Meta-Analysis: 1 Quick Tip That Helps You Trust the Overall Findings .

Understanding heterogeneity is essential when combining study results in a meta-analysis. Variability across studies—whether from differences in patients, interventions, methods, or outcome measurement—can influence how confidently a single pooled effect can be interpreted. Statistical heterogeneity is assessed by examining how much study estimates and confidence intervals overlap, the Chi² test for inconsistency, and the I² statistic, which reflects the magnitude of variation beyond chance. High heterogeneity signals that results may not belong in one combined estimate, while low heterogeneity supports pooling. Using all three assessments together offers a more reliable picture of how consistent the evidence truly is.