Simulation in Nursing Education a Review of the Research
BMC Med Educ. 2016; sixteen: 152.
Effectiveness of simulation-based nursing didactics depending on fidelity: a meta-analysis
Junghee Kim
The Catholic University of Korea 222, Banpodae-ro, Seocho-gu Seoul, 06591 Democracy of Korea
Jin-Hwa Park
Catholic University of Daegu, 33, Duryugongwon-ro 17gil, Nam-gu, Daegu, 42472 Republic of Korea
Sujin Shin
Ewha Womans University, 52, Ewhayeodae-gil, Seodaemun-gu, Seoul, 03760 Republic of korea
Received 2014 Sep 25; Accepted 2016 May fourteen.
Abstract
Background
Simulation-based nursing education is an increasingly popular pedagogical approach. Information technology provides students with opportunities to exercise their clinical and determination-making skills through various existent-life situational experiences. Nonetheless, simulation approaches autumn along a continuum ranging from low-fidelity to high-allegiance simulation. The purpose of this report was to make up one's mind the upshot size of simulation-based educational interventions in nursing and compare effect sizes according to the allegiance level of the simulators through a meta-analysis.
Method
This study explores the quantitative evidence published in the electronic databases EBSCO, Medline, ScienceDirect, ERIC, RISS, and the National Assembly Library of Korea database. Using a search strategy including the search terms "nursing," "simulation," "human being patient," and "simulator," we identified 2279 potentially relevant articles. Xl studies met the inclusion criteria and were retained in the analysis.
Results
This meta-assay showed that simulation-based nursing pedagogy was effective in various learning domains, with a pooled random-furnishings standardized mean divergence of 0.70. Subgroup assay revealed that issue sizes were larger for high-allegiance simulation (0.86), medium-fidelity simulation (1.03), and standardized patients (0.86) than they were for low-allegiance and hybrid simulations. In terms of cerebral outcomes, the upshot size was the largest for loftier-fidelity simulation (0.50). Regarding melancholia outcome, high-allegiance simulation (0.80) and standardized patients (0.73) had the largest effect sizes.
Conclusions
These results suggest that simulation-based nursing educational interventions have strong educational effects, with particularly big effects in the psychomotor domain. Since the upshot is non proportional to fidelity level, it is of import to use a diversity of educational interventions to meet all of the educational goals.
Keywords: Nursing educational activity, Patient simulation, Educational models, Meta-analysis
Background
Clinical pedagogy in nursing aims to integrate theoretical knowledge from books into practical cognition in existent-life situations and to help students develop their problem-solving skills. Due to rapid changes in clinical placements, patient safety issues, and ethical concerns, students' directly experience with patient care and opportunities to handle problem-based clinical situations have been diminished. Simulation-based clinical education is a useful pedagogical approach that provides nursing students with opportunities to exercise their clinical and conclusion-making skills through varied real-life situational experiences, without compromising the patient'south well-being.
Simulation-based clinical education in nursing refers to a variety of activities using patient simulators, including devices, trained persons, lifelike virtual environments, and role-playing, not but treatment mannequins [one]. With realistic clinical scenarios, simulation-based educational interventions in nursing can railroad train novice as well as experienced nurses, helping them develop constructive non-technical skills, practise rare emergency situations, and providing a diversity of accurate life-threatening situations. The advantages of simulation-based educational interventions include the ability to provide immediate feedback, repetitive practice learning, the integration of simulation into the curriculum, the power to adapt the difficulty level, opportunities to individualize learning, and the adaptability to diverse types of learning strategies [one].
Simulation can exist described as a continuum ranging from low-fidelity simulation (LFS) to high-allegiance simulation (HFS) [two]. Diverse simulation methods can be adapted according to specific learning outcomes and educational levels. Dieckmann [3] warns against placing as well much accent on having optimal equipment and environment that realistically replicate the clinical setting. The required learning outcomes must govern the choice of simulation method [four].
A number of research studies in nursing accept evaluated the effectiveness of simulation-based educational interventions [v]. All the same, the reported effectiveness has varied co-ordinate to the fidelity level of the simulators and the outcome variables. Issenberg et al. [1] found that HFS was constructive for learning in medicine. However, their review was limited to HFS, medical instruction, and learner outcome variables, and did non compare simulation methods. Therefore, a meta-assay synthesizing the results of these studies is needed to provide important insights into the level of simulation fidelity that is most effective for educational use.
The aims of this study were to determine the upshot size of a simulation's touch on on nursing education and compare result sizes according to the allegiance level of the simulators used.
Method
This study was planned and conducted in adherence to PRISMA standards [6] of quality for reporting meta-assay. We also considered the PRISMA criteria based on the PRISMA 2009 checklist in reporting each department, such as introduction, methods, results, and discussion.
Written report pick
Studies published betwixt January 1995 and July 2013 were identified past conducting an electronic search of the post-obit databases: EBSCO, Medline, ScienceDirect, ERIC, RISS, and the National Associates Library of Korea database. The literature search was express to articles published in English or Korean and was conducted using combinations of the keyword phrases nursing, simulation, human patient, and simulator. A full of 2279 potential studies were identified. Titles and abstracts were reviewed for eligibility.
Relevant studies were screened for inclusion based on the following criteria: ane) the study aimed to evaluate the effectiveness of simulation-based education for nursing students, and two) an experimental or quasi-experimental pattern was used. We excluded articles that did not report a control group or that tested the effectiveness of computer-based virtual patients. For abstracts that did not provide sufficient information to determine eligibility, total-length manufactures were retrieved. Disagreement on the inclusion or exclusion of manufactures was resolved by consensus. Of the potentially relevant 2279 manufactures, screening of the championship and abstracts resulted in 317 relevant studies. Later a review of these articles, 96 studies were retained and 3 manufactures included additionally via hand search. These 99 full-text articles were reviewed systematically to confirm their eligibility (Fig.1).
Menstruum of report analysis through different phases of the meta-analysis
Criteria for considering studies for this review
In this study, assessment of the methodological quality of twoscore selected studies was performed past using the Case Control Written report Checklist adult by the Critical Appraisal Skills Programme (CASP) [7]. The CASP appraisement tool was designed to facilitate systematic thinking about educational studies. This tool contains 11 questions in three sections: (1) Are the results of the trial valid? (ii) What are the results? (3) Will the results aid locally? Near of the items were responded with "yes," "no," or "can't tell." The papers were assessed by two independent reviewers using the CASP checklist. Any disagreement that arose betwixt the reviewers was resolved through discussion and consensus with a third reviewer. Forty studies met the inclusion benchmark of 9 or more than out of xi questions answered with "yep" and were consequently considered to exist applicable to this review study. The inclusion criteria for this review were as follows:
Written report participants
This study sampled pre-licensure nursing students, licensed nurses, or nurse practitioners.
Type of interventions
Nosotros defined simulation-based educational intervention every bit educational activity involving one or more of the following modalities: partial-task trainers, standardized patients (SPs), full-body task trainers, and high-fidelity mannequins.
Types of outcome variables
Study outcomes included learning and reaction outcomes. Learning outcomes were categorized into iii domains: cognitive, psychomotor, and affective.
Data coding
The level of fidelity was determined past the environment, the tools and resource used, and other factors associated with the participants [8]. Nonetheless, equally to debriefing, a few selected studies do not indicate the method of debriefing they had used, making it difficult to categorize and discuss the effects of each debriefing method. Thus, we categorized fidelity level co-ordinate to the physical equipment used. Fidelity level was coded every bit low, medium, or high according to the extent to which the simulation model resembled a human being, hybrid, or SP. LFSs were divers as static models or chore trainers primarily made of rubber trunk parts [9, 10]. Medium-fidelity simulators (MFSs) were full-body manikins that accept embedded software and can be controlled past an external, handheld device [10]. HFSs were life-sized computerized manikins with realistic anatomical structures and high response fidelity [11]. We also considered hybrid simulators, which combined 2 or more fidelity levels of simulation. As SP is a person trained as an individual in a scripted scenario for the purposes of education, practise, or evaluation [12], the use of SP was considered because of the different types of fidelity responses, such every bit body expressions and verbal feedback, which cannot exist perceived in other simulation models.
The extracted data were coded by 2 researchers. A coding manual was developed in club to maintain the reliability of coding. The manual included information regarding event size calculations and the characteristics of the study and the report. Differences between coders were resolved by discussion until a consensus was accomplished.
Data synthesis and analysis
The software Comprehensive Meta-Assay version two (Biostat, Englewood, New Bailiwick of jersey) was used to acquit the data assay. Consequence size estimates were adjusted for sample size (Cohen'due south d), and 95 % confidence intervals were calculated to appraise the statistical significance of average outcome sizes.
Stock-still effects models assume that the primary studies have a common issue size. In contrast, random furnishings models attempt to estimate the distribution of the mean outcome size, bold that each primary study has a dissimilar population [13]. A test for heterogeneity of the intervention effects was performed using the Q statistic. As the results of the test for heterogeneity was statistically significant, we used the random effects models to accommodate this heterogeneity for the main effect and sub-grouping analyses. The planned subgroup analyses were conducted on evaluation outcomes.
Results
Study characteristics
We identified 2279 potentially relevant manufactures using the search strategy described higher up, of which 40 met the inclusion criteria. The characteristics of the 40 studies included in this meta-analysis are listed in Tablei. Twenty five of the forty studies (62.five %) used random assignment, whereas the remaining fifteen (37.v %) were nonrandomized. Half of the studies compared education using loftier-fidelity simulators with a control group. Ten studies (25 %) utilized standardized patients. Learners at various levels of training were represented.
Table i
Characteristics of studies included in the assay
| Author (Year) | Country | Random consignment | Sample size experimental/command | Level of fidelity | Expertise-level of students |
|---|---|---|---|---|---|
| Tosterud (2013) | Kingdom of norway | Y | 29/28 | HFS | 1-3year |
| Alfes (2011) | USA | Y | 29/34 | HFS | 1 twelvemonth |
| Andrighetti (2011) | USA | Y | 9/5 | HFS | graduate |
| Johnson (2012) | USA | Y | 19/16 | HFS | graduate |
| LeFlore (2007) | USA | Northward | v/5 | HFS | NP students |
| Maneval (2012) | USA | Y | 13/xiii | HFS | graduate |
| Parker (2011) | United states | Y | 18/23 | HFS | 2 year |
| Shepherd (2010) | Uk | Y | nine/15 | HFS | 3 twelvemonth |
| Smith (2012) | The states | Y | 16/17 | HFS | 3 year |
| Smith (2013) | USA | N | 36/twenty | HFS | four year |
| Thomas (2012) | USA | North | 14/x | HFS | 3-4year |
| White (2013) | USA | Y | 16/38 | HFS | 4 twelvemonth |
| Brannan (2008) | USA | Due north | 54/53 | HFS | |
| Kwon (2012) | Korea | Y | 19/19 | HFS | nurse |
| Kim, D. H. (2012) | Korea | North | 69/62 | HFS | 4 year |
| Kim, S. A. (2012) | Korea | N | 103/68 | HFS | 3 year |
| Kim (2011) | Korea | N | 26/24 | HFS | nurse |
| Yang (2008) | Korea | Due north | 92/75 | HFS | 2 year |
| Yang (2012) | Korea | N | 94/91 | HFS | iii year |
| Lee (2010) | Korea | Y | 35/34 | HFS | ane year |
| Choi, Due east. H. (2013) | Korea | Y | 32/33 | HFS | ii year |
| Ha (2012) | Korea | Y | 60/58 | HFS | 3 yr |
| Heo (2012) | Korea | Y | 26/31 | HFS | 3 year |
| Lee (2013) | Korea | Y | 96/84 | SP/LFS | two year |
| Lee (2009) | Korea | North | 141/142 | SP/HFS | 1 year |
| Chang (2002) | China | Y | 14/14 | LFS | nurses |
| Shepherd (2007) | Commonwealth of australia | Y | 23/25 | LFS | nurses |
| Weiner (2011) | United states of america | Y | 23/23 | LFS | nurses |
| Alinier (2006) | Britain | Y | 49/50 | MFS | 2 year |
| Chang (2010) | Korea | Y | 20/20 | MFS | nurse |
| Becker (2006) | USA | Y | 47/82 | SP | 4 yr |
| Foley (1997) | United states of america | N | 28/38 | SP | nurses |
| Khadivzadeh (2012) | Iran | Y | 28/28 | SP | midwifery students |
| Kim, S. H. (2012) | Korea | North | 29/25 | SP | iii year |
| Roh (2013) | Korea | N | 35/39 | SP | nurse |
| Park (2012) | Korea | Y | 23/21 | SP | 4 year |
| Eom (2010) | Korea | North | 31/31 | SP | 2&iv year |
| Lee (2011) | Korea | Northward | 20/xviii | SP | 2 year |
| Cho (2012) | Korea | Y | 19/nineteen | SP | nurse |
| Choi, S. J. (2013) | Korea | Due north | 22/22 | SP | 3 yr |
Overall analysis
When the studies were combined in the meta-analysis, high heterogeneity was observed (Q = 253.22, P < .001) (Table2). The overall issue size for the random effects model was 0.70, with 95 % conviction intervals of 0.58–0.83 (Table3) (Fig. 2). The possibility of a publication bias was minimal because the funnel plot appeared symmetrical.
Woods plots for principal studies
Table 2
Results of the homogeneity test
| N | Q | p-value | −95 % CI | ES | +95 % CI | SE |
|---|---|---|---|---|---|---|
| 40 | 253.22 | < .01 | 0.54 | 0.59 | 0.64 | 0.02 |
N number of studies, Q homogeneity statistic, ES effect size, SE standard mistake
Table iii
Overall consequence of the meta-analysis, using a random effects model
| N | −95 % CI | ES | +95 % CI | SE |
|---|---|---|---|---|
| 40 | 0.58 | 0.lxx | 0.83 | 0.06 |
Due north number of studies, ES upshot size, SE standard error
Effect sizes by level of simulation fidelity
Studies using HFSs (0.86), MFSs (1.03), and SPs (0.86) had big issue sizes, whereas low-fidelity (0.35) and hybrid (0.34) simulation studies had smaller effect sizes.
Reaction result according to fidelity level
The results of the sub-group analysis for reaction result co-ordinate to allegiance level are shown in Tabular array4. The result size of HFS on reaction was larger than that of LFS (Table4).
Table four
Issue sizes by level of fidelity, to evaluation levels
| Outcomes | Blazon of allegiance | yard | −95 % CI | ES | +95 % CI | SE |
|---|---|---|---|---|---|---|
| HFS | 77 | 0.67 | 0.86 | one.05 | 0.09 | |
| MFS | 5 | 0.18 | 1.03 | 1.88 | 0.43 | |
| LFS | 13 | 0.18 | 0.35 | 0.52 | 0.86 | |
| Hybrid | v | 0.sixteen | 0.34 | 0.52 | 0.09 | |
| SP | 29 | 0.61 | 0.86 | ane.11 | 0.12 | |
| Reaction | HFS | 5 | 0.41 | 0.64 | 0.87 | 0.xi |
| LFS | 4 | 0.01 | 0.27 | 0.54 | 0.13 | |
| Cognitive | HFS | 16 | 0.36 | 0.50 | 0.64 | 0.xi |
| MFS | one | −0.55 | 0.06 | 0.68 | 0.31 | |
| LFS | 1 | −0.11 | 0.47 | 1.05 | 0.29 | |
| SP | seven | 0.12 | 0.32 | 0.52 | 0.x | |
| Affective | HFS | 21 | 0.54 | 0.80 | one.07 | 0.13 |
| MFS | 1 | −0.61 | 0.01 | 0.62 | 0.31 | |
| LFS | 4 | 0.06 | 0.39 | 0.71 | 0.16 | |
| Hybrid | 2 | −0.03 | 0.35 | 0.75 | 0.20 | |
| SP | nine | 0.51 | 0.73 | 0.95 | 0.11 | |
| Psychomotor | HFS | 28 | 0.77 | 1.03 | i.thirty | 0.13 |
| MFS | 3 | 1.41 | 1.76 | 2.11 | 0.17 | |
| LFS | 4 | −0.05 | 0.38 | 0.82 | 0.22 | |
| Hybrid | i | 0.32 | 0.62 | 0.92 | 0.15 | |
| SP | 10 | 0.64 | 1.27 | 1.89 | 0.31 |
g number of effect size, ES effect size, SE standard error
Learning outcome according to fidelity level
The results of the sub-group assay for learning outcomes co-ordinate to fidelity level are shown in Tabular arrayiv. For cerebral outcome, which is a sub-domain of learning, the consequence size was the highest for HFS (0.50), followed by LFS (0.47), SP (0.32), and MFS (0.06).
Regarding melancholia outcome, HFS (0.80) and SP (0.73) had the largest effect sizes, whereas LFS (0.39) and hybrid (0.35) simulation studies had smaller consequence sizes. MFS (ane.76), SP (1.27), and HFS (ane.03) showed large event sizes in the psychomotor domain (Tableiv).
Discussion
The present study provided meta-analytical data for evidence-based education through a comprehensive analysis of simulation-based nursing teaching with diverse backgrounds and characteristics. Compared with our previous commodity "Effectiveness of patient simulation in nursing teaching: meta-analysis" [fourteen], the current written report included an boosted electronic search of Korean databases such as RISS and the National Assembly Library of Korea database. Through this procedure, xx Korean papers were included additionally and half of papers were Korean. This could cause different issue compared to previous one. In improver to including a reaction outcome according to fidelity levels, effect sizes based on outcomes and allegiance level were identified. A systematic search of the literature resulted in 40 published studies that were eligible for inclusion in this meta-analysis. These main studies provided evidence of the effects of simulation-based nursing instruction in various evaluation and learning environments.
Random assignment studies deemed for 62.5 % of the studies included. This represents a noticeable increment in randomized enquiry designs, which made up less than 30 % of studies in a systematic review conducted 10 years ago on HSF in medical educational activity [1]. That review found that HFSs were used in 50 % of studies, and 25 % used SPs, which is similar to the findings of the study past Kim, Park, and Shin [xv]. This confirms the relatively high usage of HFSs and SP in nursing education.
The medium-to-big effect size (0.70) suggests that simulation-based nursing education is effective. This is consistent with the findings of a study on health professional education [16], which reported that technology-enhanced simulation training produced moderate to large effects.
Regarding simulator fidelity level, HFS (0.86), MFS (1.03), and SP (0.86) displayed larger effect sizes compared to LFS or hybrid simulation. This result supports the findings of a previous meta-assay of simulation in wellness professions, showing that HSF offers benefits over LFS [17]. All the same, these findings should be interpreted with caution. Recent studies advise that the degree of realism required of a simulation is a function of the learning chore and context, and can therefore vary widely for different areas of educational outcomes [17].
In the reaction domain, which includes satisfaction and learning attitudes, HFS had a larger consequence size than LFS. Satisfaction levels are high among students participating in simulation learning that utilizes human simulators or SP [18]. Considering that problem-based learning (PBL) lessons were establish to raise student attitudes more than traditional lectures [nineteen], student participation and actual activity appear to have positive effects on satisfaction and learning attitudes.
In the sub-grouping analysis for learning outcome co-ordinate to allegiance level, the outcome size was the largest for psychomotor outcome, followed by affective and cognitive outcomes. This result differs somewhat from the meta-assay on the effects of PBL [19], in which issue sizes were the largest for psychomotor outcomes, followed by the cognitive and affective domains. This departure is interpreted as reflecting PBL'due south emphasis on reasoning based on problems and cases, compared to the actual clinical exercise emphasized in simulation-based learning.
Specifically, the effect size of cerebral issue was the largest for HFS (0.50), while the lodge for affective outcome was HFS (0.80), followed by SP (0.73). In the psychomotor domain, the order was MFS (one.76), SP (1.27), and HFS (1.03). These results demonstrate that HFS and SP are effective in producing cognitive and affective outcomes; however, to achieve psychomotor learning outcomes, technical training using MFS would exist more helpful, which concurs with the lack of positive association between fidelity and procedure skills [17].
Even so, the nowadays study has the limitation of non considering learning-related factors in the analyses based on the fidelity level of simulators. Even though debriefing has go more crucial in simulation-based learning and the methods take diversified over the years, a few selected studies do not indicate the methods of debriefing they had used, making it difficult to categorize and discuss the furnishings of each debriefing method. This may be because information technology is customary to omit debriefing while learning from low fidelity simulations, especially for preparation simple nursing skills. As such, the present report has the limitation of not considering learning-related factors from debriefing at each fidelity level of simulators, including reflection, feedback, and a range of debriefing methods (cocky-debriefing, multimedia debriefing, and/or in-simulation teacher facilitated debriefing). In addition, nosotros did non include studies published in languages other than English or Korean.
Despite such limitations, this written report demonstrated that simulation-based nursing educational activity has an educational effect, with specially strong effects in the psychomotor domain. Since the furnishings are not proportional to fidelity level, educational interventions should be broad enough to satisfy educational goals, all of which are supported by the results presented above. In addition, a contempo report reported that debriefing was the almost important factor in simulation, with positive effects from self-debriefing and video-facilitated teacher debriefing [20]. Based on these findings, the clinical reflection process needs to be improved to increment the learning effects in the cognitive domain.
Conclusions
Our results indicated that simulation-based nursing educational interventions were effective with particularly large effects in the psychomotor domain. In addition, the effect of simulation-based nursing education was non proportional to fidelity level. Therefore, it is of import to employ an appropriate level of simulation to meet all of the educational goals and outcomes.
Acknowledgement
We capeesh the back up by Soonchunhynag University Library.
Funding
No funding was received.
Availability of data and materials
Data from journals used in this work found on publicly bachelor repositories.
Authors' contribution
All authors contributed to the design of the report. JK performed the statistical assay and wrote the outset draft. JP carried out information collection and data coding. SS participated in its pattern and coordination, helped to draft the manuscript, and revised the manuscript. All authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Consent for publication
Consent for publication is non applicable for this work.
Upstanding approval and consent to participate
Upstanding approval and consent from participate are non applicable for this written report.
Abbreviations
| HFS | high-allegiance simulation |
| LFS | low-fidelity simulation |
| MFS | medium-fidelity simulation |
| PBL | trouble-based learning |
| SP | standardized patients |
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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4877810/