Abstract Genetic counseling plays an important role in supporting individuals and families in understanding and adapting to the clinical and/or psychological implications of genetic contribution to a condition. With the rapid expansion of genomic testing and the integration of genetic services across specialties, there is a growing demand for genetic counseling; this means that evidence supporting its effectiveness is essential. Demonstrating the efficacy of genetic counseling remains challenging due to methodological variability across studies, including diverse study designs, small sample sizes, various delivery models, and multiple measures of success. A meta‐analysis is a statistical technique that combines results from multiple studies to provide more precise estimates of effect sizes and uncover patterns that may not be evident through individual studies. This article explores the role of meta‐analyses in genetic counseling, highlighting their utility to synthesize evidence from complex interventions, heterogeneous research designs, and disparate outcomes. The article provides introductory methodological guidance for researchers, drawing on established best practices such as PRISMA and the Cochrane Handbook, and provides an overview of each step in conducting a meta‐analysis tailored to genetic counseling. The article includes a review of existing meta‐analyses in genetic counseling, highlights key findings, and provides an overview of methodological particularities. It advocates for the development of core outcome sets (COS) to enhance standardization, as well as greater methodological rigor and transparency in future research. Training in meta‐analytic methods, improved reporting practices, and a genetic counseling specific framework for meta‐analyses and systematic reviews is also discussed. This article supports an increased use of meta‐analyses as a tool for advancing genetic counseling research by generating more synthesized results from individual studies that can help guide clinical practice, training, and policy development.
Ciucă et al. (Fri,) studied this question.