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Case study research and causal inference

Case study methodology is widely used in health research, but has had a marginal role in evaluative studies, given it is often assumed that case studies offer little for making causal inferences. We undertook a narrative review of examples of case study research from public health and health service...

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Autores principales: Green, Judith, Hanckel, Benjamin, Petticrew, Mark, Paparini, Sara, Shaw, Sara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714179/
https://www.ncbi.nlm.nih.gov/pubmed/36456923
http://dx.doi.org/10.1186/s12874-022-01790-8
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author Green, Judith
Hanckel, Benjamin
Petticrew, Mark
Paparini, Sara
Shaw, Sara
author_facet Green, Judith
Hanckel, Benjamin
Petticrew, Mark
Paparini, Sara
Shaw, Sara
author_sort Green, Judith
collection PubMed
description Case study methodology is widely used in health research, but has had a marginal role in evaluative studies, given it is often assumed that case studies offer little for making causal inferences. We undertook a narrative review of examples of case study research from public health and health services evaluations, with a focus on interventions addressing health inequalities. We identified five types of contribution these case studies made to evidence for causal relationships. These contributions relate to: (1) evidence about system actors’ own theories of causality; (2) demonstrative examples of causal relationships; (3) evidence about causal mechanisms; (4) evidence about the conditions under which causal mechanisms operate; and (5) inference about causality in complex systems. Case studies can and do contribute to understanding causal relationships. More transparency in the reporting of case studies would enhance their discoverability, and aid the development of a robust and pluralistic evidence base for public health and health services interventions. To strengthen the contribution that case studies make to that evidence base, researchers could: draw on wider methods from the political and social sciences, in particular on methods for robust analysis; carefully consider what population their case is a case ‘of’; and explicate the rationale used for making causal inferences.
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spelling pubmed-97141792022-12-02 Case study research and causal inference Green, Judith Hanckel, Benjamin Petticrew, Mark Paparini, Sara Shaw, Sara BMC Med Res Methodol Review Case study methodology is widely used in health research, but has had a marginal role in evaluative studies, given it is often assumed that case studies offer little for making causal inferences. We undertook a narrative review of examples of case study research from public health and health services evaluations, with a focus on interventions addressing health inequalities. We identified five types of contribution these case studies made to evidence for causal relationships. These contributions relate to: (1) evidence about system actors’ own theories of causality; (2) demonstrative examples of causal relationships; (3) evidence about causal mechanisms; (4) evidence about the conditions under which causal mechanisms operate; and (5) inference about causality in complex systems. Case studies can and do contribute to understanding causal relationships. More transparency in the reporting of case studies would enhance their discoverability, and aid the development of a robust and pluralistic evidence base for public health and health services interventions. To strengthen the contribution that case studies make to that evidence base, researchers could: draw on wider methods from the political and social sciences, in particular on methods for robust analysis; carefully consider what population their case is a case ‘of’; and explicate the rationale used for making causal inferences. BioMed Central 2022-12-01 /pmc/articles/PMC9714179/ /pubmed/36456923 http://dx.doi.org/10.1186/s12874-022-01790-8 Text en © The Author(s) 2022 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 Review
Green, Judith
Hanckel, Benjamin
Petticrew, Mark
Paparini, Sara
Shaw, Sara
Case study research and causal inference
title Case study research and causal inference
title_full Case study research and causal inference
title_fullStr Case study research and causal inference
title_full_unstemmed Case study research and causal inference
title_short Case study research and causal inference
title_sort case study research and causal inference
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9714179/
https://www.ncbi.nlm.nih.gov/pubmed/36456923
http://dx.doi.org/10.1186/s12874-022-01790-8
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