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Childhood obesity evidence base project: Methods for taxonomy development for application in taxonomic meta-analysis
Journal article   Open access   Peer reviewed

Childhood obesity evidence base project: Methods for taxonomy development for application in taxonomic meta-analysis

Heather King, MacKenzie Magnus, Larry V. Hedges, Chris Cyr, Deborah Young-Hyman, Laura Kettel Khan, Lori A.J. Scott-Sheldon, Jason A. Saul, Sonia Arteaga, John Cawley, …
Childhood obesity, v 16(2), pp S2-7-S2-20
01 Sep 2020
PMID: 32936039
url
https://doi.org/10.1089/chi.2020.0138View
Published, Version of Record (VoR) Open

Abstract

intervention meta-analysis prevention taxonomy
Meta-analysis has been used to examine the effectiveness of childhood obesity prevention efforts, yet traditional conventional meta-analytic methods restrict the kinds of studies included, and either narrowly define mechanisms and agents of change, or examine the effectiveness of whole interventions as opposed to the specific actions that comprise interventions. Taxonomic meta-analytic methods widen the aperture of what can be included in a meta-analysis data set, allowing for inclusion of many types of interventions and study designs. The National Collaborative on Childhood Obesity Research Childhood Obesity Evidence Base (COEB) project focuses on interventions intended to prevent childhood obesity in children 2–5 years old who have an outcome measure of BMI. The COEB created taxonomies, anchored in the Social Ecological Model, which catalog specific outcomes, intervention components, intended recipients, and contexts of policies, initiatives, and interventions conducted at the individual, interpersonal, organizational, community, and societal level. Taxonomies were created by discovery from the literature itself using grounded theory. This article describes the process used for a novel taxonomic meta-analysis of childhood obesity prevention studies between the years 2010 and 2019. This method can be applied to other areas of research, including obesity prevention in additional populations.

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Collaboration types
Domestic collaboration
Web of Science research areas
Pediatrics
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