Effects of a Preclinical Psychiatric Nursing Preparation Program Using Virtual Simulation on the Learning Flow of Nursing Students
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Abstract
The research article aimed to: 1) compare the levels of learning flow before and after the program between the experimental and control groups, 2) compare learning flow between the experimental and control groups during the post-test and follow-up periods, and 3) examine the effects of a preclinical psychiatric nursing preparation program using virtual simulation on learning flow. The study employed a quasi-experimental design. The population consisted of 120 third-year nursing students at Srinakharinwirot University, Nakhon Nayok, with a sample of 40 students. Research instruments included: (1) a self-developed learning flow measurement tool for nursing students, with a Cronbach’s alpha coefficient of 0.95, and (2) a preclinical psychiatric nursing preparation program using virtual simulation, with an item-objective congruence (IOC) index ranging from 0.60 to 1.00. Data were analyzed using means, standard deviations, and one-way repeated measures MANCOVA.
The results of the study reveal as follows: 1) In the pre-trial period, the experimental group had an overall mean learning flow score of M = 4.14 (S.D. = 0.44). In the post-experimental period, the experimental group’s mean learning flow increased significantly to M = 4.57 (S.D. = 0.47), with statistical significance at the .05 level. In contrast, the control group had a pre-experiment mean of M = 4.16 (S.D. = 0.48), which increased slightly to M = 4.31 (S.D. = 0.50) after the experiment, also reaching statistical significance at the .05 level. 2) The experimental group showed a marked increase in mean learning flow (M = 4.57, S.D. = 0.47), whereas the control group showed only a slight increase (M = 4.31, S.D. = 0.50). During the follow-up period, the experimental group maintained a high level of learning flow (M = 4.68, S.D. = 0.43), while the control group exhibited a slight increase in mean scores (M = 4.40, S.D. = 0.48), with the differences reaching statistical significance at the .05 level. 3) The analysis revealed that the experimental group exhibited continuous improvement in learning flow from the post-experiment period and maintained this level during the follow-up, whereas the control group showed smaller changes. These differences were statistically significant at the .05 level, indicating the effectiveness of the program in enhancing learning flow among the experimental group.
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References
Craig, R. (1987). Training and Development Handbook a Guide to Human Resource. (3rd ed). New York: Mc Gray-Hill Companies.
Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience. Journal of Leisure Research, 24(1), 93-94.
Donovan, L. M., & Mullen, L. K. (2019). Expanding Nursing Simulation Programs with a Standardized Patient Protocol on Therapeutic Communication. Nurse Education in Practice, 38, 126-131.
Ganzer, A. C., & Zauderer, C. (2013). Structured Learning and Self-Reflection: Strategies to Decrease Anxiety in the Psychiatric Mental Health Clinical Nursing Experience. Nursing Education Perspectives, 34(4), 244-247.
Kim, S.-H., & Park, S.-Y. (2024). Factors Influencing on Learning Flow of Nursing Students. Journal of the Korea Academia-Industrial Cooperation Society, 15(3), 1557-1565.
Kolb, D. A. (1984). Experiential Learning: Experience as the Source of Learning and Development. Englewood Cliffs, NJ: Prentice-Hall.
Kolb, D. A. (2005). Experiential Learning: Experience as the Source of Learning and Development. (2nd ed.). Englewood Cliffs, NJ: Prentice-Hall.
Landhäußer, A., & Keller, J. (2012). Flow and Its Affective, Cognitive, and Performance-Related Consequences. In S. Engeser (Ed.), Advances in Flow Research (pp. 65-85). Berlin: Springer New York.
Myers, A., & Hansen, C. (2012). Experimental Psychology. (6th ed.). Wadsworth.
Norkaeo, D. (2015). Simulation-Based Learning for Nursing Education. Journal of Boromarajonani College of Nursing, Bangkok, 31(3), 112-122.
Norsworthy, C. et al. (2023). Psychological Flow Training: Feasibility and Preliminary Efficacy of an Educational Intervention on Flow. International Journal of Applied Positive Psychology, 8, 531-554.
Park, J., & Seo, M. (2022). Influencing Factors on Nursing Students’ Learning Flow During the COVID-19 Pandemic: A Mixed Method Research. Asian Nursing Research, 16(1), 35-44.
Peng, Y. (2019). Research on Head Detection Algorithm for Indoor Scene. (Master’s Thesis). Harbin Institute of Technology. Harbin. China.
Sanongyard, J., Muangchang, Y., & Siratirakul, L. (2022). Effects of Using Simulation-Based Learning of Respiratory System Examination Model on the Ability and Confidence to Perform Children’s Respiratory System Examination of Nursing Students. Journal of Prachomklao College of Nursing, Phetchaburi Province, 5(3), 205-217.
Shernoff, D., Hamari, J., & Rowe, E. (2014). Measuring Flow in Educational Games and Gamified Learning Environments. In J. Viteli & M. Leikomaa (Eds.), Proceedings of EdMedia 2014 - World Conference on Educational Media and Technology (pp. 2276-2281). Tampere, Finland: Association for the Advancement of Computing in Education (AACE). Retrieved March 15, 2024, from https://www.learntechlib.org/primary/p/148041/
