Cargando…
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...
Autores principales: | , , , , |
---|---|
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 |
_version_ | 1784842166993944576 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9714179 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT greenjudith casestudyresearchandcausalinference AT hanckelbenjamin casestudyresearchandcausalinference AT petticrewmark casestudyresearchandcausalinference AT paparinisara casestudyresearchandcausalinference AT shawsara casestudyresearchandcausalinference |