Childhood Obesity Evidence Base Project: A Rationale for Taxonomic versus Conventional Meta-Analysis

There is a great need for analytic techniques that allow for the synthesis of learning across seemingly idiosyncratic interventions. The primary objective of this paper is to introduce taxonomic meta-analysis and explain how it is different from conventional meta-analysis. Conventional meta-analysis has previously been used to examine the effectiveness of childhood obesity prevention interventions. However, these tend to examine narrowly defined sections of obesity prevention initiatives, and as such, do not allow the field to draw conclusions across settings, participants, or subjects. Compared with conventional meta-analysis, taxonomic meta-analysis widens the aperture of what can be examined to synthesize evidence across interventions with diverse topics, goals, research designs, and settings. A component approach is employed to examine interventions at the level of their essential features or activities to identify the concrete aspects of interventions that are used (intervention components), characteristics of the intended populations (target population or intended recipient characteristics), and facets of the environments in which they operate (contextual elements), and the relationship of these components to effect size. In addition, compared with conventional meta-analysis methods, taxonomic meta-analyses can include the results of natural experiments, policy initiatives, program implementation efforts and highly controlled experiments (as examples) regardless of the design of the report being analyzed as long as the intended outcome is the same. It also characterizes the domain of interventions that have been studied. Taxonomic meta-analysis can be a powerful tool for summarizing the evidence that exists and for generating hypotheses that are worthy of more rigorous testing.