A multiple-baseline design across settings involves measuring a single participant's behavior across multiple different environments to establish baselines, and then introducing the treatment in each environment at staggered times. If the dependent variable changes in each setting only after the intervention is applied there, it increases the researcher's confidence that the treatment is responsible for the behavioral shift. For example, an intervention like positive attention could be introduced to encourage a child's reading first during school free time, and later during their free time at home, ruling out setting-specific confounding variables.