Examines readiness and capacity for community nutrition interventions, highlighting effective strategies.
Background Policy, systems, and environmental (PSE) interventions are recommended to address diet-related chronic diseases, yet guidance for selecting PSE implementation strategies for unique community contexts remains limited. Previous research identified the importance of specific readiness and capacity factors for implementing PSEs at farmers markets and translated them into a weighted assessment for practitioners. Purpose We examined the robustness of a weighted scoring algorithm and algorithm derived recommendations to guide implementation of PSE interventions. Methods The scoring algorithm, a hierarchical weighted-sum model, quantifies PSE readiness and generates recommendations to guide implementation strategies. Two tests evaluated the algorithm’s performance. Test 1 analyzed assessment data from practitioners in OH (N = 5) to explore readiness score variation and algorithm derived recommendations. Test 2 used a 30-indicator survey on farmers’ market PSEs to simulate 1000 baseline assessments (T0) and reassessments at three follow up time points (T1–T3). During reassessments, the simulation assigned probabilistic improvements in prioritized indicators to reflect varying success in accomplishing recommendations. Results In Test 1, overall readiness scores ranged from 37.31 to 70.31 (maximum = 100); 66.6% of all algorithm derived recommendations were unique to one responder. In Test 2, by the third reassessment (T = 3), 89.5% of the simulated respondents experienced changes in one (40.5%), two (36.7%), or three (12.3%) prioritized indicators from the preceding reassessment. Conclusion The algorithm effectively characterized distinct readiness and capacity profiles and refined recommendations for PSE implementation strategies in response to changes in community readiness. Findings highlight one approach to efficiently prioritize PSE implementation strategies across different communities.
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Schulte et al. (2026) studied this question.
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