What is the significance of clinical significance vs statistical significance?

• A. Statistical significance indicates unlikely to be due to chance; clinical significance refers to practical or meaningful change in functioning
• B. Clinical significance indicates sample size
• C. Statistical significance means the effect is large
• D. Clinical significance means the result generalizes to populations

Answer: (A)

The main idea is to separate whether a result is reliable from a mathematical standpoint from whether it truly matters in real life for patients. Statistical significance tells us the probability that the observed change happened by chance under the null hypothesis. It shows reliability of the finding, but it doesn’t tell us whether that change is large enough to be noticeable or valuable in everyday functioning.

Clinical significance focuses on practical impact: does the observed change meaningfully improve functioning, quality of life, or daily activities? This is about the magnitude of the effect and whether it crosses a threshold that clinicians and patients consider worthwhile, often discussed in terms of effect sizes or minimal clinically important differences. A result can be statistically significant yet have a very small, trivial real-world effect; conversely, a sizable and meaningful change might not reach statistical significance in a small study. That’s why both aspects matter when interpreting results.

Clinical significance isn’t about sample size, and statistical significance isn’t a guarantee of a large effect. Also, clinical significance is about practical impact, not generalizability to other populations—that latter idea relates to external validity.