Artificial cognitive systems sometimes neglect the impact on action selection of natural durative-state mechanisms like emotions and drives. These chemically-regulated motivation systems assist natural action selection through temporarily focusing an agent's behavioural attention on particular problems. This can improve efficiency by avoiding dithering, but taken to extremes can be inefficient in ways that seem cognitively improbable for mammal-level intelligence. This article demonstrates a flexible latching method that provides appraisal-based sensitivity to interruption, allowing reassessment of the current focus of attention. This drastically improves efficiency in handling multiple competing goals at the cost of a surprisingly small amount of extra cognitive complexity.