Content area
Aim
To synthesise recent evidence on the characteristics and effectiveness of simulation to support development of final-year undergraduate nursing students’ critical thinking.
Background
Critical thinking is fundamental to safe, effective nursing practice, particularly for final-year students transitioning to autonomous roles. Simulation-based education is widely used to foster critical thinking, yet simulation has transformed considerably in the last five years.
Design
Mixed method systematic review.
Methods
Primary studies published from 2019 to 2025 were searched across MEDLINE, EMBASE, CINAHL Complete, ERIC and SCOPUS. Eligible studies reported on final-year nursing students’ critical thinking outcomes following simulation participation. Methodological quality was appraised using the Mixed Methods Appraisal Tool. Data were integrated using convergent narrative synthesis.
Results
Eighteen studies were analysed and synthesised to present the simulation interventions, critical thinking measures and outcomes according to simulation modality. Five simulation intervention modalities were used: standardised patient (5), high-fidelity (3), low-fidelity (1), virtual-reality (5) and mixed-reality (2). Eleven critical thinking measures were used, most commonly Yoon’s Critical Thinking Disposition Scale. Most studies (n = 14) found simulation enhanced students’ critical thinking. Standardised patient, virtual and mixed reality simulations positively influenced critical thinking and high and low fidelity showed mixed results. The modality’s fidelity level did not predict effectiveness .
Conclusion
Various simulation modalities can support development of final-year nursing students’ critical thinking particularly when incorporating structured debriefing. When designing simulation, educators should look beyond fidelity and intentionally align modality with learning goals. More longitudinal and qualitative research is needed to better understand simulations’ impact on final-year nursing students’ critical thinking.
1 Introduction
The concept of critical thinking is well discussed in nursing literature, with most authors claiming that critical thinking is necessary to ensure clinical competence. A nurse’s capacity to analyse and interpret patient data, anticipate outcomes and respond quickly and appropriately is essential for safe quality patient care ( Nabizadeh-Gharghozar et al., 2021; Willers et al., 2021). As the ability to think critically can improve outcomes for the patient, it is imperative to integrate critical thinking skill development into nursing curricula to prepare future nurses for safe practice ( Lee and Oh, 2020; Parker, 2021).
1.1 Defining critical thinking
Critical thinking has been subjected to a myriad of definitions over time with one of the most widely cited foundational definitions proposed by Facione ( Facione, 2015). First published in 1992, Professor Facione, Dean of the College of Arts and Sciences and the Graduate Division of Counselling Psychology and Education, Santa Clara University from 1996 to 2001, described critical thinking as purposeful, self-regulatory judgement that facilitates the processes of interpretation, analysis, evaluation and inference ( Facione, 2015). His distinguished body of work in decision-making, critical thinking and collaborative leadership has been extended across numerous disciplines ( Facione et al., 1994). Building on this educational foundation, Scheffer and Rubenfeld ( Scheffer and Rubenfeld, 2000) led an expert panel that developed a more comprehensive nursing-specific conceptualisation of critical thinking which identified both cognitive and affective components, often referred to as dispositions.
Specifically, the panel delineated seven core cognitive skills: analysing, applying standards, discriminating, information seeking, employing logical reasoning, predicting and transforming knowledge, alongside ten 'habits of mind' that represent the disposition ( Scheffer and Rubenfeld, 2000). These affective components include confidence, contextual perspective, creativity, flexibility, inquisitiveness, intellectual integrity, intuition, open-mindedness, perseverance and reflection, reflecting the complexity and multidimensional nature of critical thinking in nursing practice ( Scheffer and Rubenfeld, 2000). More recently, Papp et al. (2014) broadened the definition further describing critical thinking as “the ability to apply higher-order cognitive skills (conceptualisation, analysis, evaluation) and the disposition to be deliberate about thinking (being open-minded or intellectually honest) that lead to action that is logical and appropriate” (p.716).
1.2 Assessing critical thinking capacity
Due to the complex nature of critical thinking, assessing a student’s ability to think critically can prove challenging. Validated instruments designed to measure critical thinking abilities encompass varying elements of both the cognitive skills and the dispositional attributes of nursing students, aiming to capture a more comprehensive picture of their critical thinking capacity during assessment. For example, the California Critical Thinking Skills Test (CCTST) ( Facione, 1990) and Health Sciences Reasoning Test (HSRT) ( Facione and Facione, 2006) measure core cognitive skills, whilst the California Critical Thinking Disposition Inventory (CCTDI) ( Facione and Facione, 1992) and the Yoon’s Critical Thinking Disposition Scale (YCTDS) ( Yoon, 2008) measure critical thinking disposition.
Furthermore, critical thinking is described in the literature using a variety of overlapping and, at times, interchangeable terms. It is frequently embedded in or associated with broader constructs such as clinical judgment, clinical reasoning, decision-making, problem-solving and clinical competence. While these terms are conceptually distinct, they often share underlying cognitive and affective processes characteristic of critical thinking. Thus, the teaching and assessment of critical thinking often integrates related constructs.
1.3 Developing critical thinking in students
Research suggests that advanced critical thinking skills are required for the processes of problem-solving and clinical decision-making ( Lee and Oh, 2020; Parker, 2021). The development of critical thinking is particularly important in final-year nursing students as they prepare to transition from supervised learning environments into autonomous professional practice. As new graduates are expected to make timely, evidence-based decisions in complex and unpredictable clinical settings, a well-developed capacity for critical thinking underpins safe and effective care ( Willers et al., 2021). The ability to analyse information, prioritise interventions and reflect on clinical outcomes is essential for sound clinical judgment and decision-making ( Nabizadeh-Gharghozar et al., 2021). Without strong critical thinking skills, novice nurses may struggle to manage the demands of real-world practice, highlighting the need for nursing curricula to intentionally foster and assess this competency prior to graduation ( Lee and Oh, 2020; Parker, 2021).
1.4 Simulation as a strategy to foster critical thinking
While a variety of learning activities have been integrated in nursing curricula to support development of nursing students’ critical thinking skills, simulation is commonly discussed in the literature ( Cant and Cooper, 2017; Theobald et al., 2021). Simulation is an experiential, interactive, collaborative and learner-centred educational approach whereby students engage in guided, scenarios that replicate real-life clinical situations in a safe, controlled environment ( Al Gharibi et al., 2021; Jeffries, 2021). Consistent with Jeffries’ Simulation Theory ( Facione et al., 1994), simulation-based learning is understood as a dynamic, multi-stage process rather than a single event, typically encompassing preparation, prebrief, simulation, debrief and application. Each stage is designed to scaffold, allowing learners to apply knowledge, refine psychomotor skills and practice decision-making without the risk of harming actual patients, thereby promoting experiential learning, reflective practice and critical thinking ( Al Gharibi et al., 2021; Jeffries, 2021).
Approaches to simulation, designed to foster critical thinking, may encompass low-fidelity or high-fidelity manikin-based scenarios, standardised patient interactions, virtual and augmented reality environments and computer-assisted simulation (
Abbas et al., 2023; Alshehri et al., 2023; Frost et al., 2020; Massoth et al., 2019; Nestle et al., 2010). These modalities vary in realism, interactivity and technological complexity, yet each offers unique opportunities to support cognitive skill development scenarios (
Alshehri et al., 2023). Simulation modality definitions are presented in
In the last five years, the landscape of simulation-based education in nursing has undergone notable transformation. This shift has been largely driven by emerging technologies and the global impact of the COVID-19 pandemic, which served as a significant catalyst for innovation in healthcare education ( Dhaussy et al., 2024; Orgill et al., 2024). The global pandemic created an urgent but favourable environment for new simulation development, including pop-up simulations for managing COVID-19 patient intubation as well as the shift from face-to-face to online learning that occurred due to isolation restrictions ( Dhaussy et al., 2024; Orgill et al., 2024). As traditional clinical placements became limited or inaccessible, educators were compelled to adopt and expand alternative learning modalities, leading to increased integration of virtual simulation, mixed reality, augmented reality and web-based simulation platforms ( Dhaussy et al., 2024; Mohamed et al., 2024). These contemporary approaches have not only broadened access but also introduced new ways of engaging students in safe, repeatable and authentic clinical experiences.
This period of rapid change has positioned simulation as a dynamic and essential component of nursing education. The development of more sophisticated digital technologies has allowed for greater realism, interactivity and scalability of simulations, making them increasingly appealing for both educators and learners ( Abbas et al., 2023). High-fidelity simulations continue to evolve, but they are now complemented by immersive virtual platforms and holographic patients, which further enhance opportunities for students to practice critical thinking in diverse, complex scenarios ( Alshehri et al., 2023).
Despite the growing use of simulation to support clinical skill development, its application specifically in supporting critical thinking remains underexplored in many contexts. While simulation is frequently cited as a pedagogical strategy to enhance critical thinking, following initial systematic searches of peer reviewed literature, there is an absence of published systematic reviews in the last five years which identifies and integrates more sophisticated simulation types such as VR, MR and AR , in relation to final-year nursing students’ critical thinking. A focus on final-year nursing students addresses the critical juncture between undergraduate education and the transition to autonomous professional practice. The final-year of study (i.e. third year of a three-year degree, fourth year of a four-year degree) is widely recognised as a pivotal stage in nursing education, where students consolidate theoretical knowledge, refine clinical reasoning and develop higher-order cognitive skills such as critical thinking in preparation for safe, independent practice. Targeting this cohort enhances the relevance of the review, as simulation-based learning at this stage is particularly aimed at bridging the gap between supervised learning and the demands of real-world clinical environments. Therefore, this systematic review investigating the characteristics and effectiveness of simulation in this context is timely.
1.5 Aim
This systematic review aimed to answer the research question, “What is the published evidence regarding the characteristics and effectiveness of simulation to support development of final-year undergraduate nursing students’ critical thinking?
1.6 Protocol and registration
The protocol for this review is registered with PROSPERO, an international prospective register of systematic reviews (Registration number CRD42024596275).
2 Methods
The review employed a mixed method systematic review approach outlined by Hong et al. (2017) A mixed methods approach enables qualitative, quantitative and mixed research perspectives to be analysed to inform a comprehensive synthesis of the current evidence, which can then inform practice or educational decisions ( Stern et al., 2020). With this approach, quantitative and qualitative data were analysed separately and results combined. The Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines were used for reporting ( Page et al., 2021).
2.1 Search strategy
In July 2025, the databases MEDLINE (via EBSCOhost), EMBASE, CINAHL Complete (via EBSCOhost), ERIC and SCOPUS were searched. The search strategy was developed with the assistance of an expert university health librarian.
The following search terms were used:
1) nurs*,
2) (baccalaureate* OR tertiary OR undergrad* OR universit* OR bachelor* OR studen*),
3) “critica* think”,
4) simulation
2.2 Inclusion and exclusion criteria
The search was limited to papers published between 2019 and July 2025, written in English and published in peer reviewed journals. Inclusion criteria included final-year undergraduate nursing students in diploma or bachelor degree programs (i.e. third year students in a three-year diploma/degree, fourth year students in a four-year diploma/degree) and simulation as the intervention to develop critical thinking. Studies were only included if they evaluated critical thinking as an outcome of simulation. We also sought primary research studies of quantitative, qualitative or mixed methods design to examine the influence of undergraduate nursing students’ participation in simulation on their critical thinking. Exclusion criteria included studies that reported on nursing students who were not in their final-year of study, students from other disciplines (unless nursing student data were identifiable and reported separately from other disciplines), nurses and other health care workers or post graduate nursing students. Systematic reviews or other review type studies and reports were excluded.
2.3 Study selection
Identified studies were uploaded into Covidence for screening. Two reviewers (KH and BP) independently screened titles and abstracts and a third reviewer (EF) resolved disagreements. Following agreement, studies were retrieved for full text review. In addition, the reference lists of eligible studies were hand searched for other potential eligible studies that were not already captured by the database searches.
2.4 Quality appraisal
The Mixed Method Appraisal Tool (MMAT) was employed to evaluate the methodological quality of the included studies ( Hong et al., 2018). This tool enabled the authors to assess the clarity and rigor of each study against a set of structured quality-related criteria ( Hong et al., 2018). With the MMAT, there are two screening questions and five quality criteria, which differ by study design ( Hong et al., 2018). For the screening questions and criteria, we determined if each study: (1) met the criteria (2) was unable to be assessed as meeting the criteria or (3) did not meet the criteria. Appraisal results were presented as a figurative comparison, similar to those used in other studies ( Brownie et al., 2023; Pierce et al., 2024). For each study, we also allocated one point to each of the five criteria that was met and calculated a total quality score. Scores of 0–2 were considered low quality, while scores of 3–5 were identified as moderate to high quality. Aligned with Hong et al.’s work, studies were included in the analysis regardless of their quality score ( Hong et al., 2018).
2.5 Data analysis
The review utilised a convergent synthesis design as outlined by Hong et al. (2017) In this convergent synthesis approach qualitative and quantitative data are extracted and analysed together. Quantitative data were ‘qualitized’ into a narrative description ( Hong et al., 2017; Stern et al., 2020). These descriptions were then aligned with qualitative results and discussed and interpreted as categories or themes, in a narrative synthesis to answer the review question ( Hong et al., 2017).
3 Results
Following the search, a total of 985 studies were identified, and 492 duplicate citations were removed, 162 studies were eligible for full text review and 18 met inclusion criteria (
3.1 Characteristics of included studies
Most of the included studies were conducted in South Korea (8) and Australia (3), with the remaining, one each, conducted in USA, Canada, Hong Kong, Malaysia, China, Sweden and Palestine. A summary of included studies’ characteristics is displayed in
3.2 Quality of included studies
The results of the quality appraisal of the included studies are found in
3.3 Participants characteristics
All participants in the included papers were final-year students, however the duration of their degree varied from 3 to 5 years depending on the country of origin. Sample sizes ranged from 22 participants ( Carr et al., 2023) to 409 participants ( Ka Ling et al., 2021).
3.4 Simulation Interventions
3.4.1 Simulation Modes
Five simulation modalities were used as interventions in the included studies; these were standardised/simulated patient (SP), high fidelity (HF), low fidelity (LF), virtual reality (VR) and mixed reality (MR). The most described simulation modality, used in five studies, was SP played by trained actors or students (
Carr et al., 2023; Finn and Livesay, 2023; Park and Hwang, 2024; Zhou et al., 2022; Jacob et al., 2022). In addition to using SPs, Finn and Livesay (
Finn and Livesay, 2023) incorporated HF manikins (SimMAN3G) and Choi and Um (
Choi and Um, 2022) incorporated LF manikins into some of their simulation interventions. Three studies used only HF manikins as the modality in their simulations (
Sterner et al., 2023; Ka Ling et al., 2021; Salameh et al., 2021). Five studies used VR simulation (
Fung et al., 2021; Sterner et al., 2023; Lee and Baek, 2024; Rose et al., 2024; Seok-Young, 2023) and two studies involved MR simulation (
Kang and Kang, 2022; Kim et al., 2024). For two studies (
Shim et al., 2019; Yang et al., 2024), the simulation modality was unclear. Simulation intervention characteristics are found in
3.4.2 Simulation aims, timing and debrief use
The aims of the included studies varied considerably, ranging from evaluating the effectiveness of simulation compared with traditional clinical placements, to exploring the role of interdisciplinary teams in simulated environments and examining differences among various simulation modalities. Despite these diverse objectives, the learning outcomes targeted across the simulations showed notable consistency. While all studies reported on the influence of simulation on students’ critical thinking, simulation was used in studies to develop students’ competencies in patient assessment ( Carr et al., 2023; Choi and Um, 2022; Finn and Livesay, 2023; Fung et al., 2021; Sterner et al., 2023; Yang et al., 2024; Zhou et al., 2022), vital sign monitoring ( Finn and Livesay, 2023; Saghafi et al., 2024; Sterner et al., 2023; Salameh et al., 2021; Kim et al., 2024) and medication administration ( Sterner et al., 2023; Ka Ling et al., 2021; Salameh et al., 2021; Seok-Young, 2023). The impact of simulation on non-technical skills was also examined in nine studies. These skills included communication, diagnosis, intervention and evaluation.
Simulation duration ranged from 10-minute, single exposures ( Ka Ling et al., 2021) to extended or repeated sessions delivered over several days or weeks ( Shim et al., 2019; Salameh et al., 2021; Yang et al., 2024; Jacob et al., 2022; Seok-Young, 2023). Similarly, debriefing approaches varied in both structure and detail. For example, several used a brief period immediately following simulation ranging from 10 to 40 min, while some studies employed structured models, such as the Debriefing for Meaningful Learning (DML) framework ( Saghafi et al., 2024; Salameh et al., 2021). Other studies provided minimal or no description of debriefing processes, making it difficult to assess their depth or consistency.
3.5 Critical thinking measures
Across studies, eleven evaluation tools were used to measure students’ critical thinking. The most used tool, reported in six studies, was Yoon’s ( Yoon, 2008) Critical Thinking Disposition Scale, a tool developed for Korean nursing students (YCTDS) ( Choi and Um, 2022; Shim et al., 2019; Park and Hwang, 2024; Yang et al., 2024; Seok-Young, 2023; Kim et al., 2024). The YCTDS includes 27 items organised into the seven subscales of objectivity, prudence, systematicity, intellectual eagerness/curiosity, intellectual fairness, healthy scepticism and critical thinking self-confidence ( Yoon, 2008). The scale has been validated in nursing student populations in several countries ( Au et al., 2023; Shin et al., 2015). Along with the YCTDS, Kim et al. (2024) used the 15-item Nurse Clinical Reasoning Competence Scale ( Liou et al., 2016). Based on the eight steps of the Clinical Reasoning Model including look, collect, process, decide, plan, act, evaluate and reflect, it has been translated and revised by Joung and Han ( Joung and Han, 2017) for nursing undergraduates.
Two studies ( Ka Ling et al., 2021; Zhou et al., 2022) used Facione and Facione’s ( Facione and Facione, 1992) California Critical Thinking Disposition Inventory (CCTDI). This tool is based on an American Philosophical Association’s ( American Philosophical Association, 1990) Delphi study, which produced a seminal consensus definition of critical thinking. The Delphi panellists were drawn from experts in philosophy, education, social sciences and physical sciences. The CCTDI includes 75 items organised into the seven subscales of truth-seeking, open-mindedness, analyticity, systematicity, confidence in reasoning, inquisitiveness and maturity of judgement. Saghafi et al. (2020) used the 33 item Health Sciences Reasoning Test (HSRT), an updated version of the CCTDI. Originally designed to specifically evaluate the critical thinking skills in allied health students, its development was rooted in the same Delphi study on critical thinking that established the CCTDI ( Facione and Facione, 2006). Sterner et al. (2023) used a critical thinking questionnaire (CTQ) developed in Swedish based on both the CCTDI and the Watson-Glaser Critical Thinking Appraisal tool to assess critical thinking. The CTQ consisted of 28 items with a total score ranging from 28 to 112 points ( Sterner et al., 2023). Two studies used faculty created instruments to assess students’ perceptions of simulation ( Carr et al., 2023; Jacob et al., 2022).
Two studies ( Finn and Livesay, 2023; Kang and Kang, 2022) used a modified version of the validated Levett- Jones et al. (2011) Satisfaction with Simulation Experience Scale (SSES). The SSES includes 18 items organised into three subscales- debrief and reflection, clinical reasoning and clinical learning. Salameh et al. (2021) used the Lasater Clinical Judgement Rubric (LCJR) ( Lasater, 2007), developed to measures 4 aspects of clinical judgment: noticing, interpreting, reflecting and responding.
Fung et al. (2021) used a Chinese version and Rose et al. (2024) used a Korean version of the Clinical Learning Environment Comparison Survey (CLES) comprising of 29 items across 6 dimensions including communication, nursing process, holism, critical thinking, teaching-learning dyad and self-efficacy. Lee and Baek ( Lee and Baek, 2024) used Kwon et al.’s ( Kwon et al., 2006) Critical Thinking Disposition Scale for Nursing Students (CTDS), a non-validated tool comprising of 35 items across 8 sub-dimensions.
3.6 Critical thinking outcomes
Most studies reported improvements in nursing students' critical thinking following simulation, though outcomes varied depending on the simulation modality and the structure and delivery of the simulation experience. Yang et al. (2024) did not specify the simulation modality in their study but compared a multi-scenario role fixation group (MRFG) with a single-scenario role rotation group (SRRG). In the MRFG participants played only one role across multiple different scenarios whilst in the SRRG participants repeated the same scenario, playing a different role each time ( Yang et al., 2024). They found a significant increase in critical thinking disposition only in the SRRG from pre-test ( M=101.65) to post-test ( M=107.94, t = −2.17, p = .038), with no change in the MRFG and no significant difference between groups ( t = 1.89, p = .063) ( Yang et al., 2024). Similarly, Shim et al. (2019) demonstrated an improvement in students’ critical thinking from pre-test ( M=59.2, SD=5.0) to post-test ( M=61.3, SD=5.4; t = -3.01, p = .003), however, they also did not provide details of the simulation modality intervention used.
3.6.1 Standardised patient (SP) simulation
Standardised patient simulations were associated with positive critical thinking outcomes in several studies. Compared with a lecture only group and an unspecified control group Park and Hwang ( Park and Hwang, 2024) found that participants’ critical thinking skills significantly increased from pre-test ( M=98.9, SD=10.42) to post-test ( M=103.16, SD=9.93, p < .001), when exposed to a 4-hour SP simulation using trained actors and disaster-related scenarios. Similarly, Jacob et al. (2022) reported that extended, immersive SP simulations enhanced evidence-based decision-making and students’ ability to prioritise care when faced with realistic pressures. These outcomes were derived from student’s perception using faculty derived survey questions.
Also presenting positive outcomes with SP simulation, Choi and Um ( Choi and Um, 2022) observed a significant increase in participants’ critical thinking propensity pre-test ( M=3.62, SD=0.42) to post-test ( M=3.79, SD=0.42, p = .043) following a dementia-focused SP simulation, involving low fidelity (manikin torso and SPs). Compared with engaging in nursing student-only SP simulations, Zhou et al. (2022) found that participants who engaged in interprofessional SP simulations (4-hour sessions over 5 weeks) had significant improvements in critical thinking scores ( M=284.08, SD =15.55; Z = -5.81; p < .001).
Not all studies found SP to positively influence participants’ critical thinking. Carr et al. (2023) reported that students perceived SP simulations to be less effective for enhancing critical thinking ( M = 3.7/5) compared with team-based learning ( M = 4.1/5) and clinical placement ( M = 4.1/5). They did however perceive SP simulation as more effective than video scenarios ( M = 3.1/5). In the study, the simulation duration was not discussed and the sample size was small ( n = 22).
3.6.2 High-fidelity (HF), Low-fidelity (LF) and/or combination simulation
High-fidelity and LF simulation results were mixed when used either independently or combined with other simulation modalities. Salameh et al. (2021) found significantly higher post-test clinical judgment scores in HF simulation groups ( M=34.51, SD= 7.87) compared with participants receiving traditional lectures ( M=14.32, SD =4.28; t = 19.55; p = .001), particularly in the subscales of noticing, interpreting and responding. The HF simulation group used six simulation scenarios which were repeated and practiced until mastered. Similarly, Sterner et al. (2023), in their study of 61 final-year nursing students, reported a statistically significant improvement in participants’ critical thinking from pre-test ( M=84.34, SD=5.66) to post-test ( M=88.67, SD=6.33, p < .001), (Cohen’s d= −0.87), indicating a large magnitude of effect, after using a combination of HF manikins and a web-based interactive simulation program.
Saghafi et al. (2024) implemented nine hours of simulation, over two weeks, using a combination of modalities (a manikin, a SP, a video and a game-based simulation). They found a statistically significant increase in participants’ critical thinking levels from pre-test to post-test ( t = 2.445, p = .018), with 60 % of students advancing at least two classification levels of critical thinking during the intervention. Finn and Livesay ( Finn and Livesay, 2023), who used both HF manikins and SPs, reported high participant agreement on the simulation’s role in developing their decision-making ( M=4.18/5, SD=086) and clinical reasoning (M=4.22/5, SD=0.87). Outcomes were based on self-report rather than validated critical thinking tools.
In contrast to these other studies, Ka Ling et al. (2021) found a decline in participants’ critical thinking dispositions following both HF and LF code blue simulations. They suggest this decline may be related to differences in participants’ interpretation of items in the CCTDI measurement tool, despite careful forwards and back translation of the instrument, rather than the simulation itself.
3.6.3 Virtual and mixed reality simulation
Studies focussed on virtual reality (VR) and mixed reality (MR) simulations mostly reported improvements in participants’ critical thinking following engagement with these simulation modalities. Compared with participants who engaged in clinical placement only, Lee and Baek ( Lee and Baek, 2024) found participants ( n = 43) who engaged with six VR simulation scenarios over six weeks, as an addition to clinical placement, had a significant increase in critical thinking scores from pre-test ( M=3.76, SD=0.33) to post-test ( M=4.25, SD=0.34; p = .007). Seok-Young ( Seok-Young, 2023) also found that participants who participated in 45 h of VR simulation and clinical placement education over five days had significantly greater improvements in critical thinking compared with participants who participated in traditional clinical placement education alone ( t = 2.40, p = .006).
Not all findings favoured VR as a strategy to enhance student critical thinking. Rose et al. (2024) found that participants ( n = 70) perceived the usefulness of VR simulation for developing critical thinking as lower ( M=2.2, SD= 1.0) compared with clinical placement ( M=3.1, SD= 1.2) and fewer participants (21–49 %) perceived critical thinking needs were met well/very well with VR simulation, compared with clinical placement (78–82 %). Their study took place over the 2020–2021 academic year during the COVID-19 pandemic ( Rose et al., 2024). Similarly, Fung et al. (2021) found that compared with participants who engaged with clinical placement, those who engaged with VR simulation had significantly lower critical thinking scores at pre-test ( t = 3.24, p < .05) and post-test ( t = 2.07, p < .05). While the authors did not report mean differences in scores (which would help determine if a true decline in critical thinking occurred), they suggested that participants’ abrupt shift during the COVID-19 pandemic to VR learning may have negatively impacted participants’ outcomes.
Alternatively, Kang and Kang ( Kang and Kang, 2022), using MR and VR, reported significantly higher satisfaction levels with critical thinking development among nursing participants ( M=18.67/20, SD=2.059) compared with medical participants ( M=15.93/20, SD=3.173; t = -2.799 p = 0.009). Although, the study design was a case study with small sample size of 4th year nursing students ( n = 15) and 3rd year medical students ( n = 15). In contrast, Kim et al. (2024) found no significant change in critical thinking scores from pre-test to post-test in either the MR simulation group (pre-test: M=3.80, SD=0.32; post-test: M=3.91, SD=0.39; p = .721) or the PBL group (pre-test: M=3.80, SD=0.42; post-test: M=3.89, SD=0.41; p = .100), while the HF simulation group demonstrated a significant improvement (pre-test: M=3.86, SD=0.36; post-test: M=4.05, SD=0.39; p = .017). No significant differences were observed in post-test critical thinking scores across the three groups ( p = .316). However, in measuring clinical reasoning, all groups showed significant gains, with post-test differences between MR simulation and PBL groups reaching statistical significance ( p = .028).
4 Discussion
This review aimed to examine the existing literature on the characteristics and effectiveness of simulation in enhancing critical thinking among final-year undergraduate nursing students. We found that simulation generally had a positive influence on the development of critical thinking in nursing students, although the degree of its impact varied depending on the simulation characteristics and modality used.
Of the 18 included studies, fourteen studies reported a significant increase in final-year nursing students' critical thinking scores after engaging in simulation. Of the remaining four studies, three determined that simulation was less effective than clinical placement; and one study reported a decline in final-year nursing students’ critical thinking disposition following simulation. These findings, which favour simulation for enhancing students’ critical thinking, contrast with those of Adib-Hajbaghery and Sharifi ( Adib-Hajbaghery and Sharifi, 2017). In their systematic review of studies involving qualified nurses and nursing students, only half of their 16 included studies showed statistically significant improvements in participants’ critical thinking scores. They attributed inconsistencies to differences in critical thinking measurement tools and the wide variation of simulation methods used across studies. Our findings align more closely with Loubbairi et al.’s ( Loubbairi et al., 2025) systematic review, which examined the impact of simulation on the development of nursing and medical students’ critical thinking and reflective skills at any stage in their degree. They found that participants’ critical thinking, mostly increased following simulation, despite variations in critical thinking measurement tools and simulation modalities across the included studies ( Loubbairi et al., 2025).
In this review, SP simulation was generally associated with positive outcomes for developing final-year nursing students’ critical thinking. Several studies demonstrated statistically significant improvements in critical thinking scores or student-reported gains in decision-making and clinical prioritisation following SP-based activities. This aligns with existing literature, where SP simulations have been shown to enhance communication, clinical reasoning and confidence, skills foundational to critical thinking development ( Burrell et al., 2023; Godzik et al., 2023; Webster and Carlson, 2020). By mimicking real-life patient interactions, SP scenarios promote analysis, inference and evaluation, which are key elements in Facione’s ( Facione, 2015) model of critical thinking.
However, not all SP simulations in this review yielded strong outcomes. One study reported that students perceived SP simulation to be less effective than clinical placements or team-based learning ( Carr et al., 2023). This suggests that while SPs can foster decision-making and clinical reasoning, their perceived or actual impact may depend on scenario complexity, facilitator expertise and comparison conditions. Additionally, SP simulations require significant resources, including trained actors and faculty, which can limit scalability and consistency across institutions ( Godzik et al., 2023).
High fidelity simulation also showed generally positive results, especially when scenarios were repeated with debriefing and feedback. These findings align with theories of deliberate practice, which conceptualise it as structured, instructor-guided activities purposefully designed to address specific performance components, enhanced through repetition and progressive refinement ( Chidume et al., 2023). The findings are also consistent with other literature that recognises HF simulation’s capacity to enhance decision-making, clinical judgment and learner confidence in nursing students across differing year levels ( Akalin and Sahin, 2020; D'Souza et al., 2020). The multi-sensory, immersive environment engages learners in complex, realistic scenarios that activate cognitive and metacognitive processes tied to critical thinking, such as information prioritisation, recognising patterns and reflecting in action ( Akalin and Sahin, 2020). Low fidelity simulations, while less resource-intensive and more cost effective, may offer less engagement and realism, possibly affecting their impact on critical thinking. They remain valuable for skill rehearsal and structured reasoning when used strategically.
In this review, one study reported a decline in students’ critical thinking dispositions in both HF and LF simulations modalities following code-blue scenarios ( Ka Ling et al., 2021). This finding is potentially linked to cultural differences affecting how critical thinking is expressed and measured, particularly when using tools like the CCTDI. Critical thinking is not only skill-based but is also disposition-dependent. Ka Ling et al.’s ( Ka Ling et al., 2021) study acknowledged that cultural values, beliefs and practices may explain the differences in critical thinking outcomes between Eastern and Western contexts. Accordingly, cultural factors can influence how students perceive and respond to critical thinking tasks ( Ka Ling et al., 2021).
Virtual reality and MR simulations demonstrated mostly positive effects on critical thinking with the literature discussing that these technologies offer immersive, repeatable environments where learners can safely engage in complex scenarios. These findings align with existing literature which supports the immersive and interactive nature of VR and MR and its alignment with critical thinking development models, which emphasise critical reflection, problem solving and application of knowledge in varied contexts ( Padilha et al., 2019; Sim et al., 2022). In our review, VR-based interventions often led to statistically significant gains in critical thinking scores, especially when used as a supplement to clinical placement. Mixed reality was found to enhance engagement and realism through holographic interfaces, offering multi-sensory cues that support complex decision-making. Interestingly Kim et al. (2024) found HF simulation to significantly improve critical thinking scores compared with the MR group; however, when measuring clinical reasoning, all groups demonstrated significant gains. This discrepancy may be attributable to differences in the assessment tools used, with critical thinking and clinical reasoning often operationalised and measured using distinct instruments that capture overlapping but not identical constructs.
However, not all findings favoured VR as a strategy to enhance final-year students’ critical thinking. Two studies in this review reported lower critical thinking scores in VR compared with traditional clinical placement, likely influenced by the rapid shift to virtual formats during the COVID-19 pandemic. This abrupt transition may have disrupted instructional continuity, reduced feedback opportunities and created technological barriers that diluted the critical thinking benefits of VR ( Fung et al., 2021). These results indicate that while VR and MR simulations offer strong potential, careful instructional design and learner preparation are crucial to maximise critical thinking outcomes.
Across the included studies, improvements in critical thinking were observed regardless of the simulation’s duration, frequency, or debriefing length. While longer and repeated exposure has been associated in the literature with deeper cognitive engagement and reinforced learning ( Chidume et al., 2023), the findings of this review align with Tong et al. (2022) suggesting that shorter or less frequent simulations can also support critical thinking and its underlying processes, particularly when they are well designed and purposefully implemented. While longer and repeated simulations may enhance opportunities for deliberate practice, critical thinking development appears to not be exclusively dependent on simulation duration.
In this review, most studies included some form of debriefing, ranging from brief reflections to structured, theory-based models such as DML ( Dreifuerst, 2011). Despite the variability in debriefing approach and duration, most studies reported improvements in students’ critical thinking. This supports the premise that guided reflection, regardless of length, can enhance cognitive processing, reinforce learning, make meaning from experience and engage in reflective processes that are central to critical thinking ( Facione, 2015; Dreifuerst, 2011). These findings align with experiential learning theory ( Kolb, 1984), which highlights the importance of engaging learners in a cycle of action and reflection. Even when brief, simulation followed by focused debriefing may activate key cognitive processes such as analysis, evaluation and judgment, especially when scenarios are relevant, emotionally engaging and learner centred.
This review identified a notable lack of qualitative and mixed methods studies. While Finn & Livesay ( Finn and Livesay, 2023) classified their study as mixed methods, it employed open ended survey questions, offering some qualitative insight but lacking the depth typically associated with interviews or focus groups ( Thomas et al., 2024). Only Rose et al. (2024) and Zhou et al. (2022) employed a true convergent mixed methods approach. The absence of qualitative inquiry restricts understanding of the elements central to critical thinking development such as cognitive, emotional and reflective processes, which are not easily captured through quantitative measures alone. Qualitative data could provide valuable insights into how and why simulation influences critical thinking, supporting the refinement of instructional design and debriefing strategies.
Despite this weakness, a notable strength across the studies was the widespread use of validated critical thinking instruments, such as the CCTDI ( Facione and Facione, 1992), YCTDS ( Yoon, 2008) and the HSRT ( Facione and Facione, 2006). The use of psychometrically sound tools enhances confidence in the reported improvements in critical thinking. However, a few studies relied on faculty-derived or non-validated tools, which limits comparability across studies and raises concerns about measurement precision ( Cook and Beckman, 2006). Future studies would benefit from capturing data using validated tools with larger samples and stronger experimental controls during simulation-based education.
Overall, this review provides nurse educators with contemporary insights into the effectiveness of various simulation characteristics (including modalities) for strengthening final-year nursing students critical thinking. Such insights are particularly important as nurse educators prepare final-year nursing students to face the realities of independent clinical practice, where critical thinking skills can directly influence patient safety and healthcare quality. By synthesising recent evidence across a range of simulation modalities, including emerging formats such as VR and MR, this review addresses the changing priorities in nursing education shaped by technological advancement and post-pandemic changes in clinical training. Due to continually emerging advancements in technology, for both education and practice, future simulation research may consider the impact of artificial intelligence informed simulation and its impact on students’ critical thinking. While simulation is well established in nursing education, its targeted application to foster critical thinking, particularly using emerging technologies, has been underexplored. This review demonstrates that, regardless of fidelity or duration, simulation can positively impact critical thinking when thoughtfully designed with cognitive and reflective learning goals.
4.1 Limitations
While most included studies demonstrated positive outcomes in the development of nursing students’ critical thinking, many lacked methodological rigor in key areas. Common limitations included small sample sizes, absence of control groups and lack of randomisation. These factors introduce potential biases and confounding variables, which may affect the conclusions drawn regarding simulation’s impact on critical thinking outcomes. Most studies also assessed outcomes immediately post-intervention, with minimal longitudinal data to determine the sustained impact of simulation on critical thinking.
The included studies varied widely in design, simulation modality, duration and outcome measures, limiting comparability and preventing meta-analysis. Methodological quality of the included studies was inconsistent, which reduce the trustworthiness and generalisability of results. Language and publication bias may be present, as only English-language, peer-reviewed studies were included.
5 Conclusion
Collectively, these findings indicate that while various simulation modalities can support critical thinking development, fidelity alone may not determine effectiveness. Rather, success may be influenced by design elements such as scenario realism, learner role immersion and the presence of guided, reflective debriefing. These features align with experiential learning theory, which emphasises the importance of engaging learners in active experience and critical reflection to promote higher-order thinking. Thus, thoughtful integration of simulation modalities with targeted learning outcomes appears essential to maximising their impact on final-year nursing students’ critical thinking. Ongoing research that incorporates robust methods and explores students’ experiences more deeply will be vital to advancing simulation as a core strategy for developing critical thinking in nursing education.
Protocol registration
The protocol for this review is registered with PROSPERO (Registration number CRD42024596275).
CRediT authorship contribution statement
Kate Harry: Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis, Conceptualization. Beth Pierce: Conceptualisation, methodology, investigation, formal analysis, writing – reviewing and editing, supervision. Elizabeth Forster: Conceptualisation, methodology, formal analysis, writing – reviewing and editing, supervision.
Funding
No external funding
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.
Table 1
| Simulation Modality | Definition |
| Low fidelity (LF) | Mainly rubber body parts (part task trainers) with limited functions. They resemble parts of a person in shape, size and weight ( Alshehri et al., 2023; Massoth et al., 2019). |
| High fidelity (HF) | A close to reality experience using manikins, which have realistic physiological responses, can communicate and interact, and have advanced feedback mechanisms ( Massoth et al., 2019). |
| Standardised/simulated patient (SP) | Individuals who are trained (actors) portray patients, (their relatives and healthcare professionals) in a reliable and consistent manner ( Nestle et al., 2010). Can often be faculty (with or without training) or students ( Mavis et al., 2010). |
| Virtual reality (VR) | Uses a web-based platform to simulate scenarios and allows students to apply knowledge, make decisions, perform interventions, and receive direct feedback on their performance. Can include non-immersive, immersive, and/or 3D ( Seok-Young, 2023). |
| Augmented reality (AR) | The superimposition of digital imagery onto a real-world view ( Abbas et al., 2023). |
| Mixed reality (MR) | A more advanced type of augmented reality, which allows digitally produced objects to be overlaid on a real environment and can be physically manipulated in three dimensions by the user ( Abbas et al., 2023; Frost et al., 2020). |
Table 2
| 80Author, year, country | Study aim | Study design; theoretical framework | Sample; Setting | CT Instrument | CT Outcomes |
Additional
outcomes reported |
Limitations | Recommendations |
| Carr et al., 2023, USA | To compare perceived effectiveness of SP simulation, Team Based Learning (TBL), clinical placement and video response assignment on student knowledge, critical thinking, communication, and attitude toward mental health illness. | Cross-sectional survey; Unspecified. | 22 nursing students;
accelerated 12-month baccalaureate at a Mississippi university. |
Faculty derived instrument measuring perceived effectiveness for CT, knowledge, communication and attitude. | Participants perceived the effectiveness of SP simulation for CT ( M = 3.7/5) to be lower than TBL ( M = 4.1/5) and clinical placement ( M = 4.1/5) but higher than video response assignment ( M = 3.1/5). | Knowledge, communication, attitude towards mental health. | No inferential comparison between learning interventions; small sample size; single site; psychometric instrument properties unknown. | Greater integration of mental health care throughout curricula and clinical experiences. |
| Choi & Um, 2022, South Korea | To examine effectiveness of home-visit/dementia simulation on students’ communication, self-efficacy and CT. | Quasi-experiment, one-group pre-test/post-test; Unspecified. | 69 fourth year nursing students;
a South Korean university. |
Critical Thinking Disposition Scale ( Yoon, 2008). | Participants’ CT propensity increased significantly from pre-test ( M=3.62, SD=0.42) to post-test ( M=3.79, SD=0.42; t = −2.06, p = .043). | Communication skills, self-efficacy. | Single group; no control group; single site; potential for confounding variables. | Simulation may be enhanced by SPs played by professional actors. |
| Finn & Livesay, 2023, Australia | To evaluate tag team patient safety simulation in managing, resourcing, and scale simulation learning with large student cohorts. | Convergent mixed methods (author designated; however, only survey-based therefore quantitative descriptive); Unspecified. | 65 third year nursing students; a Melbourne University. | Modified version of Satisfaction with Simulation Experience Scale.
Levett-Jones et al., (2011) |
Participants agreed that simulation supported their clinical reasoning skills (M=4.22/5, SD=0.87) and decision-making skills ( M=4.18/5, SD=086), enabled demonstration of clinical reasoning skills ( M=4.09/5, SD=0.96) and recognising deteriorating patient ( M=4.14/5, SD=.093). | Satisfaction with debrief and reflection, clinical learning, tag team approach. | No pre simulation perceptions; no control group; small sample size. | Utilise pre-briefing documents; use the same patient across multiple scenarios; limit student numbers per scenario to 3. |
| Fung et al., 2021, Hong Kong | To evaluate effectiveness of a VR simulation education programme (with debriefing) on perceived clinical competence and learning needs compared to clinical practicum during COVID−19. | One-group pre-test/post-test; Unspecified. | 188 fifth year nursing students; a Hong Kong university. | The Clinical Learning Environment Comparison Survey ( Gu et al., 2018). | Participants’ CT scores were significantly lower in simulated environment compared with clinical practicum at pre-test ( t = 3.24, p < .05) and post-test ( t = 2.07, p < .05). | Perceived clinical competence, learning needs. | Single group; no control group; single site; no randomisation. | Replicate the study in the next year for comparing the learning outcomes after COVID−19 pandemic to get a comprehensive picture of the effect of VR simulation. |
| Jacob et al., 2022, Australia | To investigate students’ views on the value of extended, immersive simulation in preparing them for independent practice as registered nurses. | Cross-sectional survey with content analysis of open-ended survey responses; Unspecified. | 287 third year nursing students; a Western Australian university. | Faculty derived survey questions related to teamwork, communication, CT, time management and leadership. | Simulation supported participants to make evidence-based decisions, identify changes in patient status, determine when to ask for help, and determine plans of action to manage situations. Simulation created ‘pressure’, so participants made multiple decisions that impacted patient outcomes and prioritised order of care. | Teamwork, communication, time management, leadership. | Desirability response bias; single site. | Include interdisciplinary team members to fully replicate the responsibilities of RNs in multidisciplinary teams. |
| Ka Ling et al., 2021, Malaysia | To compare knowledge and CT skills using an adult code blue drill simulated program using HF patient simulation versus LF patient mannikin. | Pre-test/post-test with experimental group (HF patient simulation) and control group (LF patient mannikin); information processing model; Unspecified. | 409 third year nursing students; assumed university across three sites in Malaysia. | California Critical Thinking Disposition Inventory.
Facione and Facione (1992) |
HF group had decline in overall CT score, (p< .001) and domains of inquisitiveness (p < 0.001), analyticity (p < 0.001), maturity of judgement (p < 0.001), and systematicity (p = .003).
LF group had decline in overall CT score, (p < .001) and domains of inquisitiveness (p < 0.001), analyticity (p < 0.001), maturity of judgement (p < 0.001) and systematicity (p = .007). |
Knowledge. | Unclear difference between HF and LF; two different types of debrief – video playback only for HF. | Written guidelines
and training are recommended for faculty members to enhance teaching and learning process objectively. |
| Kang & Kang, 2022, South Korea | To explore undergraduate medical and nursing students’ satisfaction with MR online interprofessional learning experience. | Case study; Unspecified. | 15 fourth year nursing and 15 third year medical students; educational institution unclear. | Modified version of Satisfaction with Simulation Experience Scale.
Levett-Jones et al., (2011) |
Nursing participants more satisfied with impact of MR simulation on CT (
M=18.67/20,
SD=2.059; highly satisfied) compared to medical participants (
M=15.93/20,
SD=3.173;
t = −2.799 p = .009). |
Satisfaction with debriefing and reflection and clinical learning. | Small sample; single site; no pre-test survey; no comparison group to non-simulation. | Integrate MR, online approach and structured
clinical reasoning process to enhance CT and interprofessional learning. |
| Kim et al., 2024, South Korea | Examine the effectiveness of an infection control simulation using mixed reality, comparing simulation fidelity with a HF mannequin group and problem-based learning (PBL) with written cases group. | Pre-test/post-test with experimental group (MR simulation), comparison group (HF simulation) and control group (PBL); Jeffries Simulation Model ( Jeffries, 2005). | 72 fourth year nursing students; 2 South Korean Universities. | Critical Thinking Disposition Scale ( Yoon, 2008) and Nurse Clinical Reasoning Competence Scale ( Liou et al., 2016). | There was no difference in CT from pre-test to post-test for the MR simulation group (pre-test:
M=3.80, SD=0.32; post-test:
M=3.91, SD=0.39; p = .721) or PBL group (pre-test:
M=3.80, SD=0.42; post-test:
M=3.89, SD=0.41, p = .100). The HF simulation group had a significant change in CT from pre-test
(M=3.86, SD=0.36) to post-test (
M=4.05, SD=0.39, p = .017). There was no difference in post-test CT scores across groups (p = .316).
There was a significant increase in clinical reasoning scores for the MR simulation group (pre-test: M=3.60, SD=0.48; post-test: M=4.31, SD=0.46; p < .001); the HF simulation group (pre-test: M=3.79, SD=0.39; post-test: M=4.15, SD=0.51; p = .011); and the PBL group (pre-test: M=3.68, SD=0.56; post-test: M=3.96, SD=0.41; p = .006). There was a significant difference in post-test CT scores between the MR simulation and the PBL groups (p = .028). |
Clinical competence, learning immersion in simulation, satisfaction and self-confidence. | Small sample size; two universities; no longitudinal follow up. | The level of simulation fidelity should be selected based on learning goals, students should be given repeated simulation practice opportunities when clinical placement is limited. |
| Lee & Baek, 2024, South Korea | To develop a program using VR simulation based on information processing model
and verify its effects on performance confidence, problem-solving ability and critical thinking. |
Non-quantitative pre-test/post-test with experimental group (VR simulation and clinical practice) and control group (clinical practice only); information processing model. | 43 fourth year nursing students; a South Korean university. | Critical Thinking Disposition Scale for Nursing Students ( Kwon et al., 2006). | VR simulation group had significantly greater increase in CT from pre-test ( M=3.76, SD=0.33) to post-test ( M=4.25, SD=0.34), compared to control group (pre-test M=3.82, SD=0.53, post-test M=3.78, SD =0.53; F=8.17 p = .007). | Performance confidence, problem solving ability. | Small sample size; single university; no longitudinal follow up. | Need to study the long-term effects of the simulation; construct an expanded program that can maximize the educational effect. |
| Park & Hwang, 2024, South Korea | To develop a simulation-based program, that employed SPs, to assess competency in disaster nursing, triage score, disaster preparedness, CT
and confidence. |
Non-equivalent, pre-test/post-test with experimental group (SP simulation and lectures), comparison group (lectures) and control group (unspecified);
Experiential Learning Theory ( Kolb, 1984) and Jeffries Simulation Model ( Jeffries, 2005). |
140 fourth year nursing students; two South Korean universities. | Critical Thinking Disposition Scale ( Yoon, 2008). | SP simulation group had significantly greater increase in CT from pre-test ( M=98.9, SD=10.42) to post-test ( M=103.16, SD=9.93), compared to lecture group (pre-test M=96.17, SD=8.37, post-test M=94.40, SD =8.15) and control group (pre-test M=94.86, SD=6.86, post-test M=93.03, SD =7.57; F=1.63 p < .001). | Disaster nursing, triage score, disaster preparedness,
and confidence in disaster nursing. |
Small convenience sample; two universities; no longitudinal follow up. | Repeated studies should be conducted across a wider range of years and schools. |
| Rose et al., 2024, Canada | To assess student and faculty satisfaction and usefulness of virtual simulation, the effectiveness of meeting learning needs, and the effects of the virtual simulation resource on the development of clinical judgment. | Mixed method; Kirkpatrick’s Evaluation Model ( Kirkpatrick and Kirkpatrick, 2016). | 70 final year nursing students: three Canadian universities. | The Clinical Learning Environment Comparison Survey ( Gu et al., 2018). | Usefulness of online simulation for developing critical thinking was perceived lower ( M=2.2, SD= 1.0) compared to clinical placement ( M=3.1, SD= 1.2). Fewer participants (21–49 %) perceived critical thinking needs were met well/very well with online simulation, compared to clinical placement (78–82 %). | Faculty perception, student satisfaction. | Small sample size; no inferential comparison of means. | Conduct a comparative study to test the correlation between self-reports and objective measures of learning to provide additional evidence for the value and correspondence of self-reports in this context. |
| Saghafi et al., 2024,
Australia |
To investigate how critical thinking skills were impacted after attending a purposefully designed 15-hour program with nine hours of simulation-based learning activities over two weeks. | One-group pre-test/post-test;
Clinical Reasoning Cycle ( Levett-Jones et al., 2010). |
56 third year nursing students; an Australian university across five campuses/ cities. | The Health Sciences Reasoning Test ( Facione and Facione, 2006). | CT scores significantly increased from pre-test to post-test ( t = 2.445, p = .018). 50 % of participants had pre-test scores at ‘strong’ level or above; increased to 71 % of participants at post-test; 60 % of participants increased two levels at post-test. | No other outcomes. | Low response rate (4.3 %), no breakdown of results by each type of intervention, no longitudinal follow up. | Repeat survey three months post-intervention to examine longer-term CT changes. |
| Salameh et al., 2021, Palestine | To assess students' clinical knowledge and judgment after including HF simulation involving mechanical ventilation in an undergraduate
nursing program. |
Quasi-experiment, pre-test/post-test with experimental group (HF simulation and lectures) and control group (lecture only); Tanner's Clinical Judgment Model ( Tanner, 2006). | 151 fourth year nursing students; a Palestine university. | Lasater Clinical
Judgment Rubric ( Lasater, 2007). |
No difference in pre-test clinical judgement scores between HF simulation (
M =14.0;
SD = 2.48) and lecture groups (
M =13.7;
SD = 2.58;
t = 0.649;
p = .518);
HF simulation groups’ post-test clinical judgement scores ( M=34.51, SD= 7.87) significantly greater than lecture group ( M=14.32, SD =4.28; t = 19.55; p = .001). HF simulation groups’ post-test subscale scores of noticing, interpreting, responding, and reflecting significantly greater than lecture group (all p < .001). |
Knowledge. | Single educational institution; no longitudinal follow up. | Further research using other complex case situations
might validate the impact of HF simulation on students' knowledge and clinical judgment. |
| Seok-Young, 2023, Korea | To evaluate effectiveness of VR simulation and clinical practice education versus clinical practice education on students’ CT, problem-solving and clinical performance related to child-adolescent nursing. | Quasi-experiment, pre-test/post-test with experimental group (VR simulation and clinical practice education) and non-equivalent control group (clinical practice education only); Unspecified. | 48 fourth year nursing students; a Korean college. | Critical Thinking Disposition Scale ( Yoon, 2008). | VR simulation group’ CT tendency significantly increased from pre-test ( M=95.69, SD=8.17) to post-test ( M=106.42, SD=21.49; p < .001). Clinical education group’s CT tendency increased significantly from pre-test ( M=95.69, SD=7.08) to post-test ( M=104.49, SD=8.67; p = .003). M difference for VR group significantly greater than clinical education group ( t = 2.40, p = .006). | Problem solving processes, clinical performance. | Unclear comparison of mean difference between groups. (alternate mean difference used); single site; small sample. | Develop virtual reality simulations in the future for core basic nursing training in clinical practice in child nursing. |
| Shim et al., 2019, Korea | To analyse effect of a simulation-based education program on students’ communication ability, problem-solving ability and CT. | One-group pre-test/post-test; Unspecified. | 117 fourth year nursing students; a Korean university. | Critical Thinking Disposition Scale ( Yoon, 2008). | Participants’ CT score significantly increased from pre-test ( M=59.2, SD=5.0) to post-test ( M=61.3, SD=5.4; t = −3.01, p = .003). | Communication, problem solving. | Few details of simulation; no control group; single institute; no longitudinal follow up. | Simulation can be integrated into nursing education to develop various student competencies. |
| Sterner et al., 2023, Sweden | To explore if a nursing course with blended simulation activities
(HF and web-based interactive simulation program) could increase students’ CT skills. |
Quasi-experiment, one-group pre-test/post-test; Unspecified. | 61 third year nursing students; a Swedish university. | Critical Thinking Questionnaire (CTQ) – a modified Swedish version of California Critical Thinking Disposition Inventory (
Facione and Facione, 1992)
and Watson–Glaser Critical Thinking Appraisal ( Wilder-Larsson et al., 2018). |
Participants’ CT score significantly increased from pre-test ( M=84.34, SD=5.66) to post-test ( M=88.67, SD=6.33; t = −3.01, p < .001), with large effect size (Cohen’s d= −0.87). | No other outcomes. | Low response rate, no control group, single institute. | Integrate a blended simulation approach into curricula that includes
computer-based and HF simulation. |
| Yang et al., 2024, South Korea | To compare the effects of a multi-scenario role fixation group (MRFG) and single-scenario role rotation group (SRRG) among nursing students to present foundational data for developing more effective simulation designs. | Pre-test/post-test with MRFG simulation group vs SRRG simulation group; Experiential Learning Theory ( Kolb, 1984). | 66 fourth year nursing students; a South Korea University. | Critical Thinking Disposition Scale ( Yoon, 2008). | SRRG group had significant increase in CT disposition from pre-test ( M=101.65) to post-test ( M=107.94, t = −2.17, p = .038). MRFG had no change in CT disposition from pre-test ( M=103.23) to post-test ( M=102.26, t = 0.39, p = .703) No significant difference in CT disposition between SRRG and MRFG groups ( t = 1.89, p = .063). | Learning confidence, learning competency. | Minimal detail of simulation type (eg HF vs LF), small sample size, single university, variation in facilitator approaches, difference in learning focus of simulation. | Examine whether learning effectiveness varies according to the number of roles performed in a given scenario, investigate the effects of role change simulation training on new graduate nurses. |
| Zhou et al., 2022, China | To use 3 P theory to guide interprofessional
simulation teaching and test effects of a simulated interprofessional education model on students’ CT and cooperative abilities. |
Convergent mixed methods with experimental group (simulation with interprofessional students) and control group (simulation with nursing students); 3 P model ( Biggs, 1993). | 60 third year nursing students; a Chinese
‘school’. |
The California Critical Thinking Disposition Inventory ( Facione and Facione, 1992). | No difference in pre-test CT scores between interprofessional group ( M =237.06; SD = 33.44) and nursing group ( M =237.00; SD = 28.34; Z = −0.44; p = .663). Interprofessional group’s post-test CT scores ( M=245.11, SD=30.56) significantly greater than nursing group ( M=284.08, SD =15.55; Z = −5.81; p < .001). | Cooperative
abilities. |
Single site; small sample size. | Implementation of other interprofessional discipline cooperation to test effect. |
Table 3
| Author, year, country | Simulation mode | Learning focus of simulation/ simulation details | Skill | Simulation duration | Debriefing Details |
| Carr et al., 2023, USA | SP (trained simulation actors). | Care of patients with mental health conditions-
2 scenarios: 1 patient with schizophrenia in the community, 2 patient with Bipolar in the emergency department. |
Patient assessment. | Assumed single simulations run, simulation duration not stated. | Yes, structured, time not stated. |
| Choi & Um, 2022, South Korea | LF (torso on the ground),
SP (unclear if played by student). |
Care of patients with dementia during home visit scenario. | Building rapport and home environment assessment; nursing assessment and diagnosis; planning and implementation; evaluation. | Assumed single simulation run, simulation duration not stated. | Yes, no other details stated. |
| Finn and Livesay, 2023, Australia | SP and HF
Elderly man – (played by faculty – 4 hr education provided to faculty) Transman – sim mannequin SimMAN3G. |
Tag team simulation (
Levett-Jones et al., 2015)
3 scenarios: 1 elderly delirious patient, 2 transman with early onset chest pain, 3 transman with SOB secondary to myocardial injury. |
Technical skills: vital signs; patient assessment; provision of care.
Non-technical skills: communication; decision-making; teamwork. |
Time not stated. | Yes, no other details stated. |
| Fung et al., 2021, Hong Kong | VR (instead of attending clinical placement). | Cases were chosen to provide authentic clinical simulation training and sufficient clinical hours.
4 scenarios: 1 pneumonia re-admission to assisted living patient, 2 stroke/alzheimers patient, 3 fractured femur in diabetic patient, 4 pneumonia patient. |
Chart assessment; physical assessment; nursing diagnosis; intervention; evaluation. | A two-day workshop, each session consisted of a 4-hour virtual simulation session. | 4-hr debriefing using 3D model. |
| Jacob et al., 2022, Australia | SP (students played the patient)
(faculty played the Medical Officer or Nurse Educator). |
Using extended immersive simulation to challenge students to consolidate both technical and non-technical skills to support transition to independent practice.
The program used progressive case scenarios where complex patients either improved or deteriorated depending on the nursing care provided. |
Time management; delegation; critical thinking. | The simulation was undertaken over two days, divided into six shifts of three hours. | Yes, incorporating feedback from students and expert clinicians, time not stated. |
| Ka Ling et al., 2021, Malaysia | HF- patient simulation (unclear if actors or faculty).
LF- patient mannequins. |
Code Blue Management. | Knowledge of airway management; cardiopulmonary resuscitation; administration of medication; identification of life-threatening arrhythmias; team collaboration on a deteriorating patient. | Prebrief including written case scenario provided, 40-minute presentation on code blue, each group simulation ran for 10 min. | Yes, included video recording for self -assessment, time not stated. |
| Kang & Kang, 2022, South Korea | MR-based online interprofessional education (IPE)
-holographic SP, HoloPatient. |
Ischemic Stroke. | IPE- management of ischemic stroke. | 120-minute total.
10 min immersed in HSP (steps 1–3 of CRC), 100-minute IPE (in groups discuss steps 1–3 and then work through steps 4–7 of CRC). |
10 min: debrief participants experiences, reflect on learning and discuss how to take learning forward. |
| Kim et al., 2024, South Korea | MR vs HF. | Infection control practices. | Vital signs assessment, donning and doffing personal protective equipment, providing care in negative pressure isolation room. | 140 min total.
40 min prebrief, 60 min identifying patient information, identifying care and planning, 40 min simulation. |
20 min individual, 40 min team |
| Lee & Baek, 2024, South Korea | VR. | 6 scenarios:
1 respiratory patient, 2 post-lung cancer surgery patient, 3 trauma patient, 4 severity classification (?triage) scenario, 5 myocardial infarction patient, 6 GI bleed patient. |
Problem-solving skills; critical-thinking abilities; performance confidence. | Over 6 weeks, VR simulation nursing program corresponding to each scenario was guided for 30 min using a laptop, smartphone, and tablet PC. | Not stated. |
| Park & Hwang, 2024, South Korea | SP – (professional actors). | Disaster preparedness and nursing in the disaster response phase.
2 Scenarios: 1. disaster site with multiple casualties, 2. evacuation centre for victims needing healthcare. |
Immediate response to disaster scene with mass casualties; chronic disease management during disasters. | 60 min lecture, 2x scenarios, debrief.
Total 4 h and 20 min (one session). |
40-minute debriefing. |
| Rose et al., 2024, Canada | VR. | An online screen based and self-directed resource that included 50 case scenarios spanning medical-surgical, maternal and child, mental health, and gerontology subspecialties.
Students repeated virtual simulation until they achieved a score that represented mastery level performance. |
Not stated. | Not stated. | Faculty for each group of students could include debriefing discussions in their biweekly meetings, although this was not mandatory. |
| Saghafi et al., 2024, Australia | Multiple modalities. | 4 simulations designed according to the CRC (
Levett-Jones et al., 2010)-
4 scenarios: 1 Deteriorating pt (manikin), 2 Challenging pt (SP), 3 Refusal of treatment (video), 4 ‘ward for a day’ (game-based). |
1 Interprofessional communication according to ISBAR, fluids and electrolyte imbalance, recognising and responding to a deteriorating patient;
2. Interpersonal skills, establishing rapport, maintaining dignity; 3 ethical decision making, maintaining dignity; 4. patient allocation, prioritisation, delegation. |
1–20-minute prebrief, 20-minute sim, 1 h debrief,
2–20-minute prebrief, 20-minute sim, 1 h debrief, 3–20-minute prebrief, 20-minute sim, 1 h debrief, 4 – 10-minute prefbrief, 80-minute sim, 80 min debrief. |
Varying times, used a framework – Debriefing for Meaningful Learning (DML) ( Dreifuerst, 2011). |
| Salameh et al., 2021, Palestine | HF. | Six clinical cases of respiratory emergencies that included use of a mechanical ventilator in groups of 2,3 or 4 students
After debriefing, students repeated the scenario for expert role modelling and deliberate practice with feedback until simulation performed accurately and confidently. |
Obtain vital signs; assess breathing sounds; connect heart monitor leads; give oxygen as indicated by patient symptoms,
oxygen saturation, and arterial blood gases; measure central venous pressure and arterial blood pressure; monitor results of laboratory and diagnostic tests; administer medications; and care for the patients on mechanical ventilators. |
6 simulation scenarios (15–20 min each). | Yes, used DML framework ( Dreifuerst, 2011), time not stated. |
| Seok-Young, 2023, Korea | VR. | Child adolescent nursing - 5-year-old with asthma symptoms. | Respiratory system assessment; recognise difficulties; medication administration. | 5 days (45 h) (no other specific details stated). | Not stated. |
| Shim et al., 2019, Korea | Not stated. | Simulation based education program – no specific details stated. | Communication ability; problem solving ability; critical thinking. | 2 h per session over 15 weeks (total 30 h). | Not stated. |
| Sterner et al., 2023, Sweden | Blended simulation – (hands-on simulations with HF manikins and a web-based interactive simulation program- Body Interact (a digital patient simulator). | -Interactive A-E structured assessment and reporting simulation
– Hands on team simulation according to crisis resource management (CRM) criteria – Interactive simulation according to a apply medical and patient-centred care guidelines. |
Oxygen administration and fluid therapy; history-taking; conduct a physical examination; monitor vital parameters; request different diagnostic tests; administer various medications; CRM principles. | Not stated. | Yes, states based on reflection and feedback, time not stated. |
| Yang et al., 2024, South Korea | Not stated. | MRFG simulation group: a paediatric patient with respiratory distress syndrome, a woman in the first stage of labour, and a patient with ischemic heart disease complaining of chest pain.
SRRG simulation group: cardiac arrest scenario of a patient who lost consciousness. |
Patient assessment; emergency response capabilities; situational judgment; treatment for the cause of unconsciousness; medication and emergency procedures based on different electrocardiogram rhythms; communication with the patient care team; post recovery procedures; leadership roles within the patient care team. | MRFG simulation group: 1 role per scenario, 3 scenarios over 3 weeks.
SRRG simulation group: typically 5–6 role rotations, assumed over 1 week. 10-minute orientation, 30- minute prebrief, 20-minute simulation, both groups. |
40-minute debriefing. |
| Zhou et al., 2022, China | SP – (students). | Case scenarios focused on medical, surgical and intensive care units.
Experimental group had simulation with IPE using real members of another discipline. |
Working as part of an interprofessional team to:
perform effective assessments; make correct diagnosis; take effective corrective measures to improve patient care. |
4 h simulated laboratory held over 5 weeks (total 20 h).
Prebrief 5–10 min, each simulation approx. 15–20 min. |
30–40 min, detailed description of debrief stated in paper. |
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