Natl. J. Physiol. Pharm. Pharmacol. (2025), Vol. 15(3): 240-245

Research Article

10.5455/NJPPP.2025.v15.i3.4

The impact of simulation and virtual learning about the applied physiology of ECG and its clinical application among the undergraduate medical students

Rachula Daniel^*, Prabhavathi K. and Saravanan Ayyavoo

Department of Physiology, SRM Medical College Hospital and Research Centre, SRM Institute of Science and Technology, Kattankulathur, India

*Corresponding Author: Rachula Daniel, SRM Medical College Hospital and Research Centre, SRM Institute of Science and Technology. Email: rachulaj [at] srmist.edu.in

Submitted: 17/12/2024 Accepted: 11/02/2025 Published: 31/03/2025

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Abstract

Background: An undergraduate medical student, in their first professional year, is required to know the applied physiology of electrocardiogram (ECG). This includes recording and interpreting normal and abnormal ECG. Usually, the topic is taught in classes as didactic lectures. However, teaching scenarios that occur in real-life situations within the confines of a classroom may not produce optimal learning outcomes.

Simulation-based learning is an interactive and active learning methodology that provides immersive and experiential learning to students. We conducted this study to determine whether simulation and virtual learning have an impact on the applied physiology of ECG and its clinical application among undergraduate medical students.

Aim: To evaluate the impact of simulation and virtual learning on the applied physiology of ECG and its clinical application among undergraduate medical students.

Methods: A total of 250 undergraduate students in their first professional year of MBBS, who were between 17 and 24 years old and belonged to both male and female genders, were included in this experimental study. Each student had a hands-on experience of the ALS simulator using an ECG machine, for recording the ECG and the SIMMAN 3G plus Hi-fidelity simulator to interpret normal and abnormal ECG. This was done to facilitate a better understanding of the applied physiology of ECG. A self-administered, pretested questionnaire was administered with pre- and post-test questionnaire. The data were analyzed using SPSS version 22.0 with a paired t-test.

Results: The participants of the study were aged between 17 and 23 years, of which 204 (81.6%) were between 17 and 19 years, 42 (16.8%) were between 19 and 22 years, and 4 (1.6%) were above 22 years. Regarding the sex of the participants, 97 (38.8%) belonged to male and 153 (61.2%) belonged to the female sex. The pre- and post-test results were evaluated, which suggest that the intervention had a statistically significant positive impact on the participant scores, as the p value is < 0.05. It was found that the pre-assessment scores had the largest effect size, followed by sex and age. With an increase in age, the post-assessment score decreases by 0.203 points, and the female participants are expected to have a post-assessment score that is 0.508 points higher than the male participants.

Conclusion: This study highlighted that simulation and virtual learning about the applied physiology of ECG and its clinical application have an impact on undergraduate medical students.

Keywords: Physiology, Simulation, ECG, Medical education.

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Introduction

Simulation is well known to be the creation of an artificial but realistic representation of a real-life process to enable learners to achieve specific educational learning outcomes (Flangan et al. 2004) Experiential learning, which is the essence of simulation, is an interactive and active process. It is a method of active experimental learning, which is commonly used in training or performance testing. The design of a simulated environment is based on the principle that it resembles the real-life environment as closely as possible so that the students benefit from an immersive experience, leading to optimal learning outcomes (Robertson et al. 2009).

We are aware that there has been a worldwide shift in the method of medical education toward experiential medical learning. However, applying this kind of “Hands-on” learning on real patients is not acceptable when a large group of students need to be trained due to legal and ethical issues.

The main objective of simulation-based training is to facilitate active and interactive learning by being thoroughly immersed in the clinical scenario, reflecting on the learning experience and repeated practice, without the fear of distressing the patient or exposure to risks such as blood loss or radiation, which are inherent in a real-life (Sood and Adkoli 2000) It is well known that simulation-based education plays a valuable role in skills-training, by providing “hands-on-learning” on simulators. These simulators vary from low, medium, or Hi-fidelity, based on the resemblance to reality that they offer, the Hi-fidelity simulators providing the closest resemblance to reality. Learners may make mistakes and correct themselves without harming or distressing the patient (Ziv et al. 2005).

According to the competency-based medical education (CBME) curriculum and regulations, simulation-based virtual learning (SVL) is given significant importance in the first professional year, as it is a certifiable skill and also forms a part of their formative assessment.

The undergraduate medical student in their first professional year is required to have knowledge of certain clinical skills in cardiovascular physiology, as part of SVL under the CBME curriculum.

Although there have been many studies about simulation-based training of postgraduate students, we find that there have not been many studies relating to the effect of simulation-based certifiable skills such as electrocardiogram (ECG), among the undergraduate medical students of the first professional year, which has been introduced recently (Paskins and Peile 2010; Khan et al. 2011; Subramanian et al. 2012; Borggreve et al. 2017; Riaz 2019; Morris and Conroy 2020).

Students are taught ECG in cardiovascular physiology in class; hence, we want to include hands-on experiential learning on simulators on ECG to understand how effective this module would be.

Although there are many studies based on simulation-based education, there has been no specific study on simulation and virtual learning for undergraduate students, which has been introduced recently.

Students are usually taught ECG in applied physiology during their physiology theory classes in the form of didactic lectures. It is also being included as a certifiable undergraduate competency.

As ECG is well-known to be an important investigative tool in clinical practice, we selected ECG as the subject of our study. It was then decided to teach undergraduate medical students, the applied physiology of ECG and its clinical application, using simulation and virtual learning, to understand its impact.

Aim: To evaluate the impact of simulation and virtual learning on the applied physiology of ECG and its clinical application among undergraduate medical students.

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Materials and Methods

This was an experimental study conducted with 250 undergraduate medical students in their first professional year.

Students aged 17–24 years of male and female sexes were included as study participants.

The study was conducted over a period of 3 months, from February 1, 2024 to April 1, 2024, on the premises of SRM Stratus Centre for Medical Simulation, SRM Medical College Hospital and Research Centre, Kattankulathur, Tamilnadu, India.

Institutional Ethical Committee clearance (Reg. No: ECR/8943/TN/2013/RR-19) was obtained for the study and written informed consent was obtained from all participants before the study.

The preliminary data regarding their age and sex were collected from each participant and were entered into an Excel spreadsheet. A self-administered pretested questionnaire, which was based on the applied physiology of ECG, was completed by the participants.

The students were first briefed on the objectives of the SVL session, which included

1. To record a 12-lead ECG using an ECG machine on a high-fidelity simulator and describe the various settings and leads used in recording the ECG.

2. To interpret normal and abnormal ECG rhythms, using a high-fidelity simulator (SIMMAN 3G Plus).

Skill station 1: Recording a 12-lead ECG using an ECG machine on a high-fidelity simulator.

At the outset, the participant was encouraged to use good communication skills such as greeting, introducing himself or herself, explaining the procedure of recording an ECG in simple terms, and then obtained verbal consent. The ECG is then recorded on the high-fidelity simulator.

Recording an ECG:

ECG is recorded by placing a series of electrodes on the surface of the high-fidelity simulator. These electrodes, called ECG leads, are then connected to the ECG machine. The electrodes are fixed on the limbs of the right arm, left arm, and left leg. Then, the standard 3-limb leads are placed on the right and left upper and lower limbs.

The students recorded a 12-lead ECG on the simulator using simulation-based virtual reality. They switched on the machine, applied gel to recording electrodes, and placed 6 chest leads on the chest in the following positions:

V₁: Over fourth intercostal space near right sternal margin.

V₂: Over fourth intercostal space near left sternal margin.

V₃: Between V₂ and V₄.

V₄: Over the left fifth intercostal space on the mid-clavicular line.

V₅: Over the left fifth intercostal space over the anterior axillary line.

V₆: Over the left fifth intercostal space on the mid-axillary line.

The participant then thanks the simulator and informs him/her that the ECG is normal.

Skill Station 2: Interpretation of normal and abnormal ECG

The Simman 3G Plus was used to demonstrate normal and abnormal ECG.

Normal ECG pattern: Normal sinus rhythm was shown on the Simman 3G Plus monitor, and students were encouraged to interpret the normal ECG correctly.

Abnormal ECG pattern: ST-elevation myocardial infarction was shown on the Simman 3G Plus monitor and students were encouraged to interpret it correctly. At the end of the session, the students completed the post-test questionnaire (Annexure: 1).

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Results

All the participants of the study were aged between 17 and 23 years, of which 204 (81.6%) were between 17and 19 years, 42 (16.8%) were between 19 and 22 years, and 4 (1.6%) were above 22 years (Table 1). Regarding the sex of the participants, 97 (38.8%) belonged to the male sex, and 153 (61.2%) belonged to the female sex (Table 1). The mean and SD for age, pre-assessment score, and post-assessment score were evaluated (Table 2).

The pre- and post-test results were evaluated, which suggest that the intervention had a statistically significant positive impact on participants’ scores, as the p value is < 0.05 (Table 3). In this case, the pre-assessment score has the largest effect size, followed by gender and age (Table 4).

Table 1. Distribution of participants by gender and age.

Table 2. Mean and SD for age and pre- and post-assessment scores.

Table 3. Correlation between pre-test and post-test assessment scores using the paired t-test.

Table 4. Impact of pre-program assessment score, sex, and age on post-program assessment performance using a regression model.

With an increase in age, the post-assessment score decreases by 0.203 points (Table 4). Females are expected to have a post-assessment score that is 0.508 points higher than males (Table 4).

The model appears to have a moderate fit with an R² of 0.133.

The pre-assessment score was a statistically significant predictor of the post-assessment score, as indicated by its p-value of 0.000.

Standardized coefficients (Beta) can be used to assess the relative importance of each predictor. In this case, the pre-assessment score has the largest effect size, followed by sex and age.

Constant: 26.870—This is the intercept of the regression equation. The score represents the predicted post-assessment score when all predictor variables are zero.

Age: –0.203—This coefficient indicates that for each one-unit increase in age, the post-assessment score is expected to decrease by 0.203 points, holding other variables constant.

Gender: 0.508—This coefficient suggests that females are expected to have a post-assessment score 0.508 points higher than males, holding other variables constant.

Pre-assessment score: 0.387—This coefficient indicates that for each one-unit increase in the pre-assessment score, the post-assessment score is expected to increase by 0.387 points, holding other variables constant.

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Discussion

The participants of our study included 250 MBBS students of the first professional year, comprising of aged 17–24 years, of which 97 (38.8%) were male and 153 (61.2%) were female. The students had experiential learning by recording ECG and learning the normal and abnormal ECG patterns on simulators as part of the simulation and virtual learning of the applied physiology of ECG.

It was proven by our study that the intervention of simulation and virtual learning about the applied physiology of ECG and its clinical application had a significant positive impact on participant scores.

Earlier studies have used methods such as online programs (e-learning) to provide training on ECG (Kim 2005). Other studies have used algorithms and dance and movement to provide training regarding ECG rhythms (Atwood 2005; Schultz and Brackbill 2009). Unlike previous studies, in the present study, we employed simulation and virtual learning as the teaching methodology.

In our study, the participants were medical students of one institution; therefore, if students of other institutions and from other health care disciplines were also included, the results obtained would be more informative. Hence, in future studies, we would like to involve more student populations from other institutions and health care disciplines.

Simulation is being used in diverse fields for training purposes and it is being integrated into the medical curriculum, recently as part of medical education also (Roberts 1990; Rochlin et al. 1998; McGaghie et al. 2010). Thus, we find that, of late, clinical skills training is being made mandatory, making use of simulators in clinical skills laboratories and simulation centers and emphasized in the curricula of medical students (Dent 2001; Issenberg et al. 2001). This type of simulation-based training enables an optimal learning experience (Cannon-Bowers 2008).

Thus, the learner can acquire more knowledge, by connecting the new experience with known facts and understanding it well, in order to provide optimal health care in the community.

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Conclusion

Simulation and virtual learning about the applied physiology of ECG and its clinical application have an impact on undergraduate medical students.

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Acknowledgments

None declared.

Conflicts of interest

All authors declare that they have no conflicts of interest.

Financial Disclosure/Statement

None declared.

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References

Atwood, D. 2005. Using an Algorithm to easily interpret basic cardiac rhythms. AORN J. 82(5), 757–766.

Borggreve, A.S., Meijer, J.M., Schreuder, H.W. and Ten Cate, O. 2017. Simulation-based trauma education for medical students: a review of literature. Med. Teach. 39(6), 631–638; doi: 10.1080/0142159X.2017.1303135.

Cannon-Bowers, J.A. 2008. Recent advances in Scenario-based training for medical education. Curr. Opin. Anaethesiol. 21, 784–789.

Dent, J.A. 2001. Current trends and future implications in the developing role of clinical skills centres. Med. Teach. 23, 483–9.

Flangan, B., Nestel, D. and Joseph, M. 2004. Making patient safety the focus: crisis resource management in the undergraduate curriculum. Med. Edu. 38, 56–66.

Issenberg, S.B., Gordon, M.S., Gordon, D.l., Safford, R.E. and Hart, I.R. 2001. Simulation and new learning technologies. Med. Teach. 16, 16–23.

Khan, K., Pattison, T. and Sherwood, M. 2011. Simulation in medical education. Med. Teach. 33(1), 1–3; doi: 10.3109/0142159X.2010.519412.

Kim, Y. 2005. Effects of a web-based teaching method on undergraduate nursing students’ learning of electrocardiography. J. Nurs. Educ. 44(1), 35.

McGaghie, W.C., Issenberg, S.B., Petrusa, E.R. and Scalese, R.S. 2010. A critical review of simulation-based medical education research: 2003-2009. Med. Educ. 44(1), 50–63; doi: 10.1111/j.1365-2923.2009.03547.x.

Morris, M.C. and Conroy, P. 2020. Development of a simulation-based sub-module in undergraduate medical education. Ir. J. Med. Sci. 189(1), 389–394; doi: 10.1007/s11845-019-02050-3.

Paskins, Z. and Peile, E. 2010. Final year medical students’ views on simulation-based teaching: a comparison with the best evidence medical education systematic review. Med. Teach. 32(7), 569–577; doi: 10.3109/01421590903544710.

Riaz, S. 2019. How simulation-based medical education can be started in low resource settings. J. Ayub. Med. Coll. Abbottabad 31(4), 636–637.

Roberts, K.H. 1990. Some characteristics of one type of high reliability organization. Organ. Sci. 1(2), 160–176; doi: 10.1287/orsc.1.2.160.

Robertson, B., Schumacher, L., Gosman, G., Kanfer, R., Kelley, M. and DeVita, M. 2009. Simulation-based crisis team training for multidisciplinary obstetric providers. Simul. Health. 4, 77–83.

Rochlin, G., La Porte, T. and Roberts, K. 1998. The self-designing high-reliability organization: aircraft carrier flight operations at sea. Nav. War. Coll. Rev. 51(3), 97.

Schultz, K. and Brackbill, M. 2009. Teaching electrocardiogram basics using dance and movement. Am. J. Pharm. Educ. 73(4), 70.

Sood, R. and Adkoli, B.V. 2022. Medical education in India—problems and prospects. J. Indian Acad. Clin. Med. 1. 2010–11.

Subramanian, A., Timberlake, M., Mittakanti, H., Lara, M. and Brandt, M.L. 2012. Novel educational approach for medical students: improved retention rates using interactive medical software compared with traditional lecture-based format. J. Surg. Educ. 69(2), 253–256; doi: 10.1016/j.jsurg.2012.05.013.

Ziv, A., Ben-David, S. and Ziv, M. 2005. Simulation based medical education: an opportunity to learn from errors. Med. Teach. 27, 193–9.

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Annexure: 1

Post-test questionnaire

1. The time durations of different ECG waves is plotted horizontally on the XX-axis.

     a) Strongly agree        b) agree        c) neutral       d) disagree

2. On the XX axis, 5 mm=0.20 seconds.

     a) Strongly agree        b) agree        c) neutral       d) disagree

3. Ventricular fibrillation is a dangerous tachyarrhythmia causing cardiac arrest

     a) Strongly agree       b) agree        c) neutral       d) disagree

4. The normal duration of “P-R interval” varies between 0.12 and 0.2 seconds.

     a) Strongly agree        b) agree        c) neutral       d) disagree

5. Standard limb leads are of three types: limb leads I, II, and III.

     a) Strongly agree       b) agree        c) neutral       d) disagree

6. Expansion of ACS to acute cardiac syndrome.

     a) Strongly agree        b) agree        c) neutral       d) disagree

7. In the ECG recording, the chest leads are bipolar.

     a) Strongly agree        b) agree        c) neutral       d) disagree

8. The rhythm in second-degree heart block is regular

     a) Strongly agree        b) agree        c) neutral       d) disagree

9. ST segment elevation on ECG is observed in normal individuals.

     a) Strongly agree       b) agree        c) neutral       d) disagree

10. ECG data can be recorded only at rest and not during exercise.

     a) Strongly agree        b) agree        c) neutral       d) disagree