In a follow‐up study “Network structure influence on simulated network interventions for behaviour change” the team examined how structural network features (e.g., diameter, connectedness, community clustering) influence simulation outcomes and the relative effectiveness of different seeding strategies. The results showed that structural properties can confound expected results: for example, high-degree seeding did not always outperform random selection, depending on the network. Thus, simulation allows us to explore when and why certain network-intervention methods work or fail which is a critical step for translating into real-world applications.