Cascade training remains widely used in global health. Cascade training can look great on paper: an expert trains a small group who, in turn, train others, thereby theoretically scaling the knowledge across an organization. It attempts to combine the advantages of expert coaching and peer learning by passing knowledge down a hierarchy. However, despite its promise and persistent use, cascade training is plagued by several factors that often lead to its failure. This is well-documented in the field of learning, but largely unknown (or ignored) in global health. What are the mechanics of this known inefficacy? Here are four factors that contribute to the failure of cascade training 1. Information loss Consider a model where an expert holds a knowledge set K. In each subsequent layer of the cascade, α percentage of the knowledge is lost: 2. Lack of feedback In a cascade model, only the first layer receives feedback …
