Meta-analyses in sport and exercise science: sometimes the right tool at the wrong time?

Meta-analysis is widely regarded as a high-level form of evidence in scientific research, particularly in the medical and life sciences. In sport and exercise science, the number of published meta-analyses has increased rapidly in recent years. This expansion raises important questions about when quantitative synthesis is appropriate and when meta-analysis may become the right tool at the wrong time. While meta-analysis offers a powerful tool for synthesizing data from multiple studies, it is crucial to apply appropriate methodology to ensure the validity of results.

The objective of this commentary is to clarify when meta-analysis is an appropriate method and when it risks providing misleading numerical precision, by critically discussing common methodological and interpretive pitfalls in sport and exercise science.

It therefore examines common pitfalls in the execution and interpretation using exemplary meta-analyses published in sport and exercise science, focusing on issues such as clinical and statistical heterogeneity, the selection of appropriate statistical models, and the challenges posed by methodological differences across studies. Clinical heterogeneity, including variations in study populations, interventions, and outcomes, is particularly problematic and requires careful consideration when defining inclusion and exclusion criteria. Furthermore, statistical heterogeneity, which refers to the variability in effect sizes across studies, necessitates the use of random-effects models and sensitivity analyses to account for the diversity of included studies. The choice of statistical methods and the potential impact of outliers can significantly influence meta-analytic conclusions, highlighting the need for rigorous analytical approaches. This commentary also emphasizes that meta-analysis should not always be the default method for synthesizing evidence, particularly when studies are excessively heterogeneous or of low quality. Rather than blindly aggregating data, researchers must critically assess whether a meta-analysis is warranted and if the findings can be meaningfully interpreted.

In conclusion, while meta-analysis is a valuable tool, its results should be carefully framed within the context of the studies included, acknowledging potential limitations and avoiding over-reliance on aggregated data.