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      Participatory development and pilot testing of iChoose : an adaptation of an evidence-based paediatric weight management program for community implementation

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          Abstract

          Background

          To describe the identification, adaptation, and testing of an evidence-based pediatric weight management program for a health disparate community.

          Methods

          A community advisory board (CAB) of decision-makers and staff from local health care, public health, and recreation organizations engaged with academic partners to select an evidence-based program (EBP) for local implementation. Three EBPs were identified (Traffic Light, Bright Bodies, Golan and colleagues Home Environmental Model) and each EBP was rated on program characteristics, implementation and adaptation, and adoptability. Following selection of the EBP that was rated highest, the POPS-CAB made adaptations based on the program principles described in peer-reviewed publications. The adapted intervention, iChoose, was then pilot tested in 3 iterative phases delivered initially by research partners, then co-delivered by research and community partners, then delivered by community partners. The RE-AIM framework was used to plan and evaluate the iChoose intervention across all waves with assessments at baseline, post program (3 months), and follow-up (6 months).

          Results

          Bright Bodies rated highest on program characteristics and adoptability (p’s < 0.05), while Home Environmental Model rated highest on implementation factors ( p < 0.05). Qualitatively, the selection focused on important program characteristics and on matching those characteristics to the potential to fit within the community partner services. The adapted program— iChoose—had 18% reach and with participants that were representative of the target population on age, gender, ethnicity, and race. Effectiveness was demonstrated by modest, but significant reductions in BMI z-scores at post-program compared to baseline (M Δ = − 0.047; t = − 2.11, p = 0.046). This decrease returned to values similar to baseline 3 months (M Δ = 0.009) after the program was completed. Implementation fidelity was high and implementation fidelity did not differ between community or research delivery agents.

          Conclusion

          The process to help organizations identify and select evidence-based programs appropriate for their community led to consensus on a single EBP. While iChoose was successful in initiating changes in BMI z-scores, could be implemented in a low resource community with fidelity, it was insufficient to lead to sustained child BMI z-scores. In response to these data, maintenance of program effects and delivery are the current focus of the CBPR team.

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          Most cited references49

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          Evaluating the impact of health promotion programs: using the RE-AIM framework to form summary measures for decision making involving complex issues.

          Current public health and medical evidence rely heavily on efficacy information to make decisions regarding intervention impact. This evidence base could be enhanced by research studies that evaluate and report multiple indicators of internal and external validity such as Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) as well as their combined impact. However, indices that summarize the combined impact of, and complex interactions among, intervention outcome dimensions are not currently available. We propose and discuss a series of composite metrics that combine two or more RE-AIM dimensions, and can be used to estimate overall intervention impact. Although speculative and, at this point, there have been limited empirical data on these metrics, they extend current methods and are offered to yield more integrated composite outcomes relevant to public health. Such approaches offer potential to help identify interventions most likely to meaningfully impact population health.
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            Identifying and selecting the common elements of evidence based interventions: a distillation and matching model.

            A model is proposed whereby the intervention literature can be empirically factored or distilled to derive profiles from evidence-based approaches. The profiles can then be matched to individual clients based on consideration of their target problems, as well as demographic and contextual factors. Application of the model is illustrated by an analysis of the youth treatment literature. Benefits of the model include its potential to facilitate improved understanding of similarities and differences among treatments, to guide treatment selection and matching to clients, to address gaps in the literature, and to point to possibilities for new interventions based on the current research base.
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              Obesity prevention: a proposed framework for translating evidence into action.

              Obesity as a major public health and economic problem has risen to the top of policy and programme agendas in many countries, with prevention of childhood obesity providing a particularly compelling mandate for action. There is widespread agreement that action is needed urgently, that it should be comprehensive and sustained, and that it should be evidence-based. While policy and programme funding decisions are inevitably subject to a variety of historical, social, and political influences, a framework for defining their evidence base is needed. This paper describes the development of an evidence-based, decision-making framework that is particularly relevant to obesity prevention. Building upon existing work within the fields of public health and health promotion, the Prevention Group of the International Obesity Task Force (IOTF) developed a set of key issues and evidence requirements for obesity prevention. These were presented and discussed at an IOTF workshop in April 2004 and were then further developed into a practical framework. The framework is defined by five key policy and programme issues that form the basis of the framework. These are: (i) building a case for action on obesity; (ii) identifying contributing factors and points of intervention; (iii) defining the opportunities for action; (iv)evaluating potential interventions; and (v) selecting a portfolio of specific policies, programmes, and actions. Each issue has a different set of evidence requirements and analytical outputs to support policy and programme decision-making. Issue 4 was identified as currently the most problematic because of the relative lack of efficacy and effectiveness studies. Compared with clinical decision-making where the evidence base is dominated by randomized controlled trials with high internal validity, the evidence base for obesity prevention needs many different types of evidence and often needs the informed opinions of stakeholders to ensure external validity and contextual relevance.
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                Author and article information

                Contributors
                402-552-3397 , jennie.hill@unmc.edu
                601-466-6759 , Jz9q@virginia.edu
                540-231-4083 , wenyou@vt.edu
                540-309-7830 , djbrock@virginia.edu
                434-489-9108 , Bep4s@virginia.edu
                336-285-3632 , rcalexander@ncat.edu
                540-231-9994 , frisardm@vt.edu
                402-559-6627 , fabiana.silva@unmc.edu
                540-521-6726 , xiaolu6@gmail.com
                402-559-4325 , Paul.estabrooks@unmc.edu
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                29 January 2019
                29 January 2019
                2019
                : 19
                : 122
                Affiliations
                [1 ]ISNI 0000 0001 0666 4105, GRID grid.266813.8, Department of Epidemiology, College of Public Health, , University of Nebraska Medical Center, ; Omaha, USA
                [2 ]ISNI 0000 0000 9136 933X, GRID grid.27755.32, Department of Public Health Sciences, , School of Medicine, ; P.O. Box 800717, Charlottesville, VA 22908-0717 USA
                [3 ]ISNI 0000 0001 0694 4940, GRID grid.438526.e, Department of Agricultural and Applied Economics, , Virginia Tech, ; Blacksburg, VA 24061 USA
                [4 ]ISNI 0000 0000 9136 933X, GRID grid.27755.32, Education and Outreach Specialist, , University of Virginia and Cancer Center, ; P.O. Box 800717, Charlottesville, VA 22908-0717 USA
                [5 ]ISNI 0000 0001 0287 4439, GRID grid.261037.1, Department of Family and Consumer Sciences, , North Carolina Agricultural and Technical State University, ; Benbow 202-A, Greensboro, NC 27405 USA
                [6 ]ISNI 0000 0001 0694 4940, GRID grid.438526.e, Department of Human Nutrition, Foods and Exercise, , Virginia Tech, ; 1981 Kraft Drive (0913), ILSB 23, Rm 1085, Blacksburg, VA 24061 USA
                [7 ]ISNI 0000 0001 0666 4105, GRID grid.266813.8, College of Public Health, , University of Nebraska Medical Center, ; 984365 Nebraska Medical Center, Omaha, NE 68198-4365 USA
                [8 ]ISNI 0000 0001 0694 4940, GRID grid.438526.e, Virginia Tech University, ; Blacksburg, USA
                [9 ]ISNI 0000 0001 0666 4105, GRID grid.266813.8, Department of Health Promotion, College of Public Health, , University of Nebraska Medical Center, ; 986075 Nebraska Medical Center, Omaha, NE 68198-6075 USA
                Author information
                http://orcid.org/0000-0002-0510-383X
                Article
                6450
                10.1186/s12889-019-6450-9
                6352451
                30696420
                d3083db5-911a-46ad-a744-61e96511572e
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 19 July 2018
                : 17 January 2019
                Funding
                Funded by: National Institutes of Health, National Institute on Minority Health and Health Disparities
                Award ID: R24MD008005
                Award Recipient :
                Funded by: Fralin Translational Obesity Research Center Virginia Tech
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                Public health
                childhood obesity,evidence-based programs,community-based participatory research,program adoption

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