Abstract
BackgroundThe coronavirus 2019 (COVID-19) pandemic has complicated rigorous evaluation of public health nutrition programs. The USDA Gus Schumacher Nutrition Incentive Program (USDA GusNIP) funds nutrition incentive programs to improve fruit and vegetable purchasing and intake by incentivizing Supplemental Nutrition Assistance Program (SNAP) participants at the point of sale. GusNIP grantees are required to collect survey data (e.g., fruit and vegetable intake and food insecurity status) on a subset of participants. However, due to COVID-19, most GusNIP grantees faced formidable barriers to data collection. The Hunger Task Force Mobile Market (HTFMM), a Wisconsin-based 2019 GusNIP grantee, used particularly innovative methods to successfully collect these data (n > 500 surveys). ObjectivesThe aim was to explore HTFMM’s successful participant-level data-collection evaluation during COVID-19. MethodsA single case study methodological approach framed this study. The case is the HTFMM in Milwaukee, WI, USA. Participants included HTFMM leadership (n = 3), evaluators (n = 2), staff (n = 3), volunteers (n = 3), and customers (n = 10). These teleconference interviews were recorded and transcribed verbatim. Transcripts were coded using thematic qualitative analysis methods with 2 independent coders. ResultsFour salient themes emerged: 1) there were multiple key players with unique roles and responsibilities who contributed to personalized, proactive, and time-intensive, telephone-based proctored survey collection methods; 2) the importance of resources dedicated to comprehensive evaluation; 3) longstanding relationships rooted in trust and community-based service are key to successful program delivery, engagement, and evaluation; and 4) the COVID-19 data-collection protocol also serves to mitigate nonpandemic challenges to in-person survey collection. ConclusionsThese findings provide guidance on how alternative methods for data collection during COVID-19 can be used and applied to other situations that may affect the ability to collect participant-level data. These findings contribute to a growing body of literature as to best practices and approaches to collecting participant-level data to evaluate public health nutrition programs.
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