What characterizes a repeated measures design?

A repeated measures design is characterized by the use of the same participants across multiple experimental conditions. This means that each participant takes part in every treatment or condition being tested, allowing researchers to observe how changes in the independent variable affect the same individual over time. This design has the advantage of reducing the variability that comes from differences between participants, which can lead to more sensitive measurements of effects and interactions.

In particular, by using the same individuals, the study can account for individual differences. This minimizes the impact of confounding variables that might arise from utilizing different groups, as the same subjects serve as their own control. If the goal is to assess how a manipulation affects scores or behaviors, measuring the same group under various conditions is especially useful.

Regarding the other options, they refer to different methodologies. Testing different groups under separate conditions pertains to independent measures designs, where comparison is made across distinct groups rather than the same individuals. Mentioning that only one group participates does not reflect the essence of a repeated measures design, as the focus should be on repeated assessments of the same subjects across conditions. Lastly, indicating that each participant measures a single variable overlooks the possibility in a repeated measures context where participants may contribute data across multiple dependent variables in different conditions.