Nutrition modeling tools: a qualitative study of influence on policy decision making and determining factors

Autor: Frances Knight, Megan W. Bourassa, Elaine Ferguson, Helen Walls, Saskia de Pee, Stephen Vosti, Homero Martinez, Carol Levin, Monica Woldt, Kavita Sethurman, Gilles Bergeron
Rok vydání: 2022
Předmět:
Zdroj: Annals of the New York Academy of Sciences. 1513:170-191
ISSN: 1749-6632
0077-8923
DOI: 10.1111/nyas.14778
Popis: Nutrition modeling tools (NMTs) generate evidence to inform policy and program decision making; however, the literature is generally limited to modeling methods and results, rather than use cases and their impacts. We aimed to document the policy influences of 12 NMTs and identify factors influencing them. We conducted semistructured interviews with 109 informants from 30 low- and middle-income country case studies and used thematic analysis to understand the data. NMTs were mostly applied by international organizations to inform national government decision making. NMT applications contributed to enabling environments for nutrition and influenced program design and policy in most cases; however, this influence could be strengthened. Influence was shaped by processes for applying the NMTs; ownership of the analysis and data inputs, and capacity building in NMT methods, encouraged uptake. Targeting evidence generation at specific policy cycle stages promoted uptake; however, where advocacy capacity allowed, modeling was embedded ad hoc into emerging policy discussions and had broader influence. Meanwhile, external factors, such as political change and resource constraints of local partner organizations, challenged NMT implementation. Importantly, policy uptake was never the result of NMTs exclusively, indicating they should be nested persistently and strategically within the wider evidence and advocacy continuum, rather than being stand-alone activities.
Databáze: OpenAIRE
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