grimes-protocolforthe-2018.pdf (591.67 kB)
Protocol for the process evaluation of a complex, statewide intervention to reduce salt intake in Victoria, Australia
journal contribution
posted on 2018-07-01, 00:00 authored by K Trieu, S Jan, M Woodward, Carley GrimesCarley Grimes, B Bolam, Caryl NowsonCaryl Nowson, J Reimers, C Davidson, J WebsterSystematic reviews of trials consistently demonstrate that reducing salt intake lowers blood pressure. However, there is limited evidence on how interventions function in the real world to achieve sustained population-wide salt reduction. Process evaluations are crucial for understanding how and why an intervention resulted in its observed effect in that setting, particularly for complex interventions. This project presents the detailed protocol for a process evaluation of a statewide strategy to lower salt intake in Victoria, Australia. We describe the pragmatic methods used to collect and analyse data on six process evaluation dimensions: reach, dose or adoption, fidelity, effectiveness, context and cost, informed by Linnan and Steckler’s framework and RE-AIM. Data collection methods include routinely collected administrative data; surveys of processed foods, the population, food industry and organizations; targeted campaign evaluation and semi-structured interviews. Quantitative and qualitative data will be triangulated to provide validation or context for one another. This process evaluation will contribute new knowledge about what components of the intervention are important to salt reduction strategies and how the interventions cause reduced salt intake, to inform the transferability of the program to other Australian states and territories. This protocol can be adapted for other population-based, complex, disease prevention interventions.
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Journal
NutrientsVolume
10Issue
8Pagination
1 - 12Publisher
MDPILocation
Basel, SwitzerlandPublisher DOI
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eISSN
2072-6643Language
engPublication classification
C1 Refereed article in a scholarly journalCopyright notice
2017, The Author(s)Usage metrics
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