discharge interventions, simulating realistic contexts in both real and ZEPETO-based metaverse settings, thus reflecting pediatric clinical environments’ interactions ( Erdei and Liu, 2020; Lee and Ryu, 2021; Murray and Swanson, 2020). For ‘authentic activities,” the program tackles high-risk newborn care situations by incorporating introspection, active listening, empathy training ( Kasat et al., 2019) and simulating experiences in the metaverse. The ‘expert performance and modeling processes’ enable team members to observe and model each other’s skills through structured interactions with instructors ( Hyeon and Oh, 2024). The last component, “collaboration,” allows participants to engage in team activities to find optimal solutions to challenges ( Choi and Ahn, 2021). Fig. 1 depicts the conceptual framework.
2.3 Methods2.3.1 Design
This quasi-experimental study employed a nonequivalent control group pretest-posttest design to assess the development and effect of a multimodal learning program incorporating hybrid simulation on NICU nurses.
2.3.2 ParticipantsThe study sample comprised NICU nurses working at a university hospital in South Korea. The inclusion criteria were as follows: (1) NICU nurses who understood the objectives of the study and voluntarily consented to participate; and (2) those with at least 1 year of experience caring for high-risk newborns in the NICU. This criterion was based on Fegran et al. (2008), who report that at least 1 year of work experience is essential for building effective partnerships with parents, adapting to the critical care environment and gaining sufficient practical experience. Participants who understood the purpose of the study and voluntarily consented were included.
The sample size was calculated using G*Power 3.1.9.7 ( Faul et al., 2009) based on median effect size, a significance level (α) of 0.05 and a statistical power of 0.80. The minimum required sample size was 20 participants. In addition, the post hoc power analysis of the study, based on the actual comparison results of the primary outcome (i.e., nurse-parent partnership), showed a statistical power of 0.8 with an effect size of 0.8 ( Ji, 2022; Yang and Kang, 2022). To account for a potential dropout rate of 10–15 %, participants per group were selected, ultimately, 46 participants(24 in the control group and 22 in the experimental group) completed the program ( Fig. 2).
2.3.3 Intervention developmentThe Analysis, Design, Development, Implementation and Evaluation (ADDIE) model of instructional design ( Molenda., 1996) was followed in this study. The phases include the following.
Analysis phase: A comprehensive literature review was conducted to identify the current state of knowledge on NICU nurse-parent partnerships. Additionally, an in-depth review of prior research on partnership simulation programs and metaverse applications for NICU nurses was conducted, following the program structure and implementation ( Cho et al., 2024).
Design and development phase: A multimodal learning program consisting of seven sessions was integrated based on the literature and identified educational needs ( Cho and Han, 2024). This program consisted of an initial orientation session, followed by seven modules, totaling approximately 4 hours (240 minutes). The program sequence includes the following: (a) a lecture on awareness of family-centered care, (b) self-awareness through personal self-reflection with art therapy, (c) active listening practice, (d) case-based empathy training, (e) group discussions to explore team-based problem-solving strategies using realistic high-risk neonatal care scenarios, (f) simulation performance and debriefing in a metaverse environment and (g) real-world simulation. The training uses a hybrid simulation involving both real-world and metaverse-based simulations that allows for experiential learning, where participants are positioned to recognize relevant context-specific problems and respond as needed with greater perceptual fidelity. Grounded in this learning framework, the program was developed to enhance emotional intelligence, problem-solving skills and parent partnerships while also promoting realism through metaverse-based learning ( Cho et al., 2024; Kim et al., 2023; Kim and Kim, 2019; Manzar, 2023; Mun and Yoo, 2020; Paulsamy et al., 2024; Yu et al., 2021).
In the development phase of the metaverse-based simulation program, the virtual NICU environment was built as a virtual environment using the Build It program from ZEPETO. The NICU platform was designed to offer both indoor and outdoor components, including isolation rooms, patient beds, doctor and nurse rooms and equipment rooms. The outside area included designated spaces for parents and their families. The virtual environment also featured a realistic depiction of essential medical equipment, such as ventilators, incubators, oxygen flow meters, injection pumps, syringe pumps, patient monitors and nurse carts (Supplementary Figure 1). Although direct interaction with medical devices was not possible, the environment provided a visually and audibly immersive experience. This allowed learners to familiarize themselves with the metaverse NICU setting and facilitated effective communication between nurses and parent avatars ( Moon, 2023). The initial program draft was validated and revised through consultations with a NICU nurse, a pediatric nursing professor and a professor specializing in simulation and metaverse program development.
The focus was on preparing premature patients for early discharge in collaboration with parents, ensuring the program’s relevance and applicability to pediatric critical care education. Participants were required to collaborate with virtual patient families and demonstrate family-centered care practices in the scenarios ( Yang and Kang, 2022) (Supplementary Table 1). Scenario validity was assessed by one NICU nurse, a pediatric nursing professor and a professor experienced in metaverse program development, each assigning an item Content Validity Index (I-CVI) score to every item. Only items with an I-CVI score of 0.8 or higher were included in the final version of the program.
During the implementation phase, the program began with an orientation that explained its purpose and procedures. Each participant was required to provide consent before completing the survey. The program consisted of seven sessions ( Table 1).
In the evaluation phase, online questionnaires were used to assess the effectiveness of the program. A pretest, capturing demographic characteristics and variables, was administered just before the intervention, followed by a posttest immediately afterward. The post-program questionnaire for the experimental group included additional self-report items designed to evaluate changes in partnership competency, emotional intelligence, problem solving skill, learning realisim. This included assessing the emotions of participants as parents or nurses during simulation activities, comparing metaverse role-playing with real-life simulation and reflecting on the knowledge and skills acquired throughout the program. Participants in the control group received an online lecture through a designated URL. The 60-minute lecture covered family-centered care topics, including the definition and concept of nurse-parent partnerships, their importance and how to incorporate empathy in communication with parents. Online questionnaires were used to assess the program’s effectiveness, with pre- vs. post-lecture comparisons ( Fig. 3).
2.3.4 Data collectionThis study was approved by the XXX Institutional Review Board. Data were collected between February and March 2024. Participants were recruited from NICUs at a tertiary care hospital. The recruitment document outlined the aim of the study, inclusion criteria, benefits of participation, time commitment and the study procedures. All procedures involving participants followed the guidelines of institutional and national research committees, the Declaration of Helsinki (1964) and its amendments, or equivalent ethical standards. Before participation, all participants were required to sign an informed consent form and complete a 15-minute online self-report questionnaire. To ensure anonymity and privacy, participants were assigned unique serial numbers and all data were coded systematically. Throughout the study, participants were informed of their rights, including privacy, confidentiality, voluntary participation and the right to withdraw at any time. On completion, participants received tokens of appreciation.
2.4 Measurements2.4.1 Nurse-parent partnership
The nurse-parent partnership was evaluated using Choi and Bang’s (2013) self-report instrument, which includes 34 items across seven domains: cautiousness, sensitivity, reciprocity, professional knowledge and skill, collaboration, information sharing and communication. Each item was scored on a 5-point Likert scale (1 = not at all, 5 = very much).
An example of a measurement item is: “The parent and I share information about the child.” A higher score indicates a stronger perceived level of partnership among nurses. In Choi and Bang’s (2013) study, the tool had a Cronbach’s α reliability coefficient of 0.96, while in this study, it had a reliability coefficient of 0.90.
2.4.2 Emotional intelligenceEmotional intelligence was assessed using the Wong and Law Emotional Intelligence Scale (WLEIS), initially developed by Wong and Law (2002) and later translated by Lim (2004). This 16-item instrument covers four domains: self-emotion appraisal, appraisal of the emotions of others, emotion regulation and the use of emotion. Each item was rated on a 7-point Likert scale (1 = not at all, 7 = very much). Sample items included statements such as “I am good at observing other people’s emotions.” Higher scores indicate a greater level of emotional intelligence. The tool demonstrated reliability, with Cronbach’s α ranging from 0.83 to 0.90 in Lim’s (2004) study and 0.87 in this study.
2.4.3 Problem-solving abilityProblem-solving ability was evaluated using the Korea Problem Solving Process Inventory (KPSP), developed by Lee et al. (2008). This 30-item instrument covered five domains: problem clarification, solution seeking, decision-making, solution application and evaluation and reflection. Each item was rated on a 5-point Likert scale (1 = very influential, 5 = not influential at all). Sample items included statements such as, “When faced with a problem, I first think deeply about the issue that needs to be solved.” Higher scores reflected stronger problem-solving ability. The tool showed reliability, with a Cronbach’s α of 0.93 in Lee et al.’s (2008) study and 0.94 in this study.
2.4.4 Learning realismLearning realism was measured using an instrument adapted by Park (2021) from the original tool developed by Kang et al. (2008). This 24-item instrument covered three domains: cognitive, emotional and social authenticities. Each item was scored on a 5-point Likert scale (1 = strongly negative, 5 = strongly positive). Sample items included statements such as, “I felt that I had a close relationship with my fellow students during distance learning.” Higher scores indicate a greater level of learning realism. In Park’s (2021) study, Cronbach’s α ranged from 0.81 to 0.88 across the domains, while in this study, the overall Cronbach’s α was 0.92.
2.4.5 Program satisfactionProgram satisfaction was assessed using an instrument developed by Yu and Yang (2022). This three-item tool uses a 5-point Likert scale (1 = not at all, 5 = very much). Sample items included statements such as, “This education program will be helpful for nurses working in the NICU.” Higher scores indicate greater satisfaction with the training. In Ryu and Yu., (2023) study, the instrument had a Cronbach’s α of 0.84, whereas in this study, the Cronbach’s α was 0.77.
2.5 Statistical analysisStatistical analyses were conducted using SPSS Statistics for Windows, version 29 (IBM Corp., Armonk, NY, USA), with all tests employing two-sided p-values and a significance level of 5 % (α = 0.05). Descriptive statistical analyses were performed to characterize the demographics of the participants and evaluate the distribution of variables, encompassing frequency, mean, standard deviation (SD) and percentage. Normality assumptions were rigorously examined by assessing skewness and kurtosis. Chi-square tests and independent t-tests were used to assess the homogeneity of participant characteristics and variables. Independent t-tests were employed to (a) verify the homogeneity of key variables before and after the intervention, (b) identify inter-group variations in post-intervention scores and (c) quantitatively assess the statistical significance of between-group changes from pre-intervention to post-intervention. Cronbach’s α coefficient, a standard metric for assessing reliability, was used to evaluate the internal consistency and reliability of the measurement instrument.
3 Results3.1 Homogeneity comparisons between intervention and control groups
The skewness values ranged from −0.99 to 0.54 and kurtosis values ranged from −1.14 to 2.08, confirming that the data satisfied normality assumptions. Table 2 details the general characteristics and baseline homogeneity of participants in the intervention and control groups. No statistically significant differences were observed between the groups regarding age, marital status, number of children, education level, religious affiliation, job position, clinical experience, departmental tenure, or familiarity with family-centered care. Table 3 shows the baseline homogeneity of the dependent variables, indicating no significant differences between the experimental group and control group in nurse-parent partnership, emotional intelligence, problem-solving ability, or learning realism.
3.2 Effects of the NICU Nurse Partnership Competency Enhancement Program for Family-Centered CareTable 4 presents the program’s effects on nurse-parent partnership, emotional intelligence, problem-solving ability, learning realism and program satisfaction. Hypothesis 1
Nurse-parent partnership
Posttest results showed a significant improvement in the nurse-parent partnership for the experimental group (t = 5.09, p < 0.001) and the control group (t = 7.29 , p < 0.001). Analysis of the seven subdomains of nurse-parent partnership revealed no significant increase in cautiousness (t = 0.74, p = 0.464) for both groups. However, significant improvements were observed in collaboration (t = −1.15, p = 0.256), communication (t = 1.42, p = 0.163), sharing information (t = 1.68, p = 0.100), reciprocity (t = −0.25, p = 0.808), professional knowledge and skills (t = −0.97, p = 0.337) and sensitivity to practice (t = −0.17, p = 0.864). Despite these increases, no statistically significant difference was observed between the two groups in overall nurse-parent partnership (t = 0.08, p = 0.934) ( Table 4). Hypothesis 2
Emotional intelligence
Analysis of the alterations in emotional intelligence before and after the simulation program revealed significant increases in the experimental group (t = 3.31, p = 0.003) and the control group (t = 5.57, p < 0.001). However, the magnitude of the increase did not significantly differ between the two groups (t = −0.38, p = 0.703) ( Table 4). Hypothesis 3
Problem-solving ability
Analysis of changes in problem-solving ability before and after the simulation program revealed significant increases in the experimental group (t = 3.63, p = 0.002) and the control group (t = 5.81, p < 0.001). Nonetheless, the difference in improvement between the two groups was not statistically significant (t = 0.02, p = 0.986) ( Table 4). Hypothesis 4
Learning realism
Both groups demonstrated an increase in their sense of presence; however, the experimental group showed a significantly greater increase (1.16) than that of the control group (0.57). This increase in the sense of presence was statistically significant (t = 3.73, p = 0.001). Thus, a significant difference in learning realism was observed between the experimental group and the control group, resulting in the acceptance of Hypothesis 4 (t = 3.73, p = 0.001). Analysis of the subdomains revealed significant increases in cognitive and emotional learning realism for both groups, although the magnitude of the increase did not differ significantly. Nevertheless, the experimental group showed higher increases in these subdomains. In contrast, social learning realism remained unchanged in the control group but significantly increased in the experimental group (t = 6.32, p < 0.001). The degree of this increase was also significantly greater in the experimental group (t = 4.60, p < 0.001) ( Table 4). Hypothesis 5
Program satisfaction
The average program satisfaction scores for the experimental and control groups following the NICU Nurse Partnership Competency Enhancement Program for family-centered care using hybrid simulation were 4.18 and 4.03, respectively. No significant difference was observed in program satisfaction between the two groups (t = 1.37, p = 0.177) ( Table 4) ( Fig. 4).
4 DiscussionThis study, based on situated learning theory by Lave and Wenger (1991), was implemented to enhance practical learning for NICU nurses through a multimodal family-centered care learning approach to improve partnerships with parents was evaluated.
In the experimental group, the nurse-parent partnership score increased; however, no statistically significant difference was observed when compared with the control group. Situated learning theory posits that learning is most effective in context-rich, authentic environments that mimic real-world scenarios ( Lave and Wenger, 1991). Despite the multimodal learning program’s goal to replicate the NICU environment, the levels of immersion and situational relevance may not have been sufficient to fully engage participants, having an impact on their ability to apply the learning within the complex dynamics of the nurse-parent partnership, especially considering their existing clinical experience ( Vargas-Porras et al., 2021). Future interventions should integrate more authentic components, such as organized shadowing experiences or workshops that involve parents as educators. Additionally, repeated practice, feedback and reflection could enhance the internalization of approaches. Hybrid models can bridge the virtual and practical learning divide through metaverse simulations. Engagement and authenticity can be further improved using advanced virtual reality technology, AI-driven patient avatars and dynamic interactive scenarios ( Yilmaz and Yilmaz, 2023).
Comparing these results is challenging due to the lack of identical studies and this program lasted approximately 240 minutes, which may have been insufficient for learners to fully internalize and consistently apply the skills or to develop long-term competencies in forming partnerships with parents. The limited duration may not have allowed enough time for the maturation of partnership-related competencies.
Future partnership programs must allow learners to develop expertise and include long-term follow-up assessments. Hengeveld et al. (2021) emphasize the need for initial and ongoing educational support and hospital-based curricula to equip nurses for family-centered care. Implementing educational programs that integrate family-centered care concepts—such as participation, information sharing, collaboration and respect—will be vital for enhancing nurses’ attitudes toward this approach (). While simulated learning effectively builds early skills, it may lack the depth of real-life interactions in the NICU. As per situated learning theory, practical learning could improve through direct engagement with stakeholders ( Lave and Wenger, 1991).
Additionally, no significant difference in emotional intelligence between groups post-intervention may result from factors such as high pre-existing emotional intelligence among participating nurses, given the advanced skills required in NICU work. Moreover, the intervention’s insufficient duration and intensity might have limited its effectiveness in enhancing emotional intelligence, which typically requires prolonged practice and reflection.
Understanding learning processes and intervention impacts is essential for designing effective training ( Lave and Wenger, 1991). Recent evidence shows that learning styles evolve with new experiences (Çetinkaya et al., 2024). Situated Learning Theory highlights that learning is a social process within authentic contexts and community engagement ( Lave and Wenger, 1991). Complementary interventions, like mindfulness and stress management, could enhance emotional regulation and resilience, aiding nurses in high-pressure situations ( Slatyer et al., 2018). These strategies offer a framework for improving emotional intelligence and teamwork, leading to better patient care quality.
Problem-solving abilities notably increased in the intervention group, yet no significant difference was found between the intervention and control groups. Factors explaining this lack of significant improvement involve education length; Kim et al. (2015) report that 2–6 hours enhances fragmented knowledge and skills, but at least 4 weeks of simulation-based education is needed for real improvement. Studies by Kang and Moon (2023) and Moon (2023) echo these findings, showing that short-term case analysis and simulation struggle to effectively develop problem-solving skills. Individual learning styles and prior experiences also affect how nurses benefit from training ( Kolb, 1984), underscoring the need for targeted, prolonged, individualized interventions. More sensitive assessment tools might be necessary to detect subtle improvements in problem-solving skills. To boost nurses’ problem-solving capabilities, a comprehensive approach using multiple evidence-based strategies is essential. This should involve critical thinking and decision-making training through case-based learning, collaborative learning and interdisciplinary teamwork, exposing nurses to various perspectives ( Kanbay and Okanlı, 2017; Kim. 2022; Yeung et al., 2023; Yoo and Park, 2014).
Reflective practice sessions and peer support groups would further enhance this process, allowing participants to build knowledge and refine their skills collaboratively. Continuous education and professional development are vital for keeping nurses current with evidence-based practices, while reflective practice and mentorship support ongoing growth, fostering advanced problem-solving skills ( Benner, 2001; Chang et al., 2011; Reeves et al., 2017).
that Learning realism significantly differed between the experimental and control groups, showing that this program positively influenced it. Metaverse platforms offer diverse educational opportunities, with user experiences varying based on readiness and platform features ( Hwang and Chien, 2022). Jeon et al. (2024) found nurses had higher immersion and better perceptions than nursing students in metaverse experiences. Participants—NICU nurses with over a year of clinical experience—likely exhibited high learning realism due to their experience, prior knowledge and practical activities in metaverse-based simulations. These simulations were designed to mimic actual NICU environments, potentially enhancing learning realism by providing familiar and credible settings.
5 LimitationsThese findings should be interpreted with caution. First, as we did not include nurses from a wide range of hospitals across the country, the sample population was lack of diversity. The experiences and challenges faced by NICU nurses may vary considerably depending on the institutional context, regional healthcare practices and availability of resources. Thus, future studies should focus on recruiting samples from nationwide institutional settings to improve generalizability. Second, as this study found effects immediately after the intervention, a longitudinal study is needed to examine how NICU nurses perceive the long-term partnership.
6 ConclusionThe multimodal learning program with hybrid simulation program, integrating metaverse and real-world simulations were developed to enhance the partnership competencies of NICU nurses. This program showed significant improvements in the learning realism of participants.
However, there was no significant differences between the experimental and control groups. Nevertheless, This study is significant in that a multimodal learning method and an innovative and challenging metaverse space reflecting high risk neonatal nursing practice were used to enhance family-cenered partnership competencies of NICU nurses. It could be used in nursing students for pediatric nursing education. Based on this study, when developing program taking into account individual differences in learners' learning styles and previous experience of the metaverse will be necessary for more personalised and effective interventions that can be used in continuing education for neonatal nurses in pediatric field.
AbbreviationsNICUs, neonatal intensive care units; FCC, family-centered care; EI, emotional intelligence; VR, virtual reality; SLT, Situated Learning Theory; I-CVI, Content Validity Index; AI, artificial intelligence
Ethical approvalThis study was approved by the Chonnam National University Institutional Review board (CNUH-2024–018). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consentWritten informed consent was obtained from all individual participants included in the study.
FundingThis work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government ( MSIT) (No. NRF- 2021R1G1A1004920).
CRediT authorship contribution statementKim Hee Young: Writing – original draft, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Myung Soon Hyun: Writing – original draft, Investigation, Formal analysis, Data curation, Conceptualization. Cho In Young: Writing – review & editing, Writing – original draft, Visualization, Validation, Funding acquisition, Formal analysis, Data curation, Conceptualization.
Authorship statementHee young Kim was the principle investigator of this research project. In Young Cho, Soon Hyun Myung contributed to the writing and reviewing of the manuscript. In Young Cho contributed to the study design, data collection and analysis, and wrote and revised the manuscript. All authors have read and approved the final manuscript.
Declaration of Competing InterestThe 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.
AcknowledgmentsWe would like to thank Essay Review for English language editing.
Appendix A Supporting informationSupplementary data associated with this article can be found in the online version at doi:10.1016/j.nepr.2025.104294.
Appendix A Supplementary materialSupplementary material
| | | | | |
| 1 | | Understanding FCC | | • Lecture |
| 2 | | Self-awareness
/ Introspection | | • Individual activity
• Group sharing experience |
| 3 | | Active listening practice
/Recognizing differing perspectives through observation, listening and speaking | [Activity 1]
[Activity 2] | • Group activity |
| 4 | | Empathy training / Giving and receiving empathy | | • Group activity |
| 5 | | Practical scenario analysis | | • Group activity
• Roleplay |
| 6 | | Metaverse simulation | ● Using avatars in a metaverse environment to simulate nurse-parent interactions
● Debriefing participants on their experiences | • ZEPETO-based metaverse simulation
• Sharing experience |
| 7 | | Offline practical
simulation | ● Execute real-life simulated scenarios
● Debriefing to reflect on experiences | • Real simulation
• Sharing experience |
| Characteristics | Categories | Total N (%) | Group | | ||||
| Experimental (n = 22) | Control (n = 24) | |||||||
| Mean ± SD | 29.61 ± 4.76 | 30.14 ± 4.16 | 29.13 ± 5.29 | 0.478 | ||||
| Age (years) | 20–29 | 28 | (60.9) | 12 | (54.5) | 16 | (66.7) | 0.492 |
| 30–39 | 15 | (32.6) | 9 | (40.9) | 6 | (25.0) | ||
| ≥ 40 | 3 | (6.5) | 1 | (4.5) | 2 | (8.3) | ||
| Marital status | Unmarried | 40 | (87.0) | 19 | (86.5) | 21 | (87.5) | 0.909 |
| Married | 6 | (13.0) | 3 | (13.6) | 3 | (12.5) | ||
| Children | Yes | 5 | (10.9) | 2 | (9.1) | 3 | (12.5) | 0.711 |
| No | 41 | (89.1) | 20 | (90.9) | 21 | (87.5) | ||
| Education | University | 37 | (80.4) | 16 | (72.7) | 21 | (87.5) | 0.302 |
| RN-BSN | 4 | (8.7) | 2 | (9.1) | 2 | (8.3) | ||
| Graduate school | 5 | (10.9) | 4 | (18.2) | 1 | (4.2) | ||
| Religion | Christian | 7 | (15.2) | 2 | (9.1) | 5 | (20.8) | 0.464 |
| Buddhism | 1 | (2.2) | 1 | (4.5) | 0 | (0.0) | ||
| Catholic | 3 | (6.5) | 1 | (4.5) | 2 | (8.3) | ||
| None | 35 | (76.1) | 18 | (81.8) | 17 | (70.8) | ||
| Position | Responsible nurse | 1 | (2.2) | 0 | (0.0) | 1 | (4.2) | 0.333 |
| General nurse | 45 | (97.8) | 22 | (100.0) | 23 | (95.8) | ||
| Clinical career (years) | Mean ± SD | 6.94 ± 4.81 | 7.27 ± 4.32 | 6.65 ± 5.30 | 0.666 | |||
| Departmental career
(years) | Mean ± SD | 5.55 ± 3.99 | 5.65 ± 3.77 | 5.47 ± 4.26 | 0.884 | |||
| Awareness of
family-centered nursing | Yes | 23 | (50.0) | 9 | (40.9) | 14 | (58.3) | 0.238 |
| No | 23 | (50.0) | 13 | (59.1) | 10 | (41.7) | ||
| Variables | Group | t | | |||
| Experimental (n = 22) | Control (n = 24) | |||||
| Mean ± SD | Mean ± SD | |||||
| | 3.76 ± 0.41 | 3.94 ± 0.34 | −1.60 | 0.117 | ||
| Cautiousness | 4.41 ± 0.68 | 4.35 ± 0.54 | 0.30 | 0.763 | ||
| Sensitivity | 4.02 ± 0.51 | 4.15 ± 0.39 | −0.92 | 0.361 | ||
| Reciprocity | 3.83 ± 0.52 | 4.00 ± 0.40 | −1.23 | 0.226 | ||
| Professional knowledge and skill | 3.85 ± 0.48 | 3.91 ± 0.40 | −0.46 | 0.646 | ||
| Collaboration | 4.08 ± 0.49 | 4.01 ± 0.44 | 0.45 | 0.657 | ||
| Sharing information | 2.91 ± 0.86 | 3.49 ± 0.77 | −2.40 | 0.021 | ||
| Communication | 3.17 ± 0.63 | 3.64 ± 0.53 | −2.72 | 0.009 | ||
| | 4.82 ± 0.64 | 5.08 ± 0.60 | −1.39 | 0.171 | ||
| | 3.69 ± 0.44 | 3.71 ± 0.50 | −0.12 | 0.909 | ||
| | 3.38 ± 0.48 | 3.46 ± 0.47 | −0.55 | 0.584 | ||
| Cognitive learning realism | 3.01 ± 0.51 | 3.32 ± 0.64 | −1.85 | 0.071 | ||
| Emotional learning realism | 3.48 ± 0.49 | 3.44 ± 0.53 | 0.30 | 0.769 | ||
| Social learning realism | 3.60 ± 0.77 | 3.61 ± 0.61 | −0.33 | 0.972 | ||
| Experimental group (n = 22) | Control group (n = 24) | t(
| |||||||
| Mean ± SD | Pre-post
t ( | Mean ± SD | Pre-post
t( | ||||||
| Pretest | Posttest | Pretest | Posttest | ||||||
| | 3.76 ± 0.41 | 4.24 ± 0.44 | 5.09 (<0.001) | 3.94 ± 0.34 | 4.41 ± 0.45 | 7.29 (<0.001) | 0.08
(0.934) | ||
| Cautiousness | 4.41 ± 0.68 | 4.52 ± 0.63 | 0.77 (0.448) | 4.35 ± 0.54 | 4.33 ± 0.69 | −0.19 (0.852) | 0.74
(0.464) | ||
| Sensitivity | 4.02 ± 0.51 | 4.40 ± 0.46 | 3.47 (0.002) | 4.35 ± 0.54 | 4.55 ± 0.42 | 4.58 (<0.001) | −0.17
(0.864) | ||
| Reciprocity | 3.83 ± 0.52 | 4.19 ± 0.51 | 2.59 (0.017) | 4.00 ± 0.40 | 4.39 ± 0.54 | 4.81 (<0.001) | −0.25
(0.808) | ||
| Professional knowledge skill | 3.85 ± 0.48 | 4.23 ± 0.59 | 3.01 (0.071) | 3.91 ± 0.40 | 4.43 ± 0.48 | 6.96 (<0.001) | −0.97
(0.337) | ||
| Collaboration | 4.08 ± 0.49 | 4.32 ± 0.54 | 2.35 (0.029) | 4.01 ± 0.44 | 4.42 ± 0.45 | 4.28 (<0.001) | −1.15
(0.256) | ||
| Sharing information | 2.91 ± 0.86 | 3.94 ± 0.62 | 6.65 (<0.001) | 3.49 ± 0.77 | 4.17 ± 0.64 | 4.87 (<0.001) | 1.68
(0.100) | ||
| Communication | 3.17 ± 0.63 | 4.19 ± 0.56 | 6.83 (<0.001) | 3.64 ± 0.53 | 4.42 ± 0.48 | 8.86 (<0.001) | 1.42
(0.163) | ||
| | 4.82 ± 0.64 | 5.33 ± 0.84 | 3.31 (0.003) | 5.08 ± 0.60 | 5.65 ± 0.72 | 5.57 (<0.001) | −0.38
(0.703) | ||
| | 3.69 ± 0.44 | 4.17 ± 0.52 | 3.63 (0.002) | 3.71 ± 0.50 | 4.19 ± 0.46 | 5.81 (<0.001) | 0.02
(0.986) | ||
| | 3.38 ± 0.48 | 4.55 ± 0.45 | 10.00 (<0.001) | 3.46 ± 0.47 | 4.03 ± 0.54 | 5.24 (<0.001) | 3.73
(0.001) | ||
| Cognitive learning realism | 3.01 ± 0.51 | 4.46 ± 0.51 | 10.23 (<0.001) | 3.32 ± 0.64 | 4.35 ± 0.49 | 6.24 (<0.001) | 1.93
(0.059) | ||
| Emotional learning realism | 3.48 ± 0.49 | 4.49 ± 0.47 | 8.28 (<0.001) | 3.44 ± 0.53 | 4.19 ± 0.53 | 7.61 (<0.001) | 1.63
(0.110) | ||
| Social learning realism | 3.60 ± 0.77 | 4.68 ± 0.54 | 6.32 (<0.001) | 3.61 ± 0.61 | 3.57 ± 0.79 | −0.24 (0.812) | 4.60
(<0.001) | ||
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