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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Questions?