Adverse childhood experiences (ACEs) have long-term health consequences. Young children in the southern part of the United States (US) are at greater risk than children in other parts of the US. This study assessed preschool children ACEs using a family-friendly tool, the Family Map (FMI), and compared children living in rural/urban areas while examining the potential moderation of race. The FMI–ACE score was examined as a total and two sub-scores. We found that race did not moderate the FMI–ACE score but that Black children (Cohen’s d = 0.52) and children in urban and large rural areas were at highest risk (Cohen’s d = 0.38). However, the subscale FMI–ACEs parenting risk was moderated by race such as that Black children were less at risk in rural areas than urban (Cohen’s d = 0.62). For FMI–ACEs environmental risk, race moderated risk such that Black children were most at risk in large rural areas but less so in small rural areas (Cohen’s d = 0.21). Hispanic children were most at risk in small rural areas and least in large rural environments. Findings from this study suggest that targeting the most at-risk children for interventions should consider the context including race and location.

Researchers face many decisions in developing a measurement tool and protocol for monitoring fidelity to complex interventions. The current study uses data evaluating a nutrition education intervention, Together, We Inspire Smart Eating (WISE), in a preschool setting to explore issues of source, timing, and frequency of fidelity monitoring. The overall study from which these data are drawn was a pre/post design with an implementation-focused process evaluation. Between 2013 and 2016, researchers monitored fidelity to evidence-based components of the WISE intervention in 49 classrooms in two Southern states. Data collectors obtained direct assessment of fidelity on a monthly basis in study classrooms. Research staff requested that educators provide indirect assessment on a weekly basis. We used mean comparisons (t-tests), correlations (Pearson’s r), and scatterplots to compare the direct and indirect assessments. No mean comparisons were statistically different. Correlations of direct and indirect assessments of the same component for the same month ranged between − 0.51 (p = 0.01) and 0.54 (p = 0.001). Scatterplots illustrate that negative correlations can be driven by individuals who are over reporting (i.e., self-report bias) and that near zero correlations approximate the ideal situation (i.e., both raters identify high fidelity). Our findings illustrate that, on average, observed and self-reports may seem consistent despite weak correlations and individual cases of extreme over reporting by those implementing the intervention. The nature of the component to which fidelity is being monitored as well as the timing within the context of the intervention are important factors to consider when selecting the type of assessment and frequency of fidelity monitoring. NCT03075085 Registered 20 February 2017. Trial registration corresponds to the funding that supported the writing of this manuscript, not the data collection. The original study was not a trial and was collected without registration. However, the data reported here provided foundational preliminary data for the trial.

Despite the potential to reach at-risk children in childcare, there is a significant gap between current practices and evidence-based obesity prevention in this setting. There are few investigations of the impact of implementation strategies on the uptake of evidence-based practices (EBPs) for obesity prevention and nutrition promotion. This study protocol describes a three-phase approach to developing and testing implementation strategies to support uptake of EBPs for obesity prevention practices in childcare (i.e., key components of the WISE intervention). Informed by the i-PARIHS framework, we will use a stakeholder-driven evidence-based quality improvement (EBQI) process to apply information gathered in qualitative interviews on barriers and facilitators to practice to inform the design of implementation strategies. Then, a Hybrid Type III cluster randomized trial will compare a basic implementation strategy (i.e., intervention as usual) with an enhanced implementation strategy informed by stakeholders. All Head Start centers (N = 12) within one agency in an urban area in a southern state in the USA will be randomized to receive the basic or enhanced implementation with approximately 20 classrooms per group (40 educators, 400 children per group). The educators involved in the study, the data collectors, and the biostastician will be blinded to the study condition. The basic and enhanced implementation strategies will be compared on outcomes specified by the RE-AIM model (e.g., Reach to families, Effectiveness of impact on child diet and health indicators, Adoption commitment of agency, Implementation fidelity and acceptability, and Maintenance after 6 months). Principles of formative evaluation will be used throughout the hybrid trial. This study will test a stakeholder-driven approach to improve implementation, fidelity, and maintenance of EBPs for obesity prevention in childcare. Further, this study provides an example of a systematic process to develop and test a tailored, enhanced implementation strategy. ClinicalTrials.gov, NCT03075085

In this cross-sectional study, early childhood educators (ECEs; N = 307) completed an 18-item survey regarding their role (lead vs. assistant), education level, program type, and current and childhood food insecurity (FI) and dietary intake. ECEs in this study reported poor dietary quality and a high rate of FI. Approximately one quarter of ECEs ate fruits and vegetables more than once per day. Of participating ECEs, 34.5% indicated current FI and 28.7% reported experiencing FI in childhood. Differences in prevalence of current FI were found for ECE role, program type, and education (all p ≤ 0.03). Regression models with childhood dietary intake, childhood FI, education, and program type as predictors accounted for a significant portion of variance in current dietary outcomes. In both models, childhood dietary intake was uniquely predictive (p < 0.001) although program type was not. Future training and education efforts for ECEs should consider including specific resources to assess and reduce ECE FI and provide practical support for healthy eating on a budget. Additional research is needed to determine the impact of ECE FI on a variety of educator and child outcomes.