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Developing a new pragmatic tool for assessing contextual fit and feasibility of evidence-based interventions towards
Kehinde Olawale Ogunyemi1, Scott McNabb2, Virgil Lokossou3
1Hubert Department of Global Health, Emory University Rollins School of Public Health, Atlanta, Georgia, USA ogunyemikehinde89@gmail.com.
Introduction:
Understanding the contextual fit and feasibility of evidence-based interventions (EBIs) constitutes an important aspect of implementation research to inform policy decisions for their uptake and sustainability in any given context (eg, setting, sector and population). Yet current methodologies, which attempt to assess contextual fit and feasibility of EBI as key preimplementation outcomes using a reductionist approach with summative scores, fall short in capturing the multiple forms of interactions and influences of constructs and contextual factors associated with EBI implementation in a real-world situation.
Methods:
Between 18 February 2023 and 5 August 2023, we designed a novel tool through an ongoing collaborative effort of researchers, global health practitioners, policy makers and populations from low- and middle-income countries and high-income countries using a five-step sequential process. This process included step 1 (stakeholder envisioning), step 2 (evidence synthesis), step 3 (evidence deconstruction), step 4 (stakeholder consensus and conceptual framework development) and step 5 (tool development, deployment and standardisation).
Results:
Following this process, a pragmatic contextual fit and feasibility (PCoF) tool was developed with acceptability and preference derived as potentially stable constructs for contextual fit outcome and willingness to use and resource availability for feasibility outcome. The assessment of contextual fit and feasibility outcomes with strong, somewhat, and weak ratings was determined by a total of nine real-world scenarios of construct interactions in either case. Strong, somewhat and weak ratings of contextual fit or feasibility accounted for one, seven and one construct interaction(s), respectively.
Conclusion:
This initial development of PCoF is a step in the right direction for addressing the complexity associated with EBI implementation that is in part posed by contextual factors and cannot be completely explained by summative scoring and arbitrary rating approaches of existing tools. The use of PCoF as a research and policy decision-support tool, once extensively refined, validated and standardised across multiple contexts, has the potential to generate robust evidence on the contextual fit and feasibility of EBI and to meaningfully support researchers, policy makers and other stakeholders in informing the prioritisation, adaptation and equity-focused uptake and scale-up of EBI for improved population health and social outcomes.
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