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Aligning evidence generation and use across health, development, and environment

Abstract

Although health, development, and environment challenges are interconnected, evidence remains fractured across sectors due to methodological and conceptual differences in research and practice. Aligned methods are needed to support Sustainable Development Goal advances and similar agendas. The Bridge Collaborative, an emergent research-practice collaboration, presents principles and recommendations that help harmonize methods for evidence generation and use. Recommendations were generated in the context of designing and evaluating evidence of impact for interventions related to five global challenges (stabilizing the global climate, making food production sustainable, decreasing air pollution and respiratory disease, improving sanitation and water security, and solving hunger and malnutrition) and serve as a starting point for further iteration and testing in a broader set of contexts and disciplines. We adopted six principles and emphasize three methodological recommendations: (1) creation of compatible results chains, (2) consideration of all relevant types of evidence, and (3) evaluation of strength of evidence using a unified rubric. We provide detailed suggestions for how these recommendations can be applied in practice, streamlining efforts to apply multi-objective approaches and/or synthesize evidence in multidisciplinary or transdisciplinary teams. These recommendations advance the necessary process of reconciling existing evidence standards in health, development, and environment, and initiate a common basis for integrated evidence generation and use in research, practice, and policy design.

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Publication date: 2019

Author(s): Heather Tallis, Katharine Kreis, Lydia Olander, Claudia Ringler, David Ameyaw, Mark E. Borsuk, Amber Peterman, et al.

Journal: Current Opinions in Environmental Sustainability

Volume: 39

Page(S): 81-93

Language: English

Peer reviewed: YES

Related Innocenti Project(s):

Adolescent wellbeing