metastudy

A metastudy is a study that synthesizes results from multiple other studies to draw conclusions about a particular research question. The term is sometimes used as a synonym for meta-analysis, but it can also refer more broadly to any study that aggregates findings across existing research, including systematic reviews and umbrella reviews.

The primary purpose of a metastudy is to estimate overall effects, assess consistency across studies, explore sources of heterogeneity, and identify gaps in knowledge. By combining data, metastudies can increase statistical power and help resolve conflicting findings across the literature.

Methodology typically involves several steps: framing a focused question, defining inclusion and exclusion criteria, conducting a comprehensive literature search, selecting eligible studies, and extracting relevant data. Quality assessment or risk of bias evaluation is commonly performed. If a quantitative synthesis is undertaken, meta-analytic models (fixed or random effects) are used to compute pooled effect sizes and confidence intervals. Heterogeneity is assessed with statistics such as I-squared and Q, and sensitivity analyses test the robustness of results. Publication bias may be explored with funnel plots or tests like Egger’s test.

Outcomes of a metastudy include a summarized effect estimate, assessment of consistency among studies, and an appraisal of the certainty or strength of evidence, sometimes using frameworks like GRADE. Limitations arise from the quality and scope of included studies, potential biases, and methodological choices in study selection and synthesis.

Relation to other concepts: a systematic review may be qualitative, while a metastudy with quantitative synthesis resembles a meta-analysis. An umbrella or overview of reviews compiles multiple metastudies to provide a higher-level synthesis. In some contexts, the terms metastudy and meta-analysis are used interchangeably, which can cause confusion.