Assessing Disaster Nursing Competencies and Resilience in Saudi Arabia’s Post-Pandemic Era: A Cross-Sectional Study to Strengthen Training and Policy Frameworks

Background The COVID-19 pandemic exposed critical vulnerabilities in healthcare systems worldwide, revealing an urgent need for nurses equipped with both advanced disaster competencies and psychological resilience. In Saudi Arabia, where unique challenges including mass gatherings during Hajj and emerging infectious diseases like MERS-CoV persist, the post-pandemic era demands comprehensive reassessment of nursing preparedness. Despite the central role nurses play in emergency response, persistent gaps exist in disaster nursing competencies, with only 60% of Saudi emergency nurses reporting confidence in their disaster response roles. This study aimed to assess disaster nursing competencies and psychological resilience among registered nurses across four geographically and institutionally diverse regions in Saudi Arabia, using validated instruments within a robust theoretical framework. Methods A cross-sectional, quantitative analytical design was employed. A total of 490 registered nurses were recruited from Arar, Riyadh, Hail, and Jizan through a hybrid sampling strategy combining convenience sampling with institutional randomization. Data were collected using a structured demographic questionnaire, the Disaster Nursing Ability Assessment Scale, and the Arabic version of the Connor-Davidson Resilience Scale (CD-RISC). All instruments underwent rigorous cultural adaptation and psychometric validation. Data collection was conducted electronically via Google Survey over 12 weeks with comprehensive quality assurance protocols. Results The final sample exceeded the minimum required for statistical power (N = 490), with geographic distribution across Arar (26.5%), Riyadh (36.3%), Hail (22.0%), and Jizan (15.1%). All instruments demonstrated strong internal consistency (Cronbach's α > 0.85). Participants demonstrated moderate to high psychological resilience (M = 2.97, SD = 0.78), though 3.5–5.1% scored at risk levels (≤ 1.5). Strong correlations emerged between disaster competencies and resilience (r = 0.480, p < 0.001), explaining 23.1% of shared variance. Multiple regression analysis revealed three significant predictors of disaster competency: educational level (β = 0.311, p < 0.001), formal disaster training (β = 0.185, p < 0.001), and urban residence (β = 0.195, p < 0.001), collectively explaining 16.7% of variance. Disaster Reduction/Prevention emerged as the lowest-scoring competency domain, indicating critical gaps in proactive risk assessment capabilities. Conclusions This study provides a methodologically rigorous foundation for evaluating disaster nursing competencies and resilience in Saudi Arabia's post-pandemic context. The findings will inform evidence-based training programs, policy development, and future research initiatives aimed at strengthening disaster preparedness within healthcare systems, ultimately contributing to enhanced patient safety and healthcare workforce resilience during crisis situations.