An Empirical Study on the Combined Application of the DEDICT Teaching Model and Scenario Simulation Among Operating Room Nursing Interns
Abstract
Objective: Discuss the effect of the DEDICT teaching mode combined with scenario simulation among operating room nursing interns. Methods: We selected 110 nursing interns in our hospital's operating room between October 2024 and September 2025. We randomly assigned them to a control group or an experimental group using a random number table. The control group received conventional teaching, while the experimental group underwent DEDICT teaching combined with scenario simulation. We compared the Theoretical and Practical Performance Scores, the Nursing Staff's Self-Directed Learning Ability Scores, the Nursing Competency Scores, and the Teaching Effectiveness Satisfaction Evaluation between the groups. Results: The Theoretical and Practical Performance Scores in the experimental group were 92.16 ± 7.22 and 94.36 ± 3.15, significantly higher than those of the control group at 83.24 ± 6.35 and 82.17 ± 4.54. The experimental group demonstrated higher Nursing Staff's Self-Directed Learning Ability Scores (147.19 ± 12.34 vs. 137.65 ± 11.55) and Nursing Competency Scores (192.54 ± 32.37 vs. 170.83 ± 39.64) than the control group, with all differences being statistically significant (P < 0.05). The Teaching Effectiveness Satisfaction Rate in the experimental group was 98.18%, exceeding that of the control group (89.09%). The rank-sum test yielded Z = -2.475, P =0.014. Conclusions: The application of the DEDICT teaching model combined with scenario simulation enhances nursing interns' theoretical and practical performance, improves their autonomous learning capabilities, elevates their job competency, and facilitates their adaptation to clinical nursing work more effectively and expeditiously. This approach is of significant importance to nursing education and warrants further implementation.
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PDFDOI: https://doi.org/10.5296/jbls.v17i2.23540
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Copyright (c) 2026 Peijun Xiang, Ping Lai, Zhuqing Chen, Zhaohua Zou

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