p-value

A p-value is a statistic that estimates how likely a result would be if there were no real effect. It's widely misunderstood and often mistaken for proof.

Definition from Shrinktionary, reviewed by Shariq Refai, MD, MBA, FAPA (last reviewed 2026-06-26). Shrinktionary is the network's language layer and carries the canonical short definition; this page adds the research-context detail below. Full definition on Shrinktionary →

Researchers often use a cutoff of 0.05. If the p-value is below 0.05, they call the result statistically significant. This doesn't mean the result is important or large. It means only that it is unlikely to be a fluke of chance, given the data.

P-values appear in nearly every anxiety trial, and they're widely misread. A p-value doesn't tell you the chance the treatment works. It doesn't tell you how big the effect is. It speaks only to chance.

A trial finds a treatment lowered anxiety scores more than placebo, with a p-value of 0.01. A difference this large would be uncommon if the treatment truly did nothing.

A small p-value with a tiny effect is common in large studies and may not matter to a patient. A large p-value doesn't prove a treatment fails; the study may simply have been too small to detect a real effect. Pair the p-value with the effect size and the confidence interval.