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

Abstract

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.