How Can We Make Sure that Disaster Management Training Fits Their Purpose?

Summary: The Sendai Framework for Disaster Risk Reduction 2015-2030 emphasizes education and training as essential elements for disaster risk reduction. However, recent studies have highlighted significant variability in disaster management (DM) training curricula, methodologies, and evaluation practices. A recognized issue within DM capacity-building programs is the lack of scientifically sound monitoring and evaluation (M&E). The M&E process serves two main functions: an internal function focused on quality assessment and continuous improvement of the course, and an external function related to outcome reporting and performance evaluation. Given the relatively low frequency of disasters, most responders experience real events infrequently, making effective training and M&E crucial to ensure they are prepared to perform optimally when disasters occur. DM training programs encompass a broad range of topics, from clinical medicine to management, and employ various instructional methods, including e-learning, traditional lectures, and simulations. This complexity complicates the M&E process. Additionally, evaluating DM training outcomes during actual disasters is nearly impossible due to the numerous factors that influence response effectiveness. Most educational programs in general medical education and DM training struggle to demonstrate a clear connection between training activities and desired outcomes. Organizers often only report on the number of individuals trained, participant satisfaction, and knowledge gains. This M&E approach is suboptimal because it analyses only limited aspects of the educational process and overlooks the complex, dynamic processes within the programs. Consequently, a high-quality, validated M&E process, deliberately designed to address the complexity of DM training, should incorporate a variety of evaluation methods, including formative assessments and summative assessments, incorporating both qualitative and quantitative data. A comprehensive M&E framework has the potential to improve the course itself, improve its learning outcomes, and ensure all stakeholders of a trustworthy educational process.