Virtual Reality Effectivity to Increase Self-Efficacy in Suction Skill among Nursing Student: Quasi Experiment Study

Ashamar Puri Apsari; Restuning Widiasih; Ristina Mirwanti

doi:10.24198/jnc.v6i2.44333

Virtual Reality Effectivity to Increase Self-Efficacy in Suction Skill among Nursing Student: Quasi Experiment Study

Ashamar Puri Apsari, Restuning Widiasih, Ristina Mirwanti

Abstract

Virtual reality is a technology-based learning media designed to increase student self-efficacy in performing nursing skills, one of which is suctioning. However, virtual reality has yet to be tested for its effectiveness. This study aims to determine virtual reality learning media's effectiveness in increasing student self-efficacy in performing suction nursing actions. This study used a quasi-experiment method with a one-group pre-test post-test design approach. The population in this study were 191 active students of the Faculty of Nursing, Universitas Padjadjaran. The sampling technique used was purposive sampling and obtained a sample of 68 people by the inclusion and exclusion criteria. The instrument used was a self-efficacy questionnaire developed from Bandura's theory and consisted of 35 statement items. Selected respondents filled out the pre-test and were then given an intervention by performing suction nursing actions using virtual reality after completing the post-test. Data were analyzed using the non-parametric Wilcoxon signed rank test because the data were not normally distributed. After being given the intervention, there was an increase in student self-efficacy in performing suction nursing actions, as evidenced by an increase in the median in the post-test results (113.5) compared to the pre-test results (102). The test results on the Wilcoxon signed rank test showed that the p-value showed a significant difference in self-efficacy after using virtual reality learning media (p = 0.00). Virtual reality learning media can increase student self-efficacy in performing suction nursing actions.

Keywords

Laboratory skills; self-efficacy; suction; virtual reality.

Full Text:

PDF

References

Bockelman, P., & Lingum, D. (2017). Factors of cybersickness. Communications in Computer and Information Science, 714, 3–8. https://doi.org/10.1007/978-3-319-58753-0_1

Cahan, A., Ben-Dov, I. Z., & Bursztyn, M. (2012). Association of heart rate with blood pressure variability: Implications for blood pressure measurement. American Journal of Hypertension, 25(3), 313–318. https://doi.org/10.1038/ajh.2011.230

Chang, E., Kim, H. T., & Yoo, B. (2020). Virtual reality sickness: A review of causes and measurements. International Journal of Human-Computer Interaction, 36(17), 1658–1682. https://doi.org/10.1080/10447318.2020.1778351

Dhabhar, F. S., Malarkey, W. B., Neri, E., & McEwen, B. S. (2012). Stress-induced redistribution of immune cells—From barracks to boulevards to battlefields: A tale of three hormones–Curt Richter Award Winner. Psychoneuroendocrinology, 37(9), 1345-1368.

Gallagher, M., & Ferrè, E. R. (2018). Cybersickness: A multisensory integration perspective. Multisensory Research, 31(7), 645–674. https://doi.org/10.1163/22134808-20181293

Gavgani, A. M., Nesbitt, K. V., Blackmore, K. L., & Nalivaiko, E. (2017). Profiling subjective symptoms and autonomic changes associated with cybersickness. Autonomic Neuroscience: Basic and Clinical, 203, 41–50. https://doi.org/10.1016/j.autneu.2016.12.004

Guna, J., Geršak, G., Humar, I., Krebl, M., Orel, M., Lu, H., & Pogačnik, M. (2020). Virtual reality sickness and challenges behind different technology and content settings. Mobile Networks and Applications, 25(4), 1436–1445. https://doi.org/10.1007/s11036-019-01373-w

Kim, Y. S., Won, J., Jang, S.-W., & Ko, J. (2022). Effects of cybersickness caused by head-mounted display–based virtual reality on physiological responses: Cross-sectional study. JMIR Serious Games, 10(4), e37938. https://doi.org/10.2196/37938

Nesbitt, N. &. (2018). Cybersickness. In Digital Diseases (pp. 15–52). Peter Lang AG. https://doi.org/10.1007/978-3-319-08234-9_252-1

Palmisano, S., Allison, R. S., & Kim, J. (2020). Cybersickness in head-mounted displays is caused by differences in the user’s virtual and physical head pose. Frontiers in Virtual Reality, 1. https://doi.org/10.3389/frvir.2020.587698

Passig, D., Tzuriel, D., & Eshel-Kedmi, G. (2016). Improving children’s cognitive modifiability by dynamic assessment in 3D Immersive Virtual Reality environments. Computers and Education, 95, 296–308. https://doi.org/10.1016/j.compedu.2016.01.009

Rebenitsch, L., & Owen, C. (2021). Estimating cybersickness from virtual reality applications. Virtual Reality, 25(1), 165–174. https://doi.org/10.1007/s10055-020-00446-6

Sevinc, V., & Berkman, M. I. (2020). Psychometric evaluation of Simulator Sickness Questionnaire and its variants as a measure of cybersickness in consumer virtual environments. Applied Ergonomics, 82(September 2019). https://doi.org/10.1016/j.apergo.2019.102958

Trahan, M. H., Smith, K. S., & Talbot, T. B. (2019). Past, present, and future: Editorial on virtual reality applications to human services. Journal of Technology in Human Services, 37(1), 1–12. https://doi.org/10.1080/15228835.2019.1587334

Werrlich, S., Lorber, C., & Nguyen, P. (2018). Virtual, augmented and mixed reality: Interaction, navigation, visualization, embodiment, and simulation. In 10th International Conference, VAMR (pp. 15-20).

Yu, J., Chung, Y., Lee, J. E., Suh, D. H., Wie, J. H., Ko, H. S., Park, I. Y., & Shin, J. C. (2019). The educational effects of a pregnancy simulation in medical/nursing students and professionals. BMC Medical Education, 19(1). https://doi.org/10.1186/s12909-019-1589-8

Zwart, D. P., Goei, S. L., Noroozi, O., & Van Luit, J. E. H. (2021). The effects of computer-based virtual learning environments on nursing students’ mathematical learning in medication processes. Research and Practice in Technology Enhanced Learning, 16(1). https://doi.org/10.1186/s41039-021-00147-x

DOI: https://doi.org/10.24198/jnc.v6i2.44333