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R. T. Bartee; K. A. Heelan; C. A. Golden; J. L. Hill; G. C. Porter; B. A. Abbey; K. George; N. Foster; P. A. Estabrooks – Prevention Science, 2024
Current childhood obesity treatment programs do not address medically underserved populations or settings where all members of an interdisciplinary team may not exist - either within one organization or within the community. In this paper, we describe the use of a community-academic partnership to iteratively adapt Epstein's Traffic Light Diet…
Descriptors: Obesity, Children, Access to Health Care, Pediatrics
McNeish, Daniel; Peña, Armando; Vander Wyst, Kiley B.; Ayers, Stephanie L.; Olson, Micha L.; Shaibi, Gabriel Q. – Prevention Science, 2023
Growth mixture models (GMMs) are applied to intervention studies with repeated measures to explore heterogeneity in the intervention effect. However, traditional GMMs are known to be difficult to estimate, especially at sample sizes common in single-center interventions. Common strategies to coerce GMMs to converge involve post hoc adjustments to…
Descriptors: Prevention, Intervention, Growth Models, Program Effectiveness
Thomas G. Power; Susan S. Baker; Karen V. Barale; M. Catalina Aragón; Jane D. Lanigan; Louise Parker; Karina Silva Garcia; Garry Auld; Nilda Micheli; Sheryl O. Hughes – Prevention Science, 2024
Researchers are increasingly using web-based technologies to deliver family-based, prevention programming. Few studies have examined the success of such approaches for families with low incomes. The purpose of this study was to describe the level of in-class and online engagement in a childhood obesity prevention program for parents with low…
Descriptors: Obesity, Prevention, Parent Education, Low Income Groups