Which scenario makes meta-analysis particularly appropriate?

• A. Few studies or highly variable results
• B. Many studies with identical results
• C. For narrative synthesis only
• D. When data unavailable

Answer: (A)

Meta-analysis pools numerical results from multiple studies to produce a single, more precise estimate of effect and to assess consistency across studies. It’s particularly useful when you have several independent studies addressing the same question and want to know whether their findings converge and how precise the overall estimate is.

When there are only a few studies, pooling them formally increases precision compared with any one study alone, helping to clarify the overall signal. When results are highly variable across studies, a meta-analysis (often with a random-effects approach) accounts for that between-study heterogeneity and provides an average effect that reflects those differences, while also allowing exploration of why results differ.

If there are many studies with identical results, the value of pooling is limited because the conclusion is already consistent, though meta-analysis would still yield the same estimate with potentially narrower confidence intervals. If data aren’t available, you can’t perform a meta-analysis, and narrative synthesis would be the fallback.