Next-Generation Meta-analysis for Next-Generation Questions: Introducing the Prevention Science Special Issue on Modern Meta-analytic Methods.

This commentary accompanies the special issue of Prevention Science on modern meta-analytic methods. The papers that comprise this special issue are considered in terms of the next-generation meta-analytic questions they support: questions about multivariate relationships, drawing on real-life data structures, with improved usability, and answered openly. The contributions to this special issue illustrate a range of methods to address these questions, including meta-analytic structural equation modelling; robust variance estimation and network meta-analysis methods; transportability and causal inference; Bayesian methods; and open science. This special issue collectively represents a step forward in the field's ability to address questions of use to improving human welfare through preventing ill health, supporting uptake of these next-generation methods by applied researchers in prevention science. Future methodological developments in meta-analysis should be synergistic with the questions prevention scientists seek to answer, both creating new possibilities and meeting the challenges of improving human health and wellbeing.