A statistically significant finding is one that is unlikely to be the result of chance alone, given the sample size and the statistical test used. A clinically significant finding is one that meaningfully changes patient outcomes or decisions.
Why the two can diverge
Large studies can find statistically significant effects that are clinically trivial. Small studies can find effects that look promising but lack precision.
Key concepts
Effect size, confidence interval, number needed to treat, and minimal clinically important difference are the core concepts that bridge statistical and clinical significance.
Anxiety trial example
A 2-point drop on a 21-point anxiety scale can be statistically significant in a large trial but may not represent a meaningful clinical change for an individual patient.
Why this matters for reading research on anxiety
A trial can be technically positive and clinically modest. Looking at effect sizes rather than only p-values keeps this distinction visible.
Sources
Related reading
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