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  • Title: The Shaping Healthy Choices Program: design and implementation methodologies for a multicomponent, school-based nutrition education intervention.
    Author: Scherr RE, Linnell JD, Smith MH, Briggs M, Bergman J, Brian KM, Dharmar M, Feenstra G, Hillhouse C, Keen CL, Nguyen LM, Nicholson Y, Ontai L, Schaefer SE, Spezzano T, Steinberg FM, Sutter C, Wright JE, Young HM, Zidenberg-Cherr S.
    Journal: J Nutr Educ Behav; 2014; 46(6):e13-21. PubMed ID: 25457732.
    Abstract:
    OBJECTIVE: To provide a framework for implementation of multicomponent, school-based nutrition interventions. This article describes the research methods for the Shaping Healthy Choices Program, a model to improve nutrition and health-related knowledge and behaviors among school-aged children. DESIGN: Longitudinal, pretest/posttest, randomized, controlled intervention. SETTING: Four elementary schools in California. PARTICIPANTS: Fourth-grade students at intervention (n = 252) and control (n = 238) schools and their parents and teachers. Power analyses demonstrate that a minimum of 159 students per group will be needed to achieve sufficient power. The sample size was determined using the variables of nutrition knowledge, vegetable preference score, and body mass index percentile. INTERVENTION: A multicomponent school-based nutrition education intervention over 1 academic year, followed by activities to support sustainability of the program. MAIN OUTCOME MEASURES: Dietary and nutrition knowledge and behavior, critical thinking skills, healthy food preferences and consumption, and physical activity will be measured using a nutrition knowledge questionnaire, a food frequency questionnaire, a vegetable preferences assessment tool, the Test of Basic Science Process Skills, digital photography of plate waste, PolarActive accelerometers, anthropometrics, a parent questionnaire, and the School and Community Actions for Nutrition survey. ANALYSIS: Evaluation will include quantitative and qualitative measures. Quantitative data will use paired t, chi-square, and Mann-Whitney U tests and regression modeling using P = .05 to determine statistical significance.
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