First Analysis of Nationwide Trends in the Use of the SNAP-Ed Evaluation Framework.

OBJECTIVE: To understand Supplemental Nutrition Assistance Program-Education (SNAP-Ed) Implementing Agencies'(SIAs) use of the SNAP-Ed Evaluation Framework (Framework), which is a tool that includes 51 indicators that SNAP-Ed programs can use to measure the success of their programs in the first 5 years after its release. METHODS: A repeated cross-sectional study design was utilized to administer electronic surveys to between 124 and 154 SIAs who received SNAP-Ed funding in fiscal years 2017, 2019, and 2021. Analyses included descriptive statistics and tests of proportions. RESULTS: Most SIAs indicated that they used the Framework to inform both data collection instruments and program planning decisions and the rates remained relatively constant over the 3 time points (> 80%). The most common specific use of the Framework across all 3 time points was to define, count, or measure the work accomplished, but this statistically decreased from 2017 (76%) to 2021 (57%) (z-score = 3.31; P < 0.001). CONCLUSIONS AND IMPLICATIONS: The results of this analysis confirmed that 5 years after its introduction, uptake and use of the Framework was high and that, as a whole, SIAs focused on priority indicators set by the US Department of Agriculture, with no notable increases in addressing and measuring longer-term, multisector, and population-wide outcomes. The systematic study of the Framework's usability over time has a broader application to other national health promotion initiatives with shared frameworks.

Validation of 2 Brief Fruit and Vegetable Assessment Instruments Among Third-Grade Students.

OBJECTIVE: To evaluate the validity of 2 brief instruments to estimate fruit and vegetable (FV) intake among third-grade children. METHODS: Children from an elementary school and a community center (n = 107) completed 2 retrospective questions for FV intake (fruit and vegetable questionnaire [FVQ]) and a food record (A Day in the Life Questionnaire [DILQ]) to estimate FV intake. Agreement between intake based on these instruments and 3 24-hour dietary recalls was determined. RESULTS: Disattenuated Pearson correlation coefficients ranged from 0.40 to 0.69 for FV intake; however, the low reliability of multiple 24-hour recalls may have inflated the strength of the correlations. Altman-Bland difference plots suggested that the FVQ overestimated FV intake whereas the DILQ overestimated fruit and underestimated vegetable intake. Limits of agreement were wide for both tools, indicating poor overall agreement. CONCLUSIONS AND IMPLICATIONS: The FVQ and DILQ were not valid instruments to evaluate FV consumption under current study conditions. Other assessment methods and instruments should be considered for young children.