Heterogeneity

Heterogeneity is the amount that study results differ from each other when they're combined in a meta-analysis. High heterogeneity means the studies disagreed.

This term is specific to research interpretation and is defined on AnxietyResearch. Shrinktionary, the network's language layer, doesn't currently carry a canonical entry for it.

When a meta-analysis pools several trials, the trials rarely give identical results. A little spread is normal. A lot of spread is a problem. Researchers measure it with a statistic often called I-squared, written as a percentage. A high value means the studies are telling different stories, and the single pooled number may hide more than it shows.

Anxiety trials vary in who they enroll, how they deliver treatment, and how they measure outcomes. That variety can produce real heterogeneity. When a meta-analysis of an anxiety treatment reports high heterogeneity, its average effect size deserves more caution.

A meta-analysis of mindfulness for anxiety pools 20 trials. The trials used different programs, different lengths, and different populations. The reported heterogeneity is high, which signals that "mindfulness" isn't one single, consistent thing across the studies.

A pooled number from a high-heterogeneity meta-analysis can mislead. It may average together treatments or populations that shouldn't be averaged. When heterogeneity is high, look for whether the researchers explored why, often by analyzing subgroups.