What is described as a change in one variable resulting from another variable?

The chosen answer refers to a concept commonly understood in research and data analysis known as the "intervention effect." This term is used to describe a situation where a change in one variable is directly attributed to the influence or manipulation of another variable, highlighting a cause-and-effect relationship.

Within the context of evidence-based practice, understanding how an intervention affects an outcome is crucial for validating the effectiveness of that intervention. When assessing an intervention, practitioners often look to quantify how the intervention modifies or influences a specific variable—such as health outcomes, behaviors, or other measurable indicators.

The other options provided represent different concepts that do not specifically relate to the change in variables due to another variable:

• Alternative plausible explanations relate to other factors that could influence the outcome, questioning the direct causation and suggesting that there may be confounding variables affecting the results.

• Baseline data refers to initial measurements taken before an intervention is applied, serving as a point of comparison for later measurements but not directly indicating change due to another variable.

• Trend analysis involves looking at patterns over time and is more about observing changes in data across periods rather than attributing these changes directly to one variable's influence on another.

By focusing on the relationship of intervention to outcomes, the intervention effect accurately encaps