The causal mediation literature has mainly focused on “natural effects” as measures of mediation, but these have been criticized for their reliance on empirically unverifiable assumptions. They are also impossible to estimate without additional untestable assumptions in the common situation of exposure-induced mediator–outcome confounding. “Interventional effects” have been proposed as alternative measures that overcome these limitations, and 2 versions have been described for the exposure-induced confounding problem. We aim to provide insight into the interpretation of these effects, particularly by describing randomized controlled trials that could hypothetically be conducted to estimate them. In contrast with natural effects, which are defined in terms of individual-level interventions, the definitions of interventional effects rely on population-level interventions. This distinction underpins the previously described advantages of interventional effects, and reflects a shift from individual effects to more tangible population-average effects. We discuss the conceptual and practical implications for the conduct of mediation analysis. See video abstract at, http://links.lww.com/EDE/B383.