|Titre :||Predictors of Non-Compliance with a National Early Care and Education-Based Obesity Prevention Initiative : Go NAPSACC (2022)|
|Auteurs :||Erik A. Willis, Membre de l'équipe de recherche ; Xiuya Chang, Membre de l'équipe de recherche ; Falon Smith, Membre de l'équipe de recherche ; Emily Clarke, Membre de l'équipe de recherche|
|Type de document :||Article : texte imprimé|
|Dans :||American Journal of Health Promotion (Vol. 36, n°5, June 2022)|
|Article en page(s) :||pp. 864-868|
The purpose is to examine predictors of intervention non-compliance and develop a risk stratification score.
Early care and education (ECE).
Early care and education programs (n = 3883) randomly allocated (3:1) to a development (n = 2909) or validation (n = 974) sample.
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).
Program characteristics and participation data are collected via Go NAPSACC tool.
Multivariable Lasso logistic regression was used to identify predictors. Discriminative ability was based on area under the ROC curve (AUC).
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
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."
|En ligne :||https://journals.sagepub.com/doi/full/10.1177/08901171211069550|
|RESO A.19||RE65682376||Bulletin||RESOdoc||Consultation sur place|