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Understanding the complexity of population health interventions: assessing intervention system theory (ISyT)

Given their inherent complexity, we need a better understanding of what is happening inside the “black box” of population health interventions. The theory-driven intervention/evaluation paradigm is one approach to addressing this question. However, barriers related to semantic or practical issues st...

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Autores principales: Cambon, Linda, Alla, François
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8214800/
https://www.ncbi.nlm.nih.gov/pubmed/34147105
http://dx.doi.org/10.1186/s12961-021-00743-9
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author Cambon, Linda
Alla, François
author_facet Cambon, Linda
Alla, François
author_sort Cambon, Linda
collection PubMed
description Given their inherent complexity, we need a better understanding of what is happening inside the “black box” of population health interventions. The theory-driven intervention/evaluation paradigm is one approach to addressing this question. However, barriers related to semantic or practical issues stand in the way of its complete integration into evaluation designs. In this paper, we attempt to clarify how various theories, models and frameworks can contribute to developing a context-dependent theory, helping us to understand the black box of population health interventions and to acknowledge their complexity. To achieve this goal, we clarify what could be referred to as “theory” in the theory-driven evaluation of the interventional system, distinguishing it from other models, frameworks and classical theories. In order to evaluate the interventional system with a theory-driven paradigm, we put forward the concept of interventional system theory (ISyT), which combines a causal theory and an action model. We suggest that an ISyT could guide evaluation processes, whatever evaluation design is applied, and illustrate this alternative method through different examples of studies. We believe that such a clarification can help to promote the use of theories in complex intervention evaluations, and to identify ways of considering the transferability and scalability of interventions.
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spelling pubmed-82148002021-06-23 Understanding the complexity of population health interventions: assessing intervention system theory (ISyT) Cambon, Linda Alla, François Health Res Policy Syst Commentary Given their inherent complexity, we need a better understanding of what is happening inside the “black box” of population health interventions. The theory-driven intervention/evaluation paradigm is one approach to addressing this question. However, barriers related to semantic or practical issues stand in the way of its complete integration into evaluation designs. In this paper, we attempt to clarify how various theories, models and frameworks can contribute to developing a context-dependent theory, helping us to understand the black box of population health interventions and to acknowledge their complexity. To achieve this goal, we clarify what could be referred to as “theory” in the theory-driven evaluation of the interventional system, distinguishing it from other models, frameworks and classical theories. In order to evaluate the interventional system with a theory-driven paradigm, we put forward the concept of interventional system theory (ISyT), which combines a causal theory and an action model. We suggest that an ISyT could guide evaluation processes, whatever evaluation design is applied, and illustrate this alternative method through different examples of studies. We believe that such a clarification can help to promote the use of theories in complex intervention evaluations, and to identify ways of considering the transferability and scalability of interventions. BioMed Central 2021-06-19 /pmc/articles/PMC8214800/ /pubmed/34147105 http://dx.doi.org/10.1186/s12961-021-00743-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Commentary
Cambon, Linda
Alla, François
Understanding the complexity of population health interventions: assessing intervention system theory (ISyT)
title Understanding the complexity of population health interventions: assessing intervention system theory (ISyT)
title_full Understanding the complexity of population health interventions: assessing intervention system theory (ISyT)
title_fullStr Understanding the complexity of population health interventions: assessing intervention system theory (ISyT)
title_full_unstemmed Understanding the complexity of population health interventions: assessing intervention system theory (ISyT)
title_short Understanding the complexity of population health interventions: assessing intervention system theory (ISyT)
title_sort understanding the complexity of population health interventions: assessing intervention system theory (isyt)
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8214800/
https://www.ncbi.nlm.nih.gov/pubmed/34147105
http://dx.doi.org/10.1186/s12961-021-00743-9
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