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      IMplementation and evaluation of the school-based family support PRogram a Healthy School Start to promote child health and prevent OVErweight and obesity (IMPROVE) – study protocol for a cluster-randomized trial

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          Abstract

          Background

          IMPROVE aims to conduct a hybrid type 3 evaluation design to test the effectiveness of bundled implementation strategies on intervention fidelity of the Healthy School Start (HSS) program, while simultaneously monitoring effects on health outcomes of children and parents. The HSS is a 4-component family support program for children starting school (5–7 years of age) promoting healthy dietary habits and physical activity in the home environment to prevent childhood obesity and parents’ risk of developing type 2 diabetes.

          Methods

          IMPROVE is a cluster-randomized controlled trial with two arms to evaluate and compare the effects of two different bundles of implementation strategies on intervention fidelity expressed as adherence and responsiveness at 12 and 24 months (primary outcomes). Thirty schools in two municipalities will participate in the study reaching about 1400 families per school year. In stakeholder workshops, key implementation determinants were identified according to the domains of the Consolidated Framework for Implementation Research. Through a consensus process with stakeholders, two bundles of implementation strategies were tailored to address context-specific determinants. Schools randomly assigned to group 1 will receive bundle 1 (Basic) and group 2 will receive bundle 1 + 2 (Enhanced). Bundle 2 consists of external facilitation, fidelity monitoring and feedback strategies. Secondary outcomes will include change in acceptability, appropriateness, feasibility, and organisational readiness as perceived by school staff. In addition, child weight status and diet, and parents’ feeding practices and risk of type 2 diabetes will be monitored. Linear and ordinal regression analysis will be used to test the effect on the primary and secondary outcomes, taking clustering and covariates into consideration where needed. Process evaluation will be conducted through key stakeholder interviews to investigate experiences of the program and perceptions on sustainability.

          Discussion

          This systematic approach to investigating the effectiveness of two different bundles of implementation strategies tailored to context-specific determinants on the fidelity of the HSS intervention will provide new insight into feasible implementation strategies and external support needed for the HSS to be effective and sustainable. Results will help inform how to bridge the gap between the research on school-based health programs and routine practice in schools.

          Trial registration

          Registered prospectively at ClinicalTrials.gov ID: NCT04984421, registered July 30, 2021

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12889-021-11663-2.

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          Most cited references61

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          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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            The REDCap consortium: Building an international community of software platform partners

            The Research Electronic Data Capture (REDCap) data management platform was developed in 2004 to address an institutional need at Vanderbilt University, then shared with a limited number of adopting sites beginning in 2006. Given bi-directional benefit in early sharing experiments, we created a broader consortium sharing and support model for any academic, non-profit, or government partner wishing to adopt the software. Our sharing framework and consortium-based support model have evolved over time along with the size of the consortium (currently more than 3200 REDCap partners across 128 countries). While the "REDCap Consortium" model represents only one example of how to build and disseminate a software platform, lessons learned from our approach may assist other research institutions seeking to build and disseminate innovative technologies.
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              The qualitative content analysis process.

              This paper is a description of inductive and deductive content analysis. Content analysis is a method that may be used with either qualitative or quantitative data and in an inductive or deductive way. Qualitative content analysis is commonly used in nursing studies but little has been published on the analysis process and many research books generally only provide a short description of this method. When using content analysis, the aim was to build a model to describe the phenomenon in a conceptual form. Both inductive and deductive analysis processes are represented as three main phases: preparation, organizing and reporting. The preparation phase is similar in both approaches. The concepts are derived from the data in inductive content analysis. Deductive content analysis is used when the structure of analysis is operationalized on the basis of previous knowledge. Inductive content analysis is used in cases where there are no previous studies dealing with the phenomenon or when it is fragmented. A deductive approach is useful if the general aim was to test a previous theory in a different situation or to compare categories at different time periods.
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                Author and article information

                Contributors
                Liselotte.schafer-elinder@ki.se
                Camilla.wiklund@ki.se
                asa.norman@ki.se
                nouha.saleh.stattin@ki.se
                susanne.andermo@ki.se
                emma.patterson@ki.se
                erik.hemmingsson@gih.se
                crcook@umn.edu
                sara.raposo@ki.se
                lydia.kwak@ki.se
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                6 September 2021
                6 September 2021
                2021
                : 21
                : 1630
                Affiliations
                [1 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Department of Global Public Health, , Karolinska Institutet, ; SE-171 77 Stockholm, Sweden
                [2 ]Centre for Epidemiology and Community Medicine, Region Stockholm, SE-104 31 Stockholm, Sweden
                [3 ]GRID grid.465198.7, Department of Clinical Neurosciences, , Karolinska Institutet, ; SE-171 65 Solna, Sweden
                [4 ]Academic Primary Healthcare Centre, Region Stockholm, SE-113 65 Stockholm, Sweden
                [5 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Department of Neurobiology, , Care Sciences and Society, Karolinska Institutet, ; SE-141 83 Huddinge, Sweden
                [6 ]GRID grid.416784.8, ISNI 0000 0001 0694 3737, Department of Physical Activity and Health, , Swedish School of Sport and Health Sciences, ; SE-114 68 Stockholm, Sweden
                [7 ]GRID grid.17635.36, ISNI 0000000419368657, Department of Organizational Leadership and Policy Development, , University of Minnesota, ; Minneapolis, MN 55 USA
                [8 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Institute for Environmental Medicine, , Karolinska Institutet, ; SE-171 77 Stockholm, Sweden
                Author information
                http://orcid.org/0000-0001-7270-1162
                Article
                11663
                10.1186/s12889-021-11663-2
                8419825
                34488691
                65a2e90f-9a2d-4b4a-9d47-e2929b8b7e5c
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

                History
                : 20 August 2021
                : 25 August 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100006636, Forskningsrådet om Hälsa, Arbetsliv och Välfärd;
                Award ID: 2020-01198
                Award Recipient :
                Funded by: Karolinska Institute
                Categories
                Study Protocol
                Custom metadata
                © The Author(s) 2021

                Public health
                bmi,diabetes,diet,fidelity,hybrid type 3 design,health promotion,implementation strategies,physical activity,primary health care

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