Predictors of Non-Compliance with a National Early Care and Education-Based Obesity Prevention Initiative: Go NAPSACC.

PURPOSE: The purpose is to examine predictors of intervention non-compliance and develop a risk stratification score. DESIGN: Prospective cohort. SETTING: Early care and education (ECE). SUBJECTS: Early care and education programs (n = 3883) randomly allocated (3:1) to a development (n = 2909) or validation (n = 974) sample. INTERVENTION: Go NAPSACC provides a structured, web-based process to help improve the health of children around 7 modules (nutrition, physical activity, oral health, breast/infant feeding, farm to ECE, outdoor play, and screen time). MEASURES: Program characteristics and participation data are collected via Go NAPSACC tool. ANALYSIS: Multivariable Lasso logistic regression was used to identify predictors. Discriminative ability was based on area under the ROC curve (AUC). RESULTS: Overall, ECE program non-compliance (lack of valid pre-/post self-assessment) was 65.5%. Six predictors were retained in the final development model: type of program (P = .002), Child and Adult Care Food Program (CACFP) participation (P = .065), acceptance of subsidies (P < .001), past modules attempted (P < .001), past modules completed (P < .001), and action plans created (P < .001). These factors generated a non-compliance risk score which showed good discrimination in the validation sample (AUC: .922, 95% CI: .903-.940). CONCLUSION: Lack of qualitative data limits the ability to fully understand the context of non-compliance; however, this study demonstrates readily available data captured by Go NAPSACC are strong predictors of future success. Early identification of high-risk programs will inform targets for future implementation strategies geared toward improving program success.