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Developing a tool for the measurement of social exclusion in healthcare settings

BACKGROUND: Social exclusion is a complex concept that is recognised as a key determinant of health. Many measurement tools developed looked at people from single excluded groups in isolation. We know from experience and literature that exclusion is often intersectional and multi-layered. Therefore,...

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Autores principales: O’Donnell, Patrick, Hannigan, Ailish, Ibrahim, Nuha, O’Donovan, Diarmuid, Elmusharaf, Khalifa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922776/
https://www.ncbi.nlm.nih.gov/pubmed/35292025
http://dx.doi.org/10.1186/s12939-022-01636-1
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author O’Donnell, Patrick
Hannigan, Ailish
Ibrahim, Nuha
O’Donovan, Diarmuid
Elmusharaf, Khalifa
author_facet O’Donnell, Patrick
Hannigan, Ailish
Ibrahim, Nuha
O’Donovan, Diarmuid
Elmusharaf, Khalifa
author_sort O’Donnell, Patrick
collection PubMed
description BACKGROUND: Social exclusion is a complex concept that is recognised as a key determinant of health. Many measurement tools developed looked at people from single excluded groups in isolation. We know from experience and literature that exclusion is often intersectional and multi-layered. Therefore, the aim of this research was to develop a social exclusion measurement tool for use in healthcare settings with individuals from any excluded group that would include questions to investigate socioeconomic elements and subjective experiences in their lives. METHODS: Inductive and deductive methods were used to develop the tool. Early drafts were tested with experts (both academic and experts by experience) and modified in line with feedback received. The tool was then piloted with people in the community, and this allowed us to assess the internal consistency and validity of the tool. Exploratory factor analysis was carried out as part of this evaluation. RESULTS: The measurement tool was initially evaluated by 17 academic and ‘real world’ experts. It was then piloted with seven experts by experience, two gatekeepers and two participants who were presumed not to be excluded, resulting in the development of the final tool. This was then tested with 276 participants (127 presumed excluded, 149 presumed not excluded). The socioeconomic characteristics of these participants were documented, and exploratory factor analysis was carried out on data relating to subjective items. A four-factor structure emerged comprising 22 items. Internal consistency of the factors was high, and their ability to discriminate between the two groups was notable. CONCLUSIONS: A tool for measuring the social exclusion of individuals has been developed by engaging with people from a variety of excluded groups. Socioeconomic indicators were combined with subjective items. The input of experts by experience, academics and others was sought to enhance the tool. The tool was applied to two distinct samples, showing obvious differences both in the socioeconomic items, and the items included in the factor analysis. The potential use of this tool could have positive implications for people who are excluded. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12939-022-01636-1.
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spelling pubmed-89227762022-03-22 Developing a tool for the measurement of social exclusion in healthcare settings O’Donnell, Patrick Hannigan, Ailish Ibrahim, Nuha O’Donovan, Diarmuid Elmusharaf, Khalifa Int J Equity Health Research BACKGROUND: Social exclusion is a complex concept that is recognised as a key determinant of health. Many measurement tools developed looked at people from single excluded groups in isolation. We know from experience and literature that exclusion is often intersectional and multi-layered. Therefore, the aim of this research was to develop a social exclusion measurement tool for use in healthcare settings with individuals from any excluded group that would include questions to investigate socioeconomic elements and subjective experiences in their lives. METHODS: Inductive and deductive methods were used to develop the tool. Early drafts were tested with experts (both academic and experts by experience) and modified in line with feedback received. The tool was then piloted with people in the community, and this allowed us to assess the internal consistency and validity of the tool. Exploratory factor analysis was carried out as part of this evaluation. RESULTS: The measurement tool was initially evaluated by 17 academic and ‘real world’ experts. It was then piloted with seven experts by experience, two gatekeepers and two participants who were presumed not to be excluded, resulting in the development of the final tool. This was then tested with 276 participants (127 presumed excluded, 149 presumed not excluded). The socioeconomic characteristics of these participants were documented, and exploratory factor analysis was carried out on data relating to subjective items. A four-factor structure emerged comprising 22 items. Internal consistency of the factors was high, and their ability to discriminate between the two groups was notable. CONCLUSIONS: A tool for measuring the social exclusion of individuals has been developed by engaging with people from a variety of excluded groups. Socioeconomic indicators were combined with subjective items. The input of experts by experience, academics and others was sought to enhance the tool. The tool was applied to two distinct samples, showing obvious differences both in the socioeconomic items, and the items included in the factor analysis. The potential use of this tool could have positive implications for people who are excluded. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12939-022-01636-1. BioMed Central 2022-03-15 /pmc/articles/PMC8922776/ /pubmed/35292025 http://dx.doi.org/10.1186/s12939-022-01636-1 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 Research
O’Donnell, Patrick
Hannigan, Ailish
Ibrahim, Nuha
O’Donovan, Diarmuid
Elmusharaf, Khalifa
Developing a tool for the measurement of social exclusion in healthcare settings
title Developing a tool for the measurement of social exclusion in healthcare settings
title_full Developing a tool for the measurement of social exclusion in healthcare settings
title_fullStr Developing a tool for the measurement of social exclusion in healthcare settings
title_full_unstemmed Developing a tool for the measurement of social exclusion in healthcare settings
title_short Developing a tool for the measurement of social exclusion in healthcare settings
title_sort developing a tool for the measurement of social exclusion in healthcare settings
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8922776/
https://www.ncbi.nlm.nih.gov/pubmed/35292025
http://dx.doi.org/10.1186/s12939-022-01636-1
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