How should effect sizes be interpreted in behavior-change research, and what constitutes a meaningful effect?

• A. They indicate statistical significance alone.
• B. They only matter for large samples.
• C. They have no practical meaning.
• D. They indicate practical impact; meaningful thresholds depend on context, baseline risk, and public health significance, not just statistical significance.

Answer: (D)

Effect sizes in behavior-change research quantify how large the change or difference is, so you can judge the real-world impact of an intervention. Statistical significance, by contrast, only tells you whether an observed effect is unlikely to be due to chance given the data and sample size; it says nothing about how big or important the change is. A meaningful effect depends on context: the baseline level of risk or behavior, how common the outcome is, and whether the magnitude of change would meaningfully influence decisions, outcomes, or public health impact. Sometimes a small effect can be very important if it applies to a large population or leads to a substantial health benefit; other times a large effect on a rare outcome may be less impactful overall. So, effect sizes indicate practical impact, and what counts as meaningful is determined by context, baseline risk, and public health significance, not by statistical significance alone.