Enhancing Disaster Triage Competencies through Simulation-Based Training: An Interventional Study among Undergraduate Nursing Students

Amal Hamdi and Abdulellah Al Thobaity ()
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Amal Hamdi: Abha MaternSity and Children Hospital, Abha 62562, Saudi Arabia
Abdulellah Al Thobaity: Medical Surgical Nursing Department, College of Nursing, Taif University, Taif 21944, Saudi Arabia

Sustainability, 2023, vol. 15, issue 21, 1-13

Abstract: This pre–post interventional study explores the effectiveness of simulation-based training in enhancing disaster nursing skills among nursing students at Taif University, Saudi Arabia. The training, which uses a realistic train accident simulation and involves a response team of healthcare professionals, aims to improve knowledge and performance in crisis management and triage during mass casualty incidents. The study’s necessity stems from the critical role nurses play in disaster response, requiring a comprehensive understanding of challenges, collaboration among stakeholders, and improved capabilities. A random sample of 101 nursing students voluntarily participated in the study, with the necessary approvals obtained. We measured their emergency management skills and knowledge using a detailed questionnaire (27 items) and conducted pretest and posttest evaluations. Data analysis was performed using SPSS. The results indicate the training’s effectiveness, as a significant portion of participants achieved high performance levels in the posttest, contrasting with a higher percentage of fail-level grades in the pretest. These findings underscore the potential to improve disaster management protocols and nursing professionals’ preparedness in Saudi Arabia. The study emphasizes the importance of comprehensive education in disaster nursing in enhancing emergency response and patient outcomes.

Keywords: disaster planning; mass casualty; nursing education research; simulation training; triage (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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