The article discusses how to create optimal designs for experiments that study how people make choices. The researchers focused on models that consider both discrete (like yes/no options) and quantitative (like numbers) factors. They found that designs for models assuming independent choices can be misleading, but designs for models allowing for dependent choices are more accurate for studying decision-making.