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Knowledge acquisition through
simulation in nursing education: A
systematic review
Dr. Hao Bin Yuan Associate professor, Macao Polytechnic Institute
hbyuan@ipm.edu.mo
Dr. Beverly A. Williams Associate professor, Faculty of Nursing, University of
Alberta, Edmonton, Canada
Dr. Jin Bo Fang Associate professor, West China Hospital, Sichuan
University, China
Introduction
Higher education in nursing should prepare
nursing graduates with the capability to take on
the increasingly challenging roles required of the
nursing profession.
Simulation is a risk-free approach to learning
using a device to emulate a real patient situation
for learning.
Simulation is designed to encourage active
learning and enhance students’ clinical reasoning
and decision making, and achieve the great
improvement of knowledge and clinical skills.
As the use of simulation has increased, there is a
question about whether simulation-based
learning actually demonstrates more effect on
improving learners’ knowledge compared with
the traditional techniques in nursing education?
Objective
The objective of systematic review was to provide
available evidence on the effects of high-fetidity
simulation on knowledge acquisition.
The addressed research questions were:
1. What is the effect of high-fidelity simulations on
knowledge acquisition?
2. Does the available evidence provide information
for enhancing learners’ knowledge through
high-fidelity simulations?
Criteria for considering studies for this review
Type of participants
Experienced the simulation-based training in
nursing educational program
Method
Types of studies
The primary empirical studies determining the effect of
high-fidelity simulations on knowledge acquisition in
nursing education
randomized controlled trials
nonrandomized controlled trials with a
convenience sample
quasi-experimental study with one group
pretest/posttest
Type of intervention
The experimental group experienced high-fidelity
simulation—using human patient simulator or
Emergency Care Simulator (ECS)
The control group served as the traditional techniques
without simulator--lecture combined with
demonstration, online learning with narrated
PowerPoint presentation, or hard-copy textbook study
Types of outcome measures
The multiple-choice questions (MCQs)
NCLEX-style questions
Theoretical exams
Search strategy
The computerized searches from 2000-2011
inCINAHL, Proquest, Cochrane library, Medline,
Science Direct, OVID and Chinese Academic Journal
(CAJ). were performed.
The search terms used on their own and in combination
included: simulation, knowledge, effect, effectiveness,
nursing, education.
Assessment of methodological quality
Primary empirical studies determining the effect
of high-fidelity simulation on knowledge
acquisition in nursing education were considered
Two independent reviewers assessed the eligibility
of each study, its level of evidence and the
methodological quality.
The quality of controlled trials was evaluated with the
Jadad scale focusing on the methods for random allocation,
double-blinding, and withdrawals and drop-outs.
The total scores ranged from 0 to 5 points
poor quality: 0–2 points
high quality: 3–5 points
The interrater coefficient of agreement (kappa-κ) was
reposted as 0.66 for the whole scale (Jadad et al., 1996).
Data extraction
Outcome data were extracted using a data extraction
tool developed by Joanna Briggs Institute for
Evidence Based Nursing and Midwifery (JBIEBNM).
Data were extracted only from papers which met the
quality standards specified above.
For meta-analyses in this review, data were
extracted at a single time point in the range 12
hours to 4 weeks after beginning of implementing
high-fidelity simulation.
One study (Cavaleiro et al., 2009) was excluded
from meta-analysis since the median scores were
used to measure the outcomes of theoretical exam.
Data synthesis
The data from RCTs and nonrandomized controlled trials
were analyzed by Meta - analysis using RevMan software
4.3.
In order to combine conceptually similar outcomes
measured on different instruments, the standardized mean
differences (SMD) for continuous outcome data and their 95
% confidence intervals were calculated rather than weighted
mean differences.
Heterogeneity between combined studies was
tested using the standard chi-square test.
Significant heterogeneity implies that the studies
differ more from each other than would be
expected by chance.
The random effect model was run when
heterogeneity was significantly shown.
If the 95 % CI for the SMD are greater than
zero, this indicates a significant effect favoring
the intervention , whereas confidence intervals
overlapping or less than zero indicate no effect
of the intervention , or an effect favoring the
control.
Results
Initially 30 English and 28 Chinese papers were
conducted to determine the effect of simulations in
nursing educational programs.
Only 11 studies measured the differences in
knowledge acquisition after high-fidelity
simulations and were retrieved in this review.
The reviewed studies included
three Randomized Controlled Trails (RCTs) with a Jadad
quality score of 3
five RCTs with a Jadad quality score of 2
one nonrandomized controlled trial with a convenience
sample
two quasi-experimental studies with one group pretest-
posttest design
High-fidelity simulations promoted knowledge
acquisition in nursing education
5 RCTs (Chen et al., 2009; Cui et al., 2010; Fei et al., 2010; Liu, 2009;
Su et al., 2009)
One nonrandomized controlled Trail (Jiang et al., 2008)
2 quasi-experimental studies with one group pretest/posttest
design (Elfrink et al., 2010; Zheng et al., 2010)
Study
Jadad
score Design Participants Instruments
Duration of
HFS Findings
Corbridge
et al.
2010
level I
2 RCT 20 advanced
nurse
practitioners
MCQs Not mention Both groups were no differences in
knowledge acquisition of mechanical
ventilation (EG 9.2 ±1.3 vs CG 9.1±1.7,
P= 0.891).
Gao and
Zhao
2008
Level I
2 RCT 64 nursing
students
Exam paper 12 hours Both groups were not different at
knowledge test (EG 76.7±8.3 vs CG
7.3±7.0, P>0.05) .
Chen et al.
2009
Level I
2 RCT 96 nursing
students
Exam paper Not mention The EG had higher score than the CG at
knowledge (EG 88.0 ±7.5 vs CG 82.0
±5.1, P=<0.05).
Liu
2009
Level I
3 RCT 105 nursing
students
Exam paper Not mention The EG had higher score than the CG at
knowledge of emergency care (EG
81.36±6.38 VS CG 76.93±6.04, P=0.000).
Su et al.
2009
Level I
2 RCT 62 nursing
students)
Exam paper 4 weeks The EG got higher score than the CG at
knowledge of emergency care (EG 80.8
±5.2 vs CG 75.5±4.8, P<0.01).
Luo
2010
Level I
2 RCT 82 nursing
students
Exam paper 12 hours Both groups did not differ in CPR
knowledge. (EG 83.2 ±9.1 vs CG
81.7±10.5, P>0.05).
Table 1 Description of the reviewed studies in nursing education
Study Jadad
score Design Participants Instruments
Duration of
HFS Findings
Fei et
al.2010
Level I
3 RCT 90 nursing
students
Exam paper Not mention The EG had higher score than the CG at
first-aid knowledge (EG 85.1±2.9 vs CG
82.0±4.2, P <0.05).
Cui et al
2010
Level I
3 RCT 41 registered
nurses
Exam paper 2 weeks The improvement of CPR knowledge in
the EG was significantly higher than that
in the CG (EG 20.3 ± 4.6 vs 11.6 ± 3.1,
P<0.001).
Jiang et
al. 2008
Level II
1 Nonrand
omized-
controll
ed Trail
100 nursing
students
Exam paper Not mention The EG had higher score than the CG at
first-aid knowledge (EG 90.5±2.6 vs CG
81.8± 5.8, P<0.01) .
Zheng
et al.
2010
Level II
1 QES 69
undergraduate
nursing
students)
Exam paper 32 hours The mean score of performance on
application of theoretical knowledge
increased from 23.7 ±1.9 to 24.9 ±1.6
(P<0.01)
Elfrink
et al.
2010
Level II
1 QES 84 nursing
students
NCLEX-
style
questions
Not mention Knowledge was improved after training
(mean difference 0.38~0.59, P=0.000).
Table 1 Description of the reviewed studies in nursing education
In this systematic review, heterogeneity between
combined studies was showed in the
measurements of knowledge (2= 46.88,
P<0.0001), so the random effect model was run
and 95% CI for standardized mean difference
(SMD) with random effect model was reported.
Outcome Citation Experimental Group
Mean ± SD (n)
Control Group Mean ± SD (n)
SMD (95% CI random)
MCQs/ exam
paper
Corbridge et al.(2010) 9.20±1.30 (10) 9.10±1.70 (10) 0.06 (-0.18~ 0.94)
Gao,et al.(2008) 76.75±8.30 (32) 77.32±7.00 (32) -0.07 (-0.56~ 0.42)
Jiang, et al.(2008) 90.50±2.60 (50) 81.80±5.80 (50) 1.92 ( 1.44~ 2.40)
Chen et al.(2009) 88.00±7.50 (48) 82.00±5.10 (48) 0.93 (0.51~ 1.35)
Liu et al.(2009) 81.36±6.38 (53) 76.93±6.04 (52) 0.71 (0.31~ 1.10)
Su et al.(2009) 80.80±5.20 (32) 75.50±4.80 (30) 1.04( 0.51~ 1.58)
Cui et al.(2010) 71.15±7.04(21) 68.28±6.85 (20) 0 41(-0.21~ 1.02)
Fei et al.(2010) 85.10±2.90(45) 82.00±4.20 (45) 0.85 (0.42~1.28)
Luo et al.(2010) 83.20±9.10 (42) 81.70±10.50 (40) 0.15(-0.20~ 0.59)
Total (95% CI random) 0.69(0.29~ 1.09); Test for overall effect Z=3.40, P=0.0007
Table 2 The effect of high-fidelity simulations on knowledge acquisition
The result of meta-analysis indicated that high-
fidelity simulations increased the standardized
mean score of knowledge exam by 0.69 point
(95% CI for SMD with random effect model 0.29
~ 1.09, P=0.0007)
Discussion
The meta-analysis in this systematic review indicates that
high-fidelity simulations do enhance knowledge
acquisition.
High-fidelity simulation can provide the opportunity for
learners to critically analyze their actions, to reflect on
their technical, psychomotor and affective skills, and to
critique the clinical decisions of others.
After analysis of their mistakes and feedback from
the instructor, learners may repeat the scenario to
enhance their learning.
High-fidelity simulation can increase retention of
knowledge through the active learning in
simulation.
However, two thirds of reviewed RCTs are of low
methodological quality since the methods of randomization
and double blinded were not clarified.
There is a lack of formal measurement tools available to
evaluate simulations
Although the results of meta-analysis provided a
comprehensive summary and synthesis of existing empirical
studies, there is still a lack of strong evidence on the
evaluation of high-fidelity simulations for knowledge
acquisition.
Conclusion
The meta-analysis in this systematic review indicates that
high-fidelity simulations do enhance knowledge acquisition.
It is necessary to develop the measurement tools particularly
for high-fidelity simulations, and conduct more RCTs with
high methodological quality and large sample size for
determining whether high-fidelity simulations can enhance
knowledge acquisition among different student groups.
Appendix
The levels of evidence outline by JBI (Hu and Li, 2007)
Level I: Randomized Controlled Trials (RCTs)
Level II: nonrandomized-controlled trial or quasi-
experimental study
Level III: IIIa Cohort Controlled Study
IIIb Case-Controlled study
IIIc Uncontrolled observation study
Level IV: Expert Opinion
Jadad’s Scale (Jadad et al., 1996)
Is the study randomized?
2 points: the method to generate the sequence of
randomization is described and is appropriate (eg. table of
random numbers, computer generated).
1 point: the method to generate the sequence is not
described.
0 point: the method to generate the sequence of
randomization is described and is inappropriate.
Is the study double blinded?
2 points: The method of masking is described and
appropriate (eg. Identical placebo).
1 point: The method of masking is conducted but not
described.
0 point: The method of masking is described and
inappropriate.
Is there a description of withdrawals?
1 point: The withdrawals are defined, as trial participants
who were included in the study but did not complete
observation period or who were not included in the analysis
(but should have been described). If there were no
withdrawals, the report should have said so.
0 point: there is no statement of withdrawals.
This presentation is one part of our research, more findings were published in
the following:
Yuan H. B., Williams B. & Fang J.B. (2012). The contribution of high-
fidelity simulation to nursing students’ confidence and competence: a
systematic review. International Nursing Review,59(1), 26-33.
Yuan H. B., Williams B., Fang J.B. & Ye Q.H. (2012). A systematic review
of selected evidence on improving knowledge and skills through high-fidelity
simulation. Nurse Education Today, 32(3), 294-298.
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