Confounding in studies can mess up results by making it seem like a treatment is causing an effect when it's not. To fix this, researchers use something called propensity scores to balance out variables that might be causing confusion. They can do this by matching, grouping, or adjusting the data. This helps make sure that any relationship found between a treatment and an outcome is actually real.