Pros and Cons of Simulation in Medical Education a Review Krishnan
J Med Cyberspace Res. 2019 Mar; 21(3): e11529.
Clinical Virtual Simulation in Nursing Didactics: Randomized Controlled Trial
Monitoring Editor: Gunther Eysenbach
José Miguel Padilha, PhD, 
# 1 Paulo Puga Machado, PhD,2 Ana Ribeiro, PhD,2 José Ramos, MSc,3 and Patrício Costa, PhDfour
1 Nursing Schoolhouse of Porto; CINTESIS – Tech4edusim, Porto, Portugal,
2 Nursing School of Porto; CINTESIS – NursID, Porto, Portugal,
three Nursing School of Porto, Porto, Portugal,
4 Life and Health Sciences Inquiry Plant (ICVS), School of Medicine, University of Minho, Braga, ICVS / 3B's–PT Government Acquaintance Laboratory, Braga / Guimarães, Portugal, Faculty of Psychology and Education Sciences, University of Porto, Porto, Portugal
José Miguel Padilha, Nursing School of Porto; CINTESIS – Tech4edusim, Street Dr António Bernardino de Almeida, Porto, 4200-072, Portugal, Phone: 351 225 073 500, Fax: 351 225 096 337, Email: tp.fnese@ahlidapleugim.
José Miguel Padilha
ane Nursing School of Porto; CINTESIS – Tech4edusim, Porto, Portugal,
Paulo Puga Machado
2 Nursing School of Porto; CINTESIS – NursID, Porto, Portugal,
Ana Ribeiro
2 Nursing School of Porto; CINTESIS – NursID, Porto, Portugal,
José Ramos
3 Nursing School of Porto, Porto, Portugal,
Patrício Costa
4 Life and Wellness Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, ICVS / 3B's–PT Government Associate Laboratory, Braga / Guimarães, Portugal, Faculty of Psychology and Educational activity Sciences, Academy of Porto, Porto, Portugal
Received 2018 Jul 10; Revisions requested 2018 Oct 14; Revised 2018 Dec 21; Accustomed 2019 January 3.
- Supplementary Materials
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Multimedia Appendix 1.
Consort-EHEALTH checklist (V 1.6.1).
GUID: BA24BCA0-D0B5-4295-BB0C-D7B8B6F0FC42
Abstract
Background
In the field of wellness care, knowledge and clinical reasoning are key with regard to quality and conviction in conclusion making. The development of knowledge and clinical reasoning is influenced not simply past students' intrinsic factors but also by extrinsic factors such as satisfaction with taught content, pedagogic resources and pedagogic methods, and the nature of the objectives and challenges proposed.
Nowadays, professors play the part of learning facilitators rather than elementary "lecturers" and face students as active learners who are capable of attributing individual meanings to their personal goals, challenges, and experiences to build their own noesis over time.
Innovations in health simulation technologies have led to clinical virtual simulation. Clinical virtual simulation is the recreation of reality depicted on a computer screen and involves real people operating faux systems. It is a type of simulation that places people in a central role through their exercising of motor control skills, conclusion skills, and communication skills using virtual patients in a variety of clinical settings.
Clinical virtual simulation tin provide a pedagogical strategy and can act as a facilitator of noesis retention, clinical reasoning, improved satisfaction with learning, and finally, improved cocky-efficacy.
However, niggling is known about its effectiveness with regard to satisfaction, cocky-efficacy, noesis retention, and clinical reasoning.
Objective
This study aimed to evaluate the event of clinical virtual simulation with regard to knowledge retention, clinical reasoning, self-efficacy, and satisfaction with the learning experience among nursing students.
Methods
A randomized controlled trial with a pretest and 2 posttests was carried out with Portuguese nursing students (North=42). The participants, split into 2 groups, had a lesson with the aforementioned objectives and timing. The experimental group (due north=21) used a case-based learning approach, with clinical virtual simulator as a resources, whereas the command group (n=21) used the same case-based learning approach, with recourse to a low-fidelity simulator and a realistic surroundings. The classes were conducted past the usual course lecturers.
We assessed knowledge and clinical reasoning before the intervention, after the intervention, and 2 months later, with a true or faux and multiple-selection knowledge test. The students' levels of learning satisfaction and self-efficacy were assessed with a Likert calibration later on the intervention.
Results
The experimental group made more significant improvements in knowledge after the intervention (P=.001; d=one.13) and 2 months after (P=.02; d=0.75), and information technology also showed higher levels of learning satisfaction (P<.001; d=1.33). We did not find statistical differences in cocky-efficacy perceptions (P=.9; d=0.054).
Conclusions
The introduction of clinical virtual simulation in nursing pedagogy has the potential to meliorate knowledge retention and clinical reasoning in an initial stage and over time, and it increases the satisfaction with the learning experience among nursing students.
Keywords: clinical virtual simulation, nursing instruction, virtual patient, user-computer interface
Introduction
Nursing pedagogy
The educational activity of nursing students has e'er been a challenge for governments, health educators, wellness managers, and the students themselves to ensure the quality and condom of learning and clinical do.
Twenty-showtime century students have grown up using information and communications technologies (ICT) on a day-to-twenty-four hour period basis. The employ of ICT leads to unlike learning processes and information structuring processes [1].
Professors and managers should carry in mind that these students are able to access information in existent time, to use parallel processes and multitask; in addition, they adopt graphics to text, they function best when networked, and they demand instant gratification and frequent rewards [2].
These students' ICT skills telephone call for innovation in the pedagogical strategies in health instruction underpinned by a constructivist prototype of health teaching [3]. Nowadays, professors play the role of learning facilitators rather than simple "lecturers" and face students every bit active learners who are capable of attributing individual meanings to their personal experiences and building their ain cognition over time. An active and constructive educational environs based on challenges and learning objectives will promote deeper learning, emphasizing agreement and the application of knowledge over memorization and recall [4-8].
Innovation in simulation technologies has made available high-allegiance simulators that have supported the change in the health education image. The utilise of high-fidelity simulators has improved the acquisition of noesis and skills and strengthened quality and safety in clinical exercise [3,9-15]. However, we accept been facing challenges with the increasing cost of simulators, the difficulties of space management, and the low number of clinical scenarios bachelor.
Clinical Virtual Simulation
Developments in digital and virtual technology have eased the way to recreating reality using virtual patients [16] depicted on a figurer touchscreen (clinical virtual simulation). Clinical virtual simulation is the recreation of reality depicted on a estimator screen, and it involves real people operating simulated systems. It is a type of simulation that places people in a primal function through the exercising of their determination-making, motor control, and communication skills [11]. Clinical virtual simulation uses virtual patients in dynamic and immersive clinical environments ranging from prehospital environments to environments in the community (Figures 1 and 2). The concept is based on the virtual patient being accessed through a variety of multimedia, screen-based interactive [17] and dynamic patient scenarios, which are supported by physiological algorithms. Clinical virtual simulation increases interaction and feedback [18] and raises both the perception of self-efficacy and the user's satisfaction levels [19]. The employ of clinical virtual simulation in the development of nursing competences improves operation [20] and competences related to psychomotor skills [21], critical thinking [22], clinical skills [23], and conclusion making [17].
Clinical virtual simulation in hospital environment.
Clinical virtual simulation in environments in the community.
The latest technological advances in clinical virtual simulation have improved realism and dynamic interaction, with the possibility of thousands of clinical scenarios depicted on a touchscreen table or on the Web. All the same, nowadays, little is known about its effectiveness with regard to students' learning satisfaction, self-efficacy, knowledge retention, and clinical reasoning, specially when using the latest advances in clinical virtual simulation.
As professors in the field of health, we are concerned virtually students' learning satisfaction and effective learning outcomes [13]. This report intended to assess the effectiveness of clinical virtual simulation in raising levels of learning satisfaction, self-efficacy, knowledge retention, and clinical reasoning amid nursing students.
Methods
A randomized controlled trial and a prospective and analytical study was conducted between March and May 2017 with a pretest and two posttests.
Participants and Allocation Process
The participants were volunteer graduation students in the second year at the Nursing School of Porto in Portugal, enrolled in the course "Corporal Body Responses 1" (respiratory, cardiac, and urinary systems). This report was accomplished through an elective curriculum made available to all students. All the students enrolled in the course (North=128) were invited by electronic mail to be volunteers in the report. Those who did volunteer were invited to an initial meeting at which 56 educatee volunteers were present, all of whom accepted the invitation and gave informed consent. The volunteers filled out a questionnaire with sociodemographic and educatee information (average current course grade, number of European Credit Transfer System credits achieved as part of the nursing degree, and average course required for admission into the caste course); these information were used in the randomization process. The anonymization of students was performed past the assignment of a number with six digits chosen by the pupil, with no possibility of the students being identified by the researchers.
The study sample size was determined considering a 1-tailed, unpaired t test, a type I error of 0.05, a statistical power of 0.80, and an consequence size of d=0.eighty. Using Chiliad*Power3 [24] this study required a total of 42 students, 21 per group.
Students were allocated to each group through a simple random allocation using IBM SPSS Statistics version 24.
One calendar week after the initial coming together (and afterward the randomization process), all the 56 volunteer students were invited to another coming together, which took place immediately before the intervention. At this second meeting, students were invited to do the outset cognition and clinical reasoning test (assessment before intervention—A0). Immediately after this, the students were directed, according to identification number (which merely they were able to identify), to the classroom where they were informed nigh which group they had been allocated to.
Both groups received a laboratory course of 45 min, with the aim of activating noesis and developing clinical reasoning skills in the field of the respiratory procedure in relation to ineffective airway clearance and hypoxia. With the experimental group, a instance-based learning arroyo was used, with recourse to a clinical virtual simulator scenario (Body Interact) facilitated by the regular discipline instructor.
The clinical virtual simulator (Body Collaborate) presents virtual patients backed upwardly past a physiological algorithm that recreates a dynamic wellness condition that responds to user interventions. The clinical scenario is initiated past a briefing; subsequently, the user tin interact with the virtual patient through dialogues, monitoring the physiological parameters, observation and concrete examination, the prescription and/or analysis of complementary examinations, and the prescription of intervention and/or pharmacological treatment. The responses to and the development of the clinical case are dynamic and provisional on the decisions taken. The closure of the clinical instance is determined either by the successful resolution of the scenario or by the amount of time that has elapsed (every bit defined past the user). Immediately after the simulation ends, a differential diagnosis interface is presented. After the simulation has concluded, the simulator provides a debriefing tool whereby three categories of data can be analyzed: the simulation report, the simulation timeline, and the functioning report. In the simulation report, the right differential diagnosis and the option chosen by the user are presented. All the deportment carried out and the hemodynamic consequences are presented on the timeline together with all the complementary diagnosis examinations that were requested. In the simulation report, performance scores are given for iii categories of data: concrete examination, diagnosis, and therapeutic activities. In each ane of these categories, the decisions made and their appropriacy are presented, every bit well as the best decision, on the basis of the show. The debriefing tool as well provides the scientific references that support the clinical scenario and its optimal resolution.
The control group received a laboratory course of 45 min, with the aforementioned aim, using the aforementioned case-based learning approach only making use of a depression-fidelity simulator and a realistic surroundings (pedagogical strategies that were already used in the nursing school), guided throughout past the regular bailiwick teacher. For both groups, there was a simulation pedagogical strategy of briefing (5 min), simulation (20 min), and debriefing (20 min), with the aforementioned structure and contents.
Immediately subsequently the end of the intervention (the laboratory grade), all the students were invited to a second examination (assessment after intervention—A1), and 2 months later, they were invited over again to a tertiary test (cess follow-up—A2).
In all the knowledge assessments, we used the same true or false and multiple-choice test, which had been developed by the usual course lecturers. These cognition assessments were based on features intrinsically related to the clinical reasoning practical inside the specific scenario. In the assessment immediately after the intervention with both groups, nosotros too assessed the students' satisfaction levels with the simulation, and their general perception of self-efficacy.
The assessment of student satisfaction was conducted using a Portuguese version [25] of the Learner Satisfaction with Simulation Tool [nineteen], a 10-betoken Likert calibration. The assessment of their perception of self-efficacy was conducted with a Portuguese version [26] of the General Cocky-efficacy Scale [27], a 5-bespeak Likert scale. The Cronbach alpha coefficients of the scales have been illustrated in Table 1.
Tabular array 1
Cronbach blastoff coefficients for the original, for the Portuguese versions, for this study's sample of the Learner Satisfaction with Simulation Tool, and for the General Self-efficacy Scale.
| Scales | Original version, Cronbach alpha | Portuguese version | Study sample | ||
| Cronbach alpha | Correlation item-item total | Cronbach alpha | Correlation particular-item total | ||
| Learner Satisfaction with Simulation Tool | .952 | .969 | .633-.823 | .970 | .660-.910 |
| The General Self-Efficacy Scale (average for 25 language versions) [28] | .860 | .760 | .290-.530 | .882 | .527-.726 |
Information Analysis
We performed the Kolmogorov-Smirnov examination with the Lilliefors correction to check for the normality assumption. We obtained statistically nonsignificant results for both groups in the 3 variables nether study, meaning that the normality assumption was met.
The main variable under study (the development of knowledge and clinical reasoning) was obtained by the difference between the assessment earlier and after the intervention. Positive values reveal comeback between the two assessments.
To compare both groups in the relevant variables under study, we used an unpaired t student to compare averages.
When the homogeneity of variances assumption was violated, the Welch correction was used.
A multivariate analysis of variance (MANOVA) was performed to compare the ii groups across the 3 measurement points.
The results were considered statistically significant for P<.05, and regarding effect size measures, Cohen criteria (1988) [29] were considered to rank the size of the magnitude effect (Cohen d: 0.two—small, 0.5—medium, and 0.8—large; fractional Eta-squared: 0.02—small, 0.13—medium, and 0.26—large).
This study was approved by the ethics committee of the Nursing Schoolhouse of Porto with the number 2017/1. This randomized controlled trial does non possess a trial identifier as information technology is not legally required in the context of the study.
Results
A total of 42 students from the second year of a degree course participated in this study (n=21 in the experimental group and n=21 in the command group). The average age of the students was 19.9 (SD i.99) years, and 95% (40/42) of the students were females. The flow diagram (Figure 3) represents the randomization and allocation procedure. Tabular array 2 shows the results of the variables under analysis.
Flow diagram of sample randomization and allotment process.
Table 2
Means of sample characteristics and study variables and SDs.
| Written report variables | Command group | Experimental grouping | |
| Sex, n | |||
| | Female | 19 | 21 |
| | Male person | 2 | 0 |
| Age, hateful (SD) | 20.29 (2.nineteen) | 19.29 (0.46) | |
| Hateful entry form to the caste course, hateful (SD) | 15.54 (i.46) | fifteen.97 (0.85) | |
| European Credit Transfer System credits on the degree course, mean (SD) | 87.29 (6.90) | 86.86 (5.41) | |
| Caste grade mean class and so far, mean (SD) | 13.21 (0.67) | 13.42 (0.99) | |
| Self-efficacy perception, mean (SD) | 30.14 (4.29) | xxx.38 (4.57) | |
| Learning Satisfaction, mean (SD) | 7.47 (1.58) | 9.04 (0.55) | |
| Knowledge assessment before intervention (A0), mean (SD) | 9.87 (two.24) | 10.15 (1.27) | |
| Knowledge cess later on intervention (A1), mean (SD) | x.51 (one.89) | 12.47 (1.57) | |
| Noesis assessment follow-up (2 months; A2), mean (SD) | 10.55 (1.81) | 11.93 (ane.84) | |
Knowledge Memory and Learning Satisfaction
The results of the students' t tests showed the beingness of statistically significant differences in knowledge retentiveness after the intervention (t twoscore=−three.656; P=.001; d=1.xiii), knowledge retention 2 months subsequently (t 40=−2.439; P=.02; d=0.75), and in learning satisfaction (t 40=−4.309; P<.001; d=ane.33). The students in the experimental grouping presented better outcomes in knowledge retention and learning satisfaction than students in the command group. The values of the Cohen d reinforce the magnitude consequence of the intervention.
The MANOVA consequence was meaning for fourth dimension (Pillai Trace; F 2,39=13.4, P<.001, fractional eta squared=.407) and for the interaction term fourth dimension x group (F 2,39=4.45, P=.02, fractional eta squared=.186), indicating that in that location are differences in the students' levels of knowledge across time and that those differences are grouping dependent. Differences amidst moments were tested through a Bonferroni test, and significant results were observed for A0-A1 (P<.001), for A0-A2 (P=.02) but not for A1-A2 (P>.99; A0—assessment before intervention, A1—cess after intervention, A2—cess follow-upwards). Regarding comparisons of the different groups across time, significant differences were observed for A0-A1 (P<.001), for A0-A2 (P=.01), but non for A1-A2 (P=.75). No significant differences were obtained for the command group (A0-A1: P=.44, A0-A2: P=.99, A1-A2: P>.99).
Self-Efficacy Perception
In self-efficacy perception, the results did non testify statistical differences between the groups: t 40=−0.174, P=.nine, d=0.054.
Statistically significant results were also found for the overall upshot of the grouping at the three measurement points: F 1,twoscore=ten.2, P=.003, partial eta squared=.204. These results signal that xx.4% of students' scores across the 3 measurement points are explained by the group to which the students were assigned.
Discussion
Principal Findings
This paper indicates that clinical virtual simulation improves knowledge retentiveness and initial clinical reasoning over time (two months) and improves student satisfaction with learning, without influencing the perception of general efficiency. Clinical virtual simulation enabled a xx.four% improvement in students' knowledge memory and clinical reasoning in the context of the study. This study showed that clinical virtual simulation is a pedagogical strategy that, combined with other strategies such as conference, simulation, and debriefing, improves both initial cognition memory and cognition retention over time. Clinical virtual simulation also raises the level of satisfaction with the learning experience among nursing students. These results reveal the fit of clinical virtual simulation with the new generation's expectations and means of learning. The effect of the utilize of clinical virtual simulation every bit a pedagogical strategy in improving cognition retention and clinical reasoning and students' satisfaction levels showed a lucifer with the features of twenty-first century nursing students. The twenty-first century nursing students had already shown high levels of usefulness, ease, and intention to apply clinical virtual simulation [thirty]. In add-on, this paper now indicates that the utilise of clinical virtual simulation can amend knowledge retention, clinical reasoning, and satisfaction with learning.
These results are in line with the results of other studies, where the authors establish that levels of knowledge [31-33] and satisfaction [14] with the learning process ameliorate with the use of virtual simulation.
Clinical virtual simulation brings together such strategies every bit gaming and problem-based learning, using an interactive and dynamic 3-dimensional technology that encourages active and disquisitional action-based learning.
We did not find any differences in the self-efficacy perception of the students using this strategy. This is in line with the theoretical construct of Bandura's [34] cocky-efficacy theory, in which the cocky-efficacy perception results from the interaction of different variables over time, and in this study, there was only 1 intervention with ane course.
Clinical Virtual Simulation in Nursing Didactics
Clinical virtual simulation is a complementary pedagogical strategy that provides the opportunity to improve clinical reasoning skills in students through exposure to a large number of clinical scenarios. The use of clinical virtual simulation as a pedagogical strategy should exist integrated and coordinated with other pedagogical strategies in classes [35,36] and with other resources, such equally loftier-, medium-, and low-tech simulators in utilise in our simulation labs to maximize the evolution of cognitive, affective, and psychomotor skills in the students.
This written report is in line with the writings of Berman and colleagues [17]. Clinical virtual simulation is an interactive learning strategy that captures students' intrinsic motivations and satisfaction, and information technology is focused on the awarding of foundational knowledge oriented toward a clinical learning challenge that recreates clinical scenarios with which students volition be confronted in future clinical contexts. It allows a competency-based education and assessment that consequently enables a deep level of learning and the evolution of clinical expertise. Clinical virtual simulation tin contribute toward reducing clinical fault and improving the safety and quality of health care.
Clinical virtual simulation responds to the difficulties of managing laboratorial space, enabling teaching institutions to aggrandize the number of clinical scenarios bachelor for educatee grooming. Clinical virtual simulation makes preparation in the classroom context feasible and broadens the availability of scenarios in the Web surround, a feature that, in our feel, enables a tremendous increment in the number of students receiving individual training and a significant reduction in the costs of simulation use per student.
Equally limitations of this study, we identified the fact that it was merely carried out in a single context, with second-year nursing students, and on a single course with content related simply to the respiratory process. We also judge that the follow-up time was too short to fully evaluate the noesis retentivity over time.
In light of these promising results, we propose the replication of this study with a multicentric and prospective pattern on different wellness scientific discipline courses.
Conclusions
Clinical virtual simulation is a pedagogical strategy that contributes to the comeback of knowledge retention initially and over time and increases the students' satisfaction.
This paper reveals the impact of clinical virtual simulation use in nursing education and helps professors in the field of health to exist aware of its pedagogical utility and appropriacy.
These results show the potential of clinical virtual simulation to exist an constructive pedagogical strategy to build an educational environment that supports the development of clinical competences in the next generation of care providers, contributing toward improvements in the condom and quality of health care.
Acknowledgments
This study was supported by European Regional Development Fund through the performance POCI-01-0145-FEDER-023342 funded past the Programa Operacional Competitividade e Internacionalização-COMPETE2020 and past Portuguese National Funds through Fundação para a Ciência e a Tecnologia.
Abbreviations
| ICT | data and communications technologies |
| MANOVA | multivariate analysis of variance |
Multimedia Appendix 1
CONSORT-EHEALTH checklist (V 1.six.1).
Footnotes
Conflicts of Interest: None alleged.
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