Assessment of the Core Competencies for Disaster Management Among Nurses Dealing With Casualties: A Study From Yemen

Background Yemen has faced numerous war-related disasters in recent years, yet limited research exists on the disaster core competencies and preparedness of Yemeni nurses. This study evaluated the disaster core competencies and preparedness levels of Yemeni nurses managing disasters. Methods A cross-sectional descriptive study. Data were collected from 126 nurses using a demographic questionnaire and the Nurses' Perceptions of Disaster Core Competencies (NPDCC) scale. Inferential statistics, including independent t-tests and one-way ANOVA, assessed relationships between demographic characteristics and competency levels. Data normality was verified using the Kolmogorov-Smirnov test. Results The mean competency score was moderate (3.43 ± 0.18). General diagnostic skills scored the highest (4.01 ± 0.12), while special diagnostic skills scored the lowest (2.98 ± 0.44). Nurses with master's degrees (t = 4.3, p = 0.010), those with work experience in previous incidents and disasters (t = 2.9, p = 0.032), those attending disaster training course/drill (t = 3.7, p = 0.005), and those with workplaces prepared with an established disaster plan (t = 4.6, p = 0.002) had significantly higher scores for competencies. Conclusions In the current study, Yemeni nurses demonstrated moderate competencies in disaster risk management, with gaps in specialized diagnostic skills. Nurses with master's degrees, those with work experience in previous incidents and disasters, those attending the disaster risk management training course/drill, those with more extended professional experience, and those with workplaces prepared with an established disaster plan had significantly higher scores in disaster risk management. Enhancing disaster preparedness should focus on targeted training, institutional planning, and resource allocation. These initiatives will strengthen the resilience of the nursing workforce in Yemen and similar conflict-affected regions.