postTests

Posttests are measurements taken after an intervention, event, or time period to assess its outcomes. In research and evaluation, they are used across education, psychology, healthcare, and social sciences to determine whether a program or treatment produced desired changes. When combined with a pretest, they form a pretest–posttest design that allows researchers to quantify change over time.

There are two common forms: posttest-only designs, where a single measurement is taken after the intervention, and pretest-posttest designs, which include baseline data before the intervention. The latter generally provides stronger evidence of change because it accounts for initial differences among participants. Random assignment and control groups further strengthen causal inferences, while threats to validity—such as maturation, history, testing effects, instrumentation, and regression to the mean—must be considered in planning and analysis.

Interpretation of posttest results depends on the timing of the measurement, the construct being assessed, and the reliability and validity of the instrument. Posttests can be influenced by practice effects, social desirability, and ceiling or floor effects if the task is too easy or too hard. In practice, researchers use appropriate controls, multiple measures, or statistical adjustments to isolate the effect of the intervention.

Common applications include evaluating educational interventions after a unit or course, measuring clinical outcomes after treatment, and assessing program impact in policy studies. While informative, posttest data alone do not guarantee causality; robust study designs and analyses are required to support conclusions about effectiveness. See also pretests and pretest–posttest control group designs.