Open-science meta-analysis Cochrane module for JASP

František Bartoš, from the Department of Psychology, the University of Amsterdam and Wim Otte, Department of Pediatric Neurology, UMC Utrecht Brain Center developed a Cochrane meta-analysis module: open-science software targeting applied clinical research. The module was funded by the Dutch Research Agenda (Idea Generator grant) and Utrecht University and released in the 0.16.1 version of JASP and contains all meta-analysis tables published in >8,000 high-quality systematic reviews covering the entire field of clinical medicine (up to February 2022).

More than 550,000 standardized clinical trial outcomes are retrievable based on keyword matching, topic selection, or title search in a user-friendly graphical interface. The module has been designed with everyday clinical users in mind and will be regularly updated. Users may also enter custom data into existing meta-analysis tables if needed.

Screen shot of the software

Results from individual studies converted into overall findings

The open software addresses a significant challenge in day-to-day clinical practice: Using new information from multiple independent small studies to reach a sound conclusion. In an ideal world, the state of a particular disease, treatment, or outcome could be instantaneously assessed and placed into perspective. However, it has turned out, again and again, that solid decisions based on more than one study are almost always more nuanced and less extreme. Therefore, high-quality overview papers containing so-called meta-analyses provide the only means to draw reliable conclusions from clinical trials. In these meta-analyses, results from individual studies are aggregated and converted into overall findings. The software also targets users in need of a rapid overview of a representative sample of clinical outcomes in the field of evidence-based medicine. 

The module helps to place the individual data into proper perspective while determining the most likely evidence with a Bayesian model‐averaged (BMA) meta‐analysis for continuous and dichotomous clinical outcome data. This model averaging removes the difficult decision in taking between-study heterogeneity into account. However, the classical fixed-effect and random-effects models are also available. Therefore, the module offers a complete set of open-science meta-analysis tools.