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Conceptualising natural and quasi experiments in public health
BACKGROUND: Natural or quasi experiments are appealing for public health research because they enable the evaluation of events or interventions that are difficult or impossible to manipulate experimentally, such as many policy and health system reforms. However, there remains ambiguity in the litera...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7879679/ https://www.ncbi.nlm.nih.gov/pubmed/33573595 http://dx.doi.org/10.1186/s12874-021-01224-x |
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author | de Vocht, Frank Katikireddi, Srinivasa Vittal McQuire, Cheryl Tilling, Kate Hickman, Matthew Craig, Peter |
author_facet | de Vocht, Frank Katikireddi, Srinivasa Vittal McQuire, Cheryl Tilling, Kate Hickman, Matthew Craig, Peter |
author_sort | de Vocht, Frank |
collection | PubMed |
description | BACKGROUND: Natural or quasi experiments are appealing for public health research because they enable the evaluation of events or interventions that are difficult or impossible to manipulate experimentally, such as many policy and health system reforms. However, there remains ambiguity in the literature about their definition and how they differ from randomized controlled experiments and from other observational designs. We conceptualise natural experiments in the context of public health evaluations and align the study design to the Target Trial Framework. METHODS: A literature search was conducted, and key methodological papers were used to develop this work. Peer-reviewed papers were supplemented by grey literature. RESULTS: Natural experiment studies (NES) combine features of experiments and non-experiments. They differ from planned experiments, such as randomized controlled trials, in that exposure allocation is not controlled by researchers. They differ from other observational designs in that they evaluate the impact of events or process that leads to differences in exposure. As a result they are, in theory, less susceptible to bias than other observational study designs. Importantly, causal inference relies heavily on the assumption that exposure allocation can be considered ‘as-if randomized’. The target trial framework provides a systematic basis for evaluating this assumption and the other design elements that underpin the causal claims that can be made from NES. CONCLUSIONS: NES should be considered a type of study design rather than a set of tools for analyses of non-randomized interventions. Alignment of NES to the Target Trial framework will clarify the strength of evidence underpinning claims about the effectiveness of public health interventions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01224-x. |
format | Online Article Text |
id | pubmed-7879679 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-78796792021-02-17 Conceptualising natural and quasi experiments in public health de Vocht, Frank Katikireddi, Srinivasa Vittal McQuire, Cheryl Tilling, Kate Hickman, Matthew Craig, Peter BMC Med Res Methodol Technical Advance BACKGROUND: Natural or quasi experiments are appealing for public health research because they enable the evaluation of events or interventions that are difficult or impossible to manipulate experimentally, such as many policy and health system reforms. However, there remains ambiguity in the literature about their definition and how they differ from randomized controlled experiments and from other observational designs. We conceptualise natural experiments in the context of public health evaluations and align the study design to the Target Trial Framework. METHODS: A literature search was conducted, and key methodological papers were used to develop this work. Peer-reviewed papers were supplemented by grey literature. RESULTS: Natural experiment studies (NES) combine features of experiments and non-experiments. They differ from planned experiments, such as randomized controlled trials, in that exposure allocation is not controlled by researchers. They differ from other observational designs in that they evaluate the impact of events or process that leads to differences in exposure. As a result they are, in theory, less susceptible to bias than other observational study designs. Importantly, causal inference relies heavily on the assumption that exposure allocation can be considered ‘as-if randomized’. The target trial framework provides a systematic basis for evaluating this assumption and the other design elements that underpin the causal claims that can be made from NES. CONCLUSIONS: NES should be considered a type of study design rather than a set of tools for analyses of non-randomized interventions. Alignment of NES to the Target Trial framework will clarify the strength of evidence underpinning claims about the effectiveness of public health interventions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-021-01224-x. BioMed Central 2021-02-11 /pmc/articles/PMC7879679/ /pubmed/33573595 http://dx.doi.org/10.1186/s12874-021-01224-x Text en © The Author(s) 2021 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/. The Creative Commons Public Domain Dedication waiver (http://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 | Technical Advance de Vocht, Frank Katikireddi, Srinivasa Vittal McQuire, Cheryl Tilling, Kate Hickman, Matthew Craig, Peter Conceptualising natural and quasi experiments in public health |
title | Conceptualising natural and quasi experiments in public health |
title_full | Conceptualising natural and quasi experiments in public health |
title_fullStr | Conceptualising natural and quasi experiments in public health |
title_full_unstemmed | Conceptualising natural and quasi experiments in public health |
title_short | Conceptualising natural and quasi experiments in public health |
title_sort | conceptualising natural and quasi experiments in public health |
topic | Technical Advance |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7879679/ https://www.ncbi.nlm.nih.gov/pubmed/33573595 http://dx.doi.org/10.1186/s12874-021-01224-x |
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