What term describes the variation among results from different studies in a meta-analysis, which is often shown with a forest plot and quantified by I^2?

• A. Homogeneity; Forest plot; Q
• B. Variability; Scatter plot; p-value
• C. Heterogeneity; Forest plot; I^2
• D. Consistency; Bar chart; p-value

Answer: (C)

Variation among results from different studies in a meta-analysis is called heterogeneity. This variability is often read from a forest plot, which shows each study’s effect estimate and confidence interval, plus the overall pooled effect. I^2 specifically measures how much of the observed differences are due to real differences between studies rather than random sampling error, expressed as a percentage. A low I^2 means studies are fairly consistent with one another; a high I^2 signals substantial heterogeneity, suggesting that factors like study design, populations, or interventions might be influencing the results. The other terms and visuals in the distractors don’t capture this concept: homogeneity would mean little to no variation, a scatter plot isn’t the standard visualization for this purpose, and bar charts or p-values aren’t the typical summary of cross-study variability.