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CUBES: A practical toolkit to measure enablers and barriers to behavior for effective intervention design
A pressing goal in global development and other sectors is often to understand what drives people’s behaviors, and how to influence them. Yet designing behavior change interventions is often an unsystematic process, hobbled by insufficient understanding of contextual and perceptual behavioral driver...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6601426/ https://www.ncbi.nlm.nih.gov/pubmed/31294419 http://dx.doi.org/10.12688/gatesopenres.12923.2 |
Sumario: | A pressing goal in global development and other sectors is often to understand what drives people’s behaviors, and how to influence them. Yet designing behavior change interventions is often an unsystematic process, hobbled by insufficient understanding of contextual and perceptual behavioral drivers and a narrow focus on limited research methods to assess them. We propose a toolkit (CUBES) of two solutions to help programs arrive at more effective interventions. First, we introduce a novel framework of behavior, which is a practical tool for programs to structure potential drivers and match corresponding interventions. This evidence-based framework was developed through extensive cross-sectoral literature research and refined through application in large-scale global development programs. Second, we propose a set of descriptive, experimental, and simulation approaches that can enhance and expand the methods commonly used in global development. Since not all methods are equally suited to capture the different types of drivers of behavior, we present a decision aid for method selection. We recommend that existing commonly used methods, such as observations and surveys, use CUBES as a scaffold and incorporate validated measures of specific types of drivers in order to comprehensively test all the potential components of a target behavior. We also recommend under-used methods from sectors such as market research, experimental psychology, and decision science, which programs can use to extend their toolkit and test the importance and impact of key enablers and barriers. The CUBES toolkit enables programs across sectors to streamline the process of conceptualizing, designing, and optimizing interventions, and ultimately to change behaviors and achieve targeted outcomes. |
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