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Latent variable and clustering methods in intersectionality research: systematic review of methods applications
PURPOSE: An intersectionality framework has been increasingly incorporated into quantitative study of health inequity, to incorporate social power in meaningful ways. Researchers have identified “person-centered” methods that cluster within-individual characteristics as appropriate to intersectional...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8784367/ https://www.ncbi.nlm.nih.gov/pubmed/34773462 http://dx.doi.org/10.1007/s00127-021-02195-6 |
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author | Bauer, Greta R. Mahendran, Mayuri Walwyn, Chantel Shokoohi, Mostafa |
author_facet | Bauer, Greta R. Mahendran, Mayuri Walwyn, Chantel Shokoohi, Mostafa |
author_sort | Bauer, Greta R. |
collection | PubMed |
description | PURPOSE: An intersectionality framework has been increasingly incorporated into quantitative study of health inequity, to incorporate social power in meaningful ways. Researchers have identified “person-centered” methods that cluster within-individual characteristics as appropriate to intersectionality. We aimed to review their use and match with theory. METHODS: We conducted a multidisciplinary systematic review of English-language quantitative studies wherein authors explicitly stated an intersectional approach, and used clustering methods. We extracted study characteristics and applications of intersectionality. RESULTS: 782 studies with quantitative applications of intersectionality were identified, of which 16 were eligible: eight using latent class analysis, two latent profile analysis, and six clustering methods. Papers used cross-sectional data (100.0%) primarily had U.S. lead authors (68.8%) and were published within psychology, social sciences, and health journals. While 87.5% of papers defined intersectionality and 93.8% cited foundational authors, engagement with intersectionality method literature was more limited. Clustering variables were based on social identities/positions (e.g., gender), dimensions of identity (e.g., race centrality), or processes (e.g., stigma). Results most commonly included four classes/clusters (60.0%), which were frequently used in additional analyses. These described sociodemographic differences across classes/clusters, or used classes/clusters as an exposure variable to predict outcomes in regression analysis, structural equation modeling, mediation, or survival analysis. Author rationales for method choice included both theoretical/intersectional and statistical arguments. CONCLUSION: Latent variable and clustering methods were used in varied ways in intersectional approaches, and reflected differing matches between theory and methods. We highlight situations in which these methods may be advantageous, and missed opportunities for additional uses. |
format | Online Article Text |
id | pubmed-8784367 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-87843672022-02-02 Latent variable and clustering methods in intersectionality research: systematic review of methods applications Bauer, Greta R. Mahendran, Mayuri Walwyn, Chantel Shokoohi, Mostafa Soc Psychiatry Psychiatr Epidemiol Review PURPOSE: An intersectionality framework has been increasingly incorporated into quantitative study of health inequity, to incorporate social power in meaningful ways. Researchers have identified “person-centered” methods that cluster within-individual characteristics as appropriate to intersectionality. We aimed to review their use and match with theory. METHODS: We conducted a multidisciplinary systematic review of English-language quantitative studies wherein authors explicitly stated an intersectional approach, and used clustering methods. We extracted study characteristics and applications of intersectionality. RESULTS: 782 studies with quantitative applications of intersectionality were identified, of which 16 were eligible: eight using latent class analysis, two latent profile analysis, and six clustering methods. Papers used cross-sectional data (100.0%) primarily had U.S. lead authors (68.8%) and were published within psychology, social sciences, and health journals. While 87.5% of papers defined intersectionality and 93.8% cited foundational authors, engagement with intersectionality method literature was more limited. Clustering variables were based on social identities/positions (e.g., gender), dimensions of identity (e.g., race centrality), or processes (e.g., stigma). Results most commonly included four classes/clusters (60.0%), which were frequently used in additional analyses. These described sociodemographic differences across classes/clusters, or used classes/clusters as an exposure variable to predict outcomes in regression analysis, structural equation modeling, mediation, or survival analysis. Author rationales for method choice included both theoretical/intersectional and statistical arguments. CONCLUSION: Latent variable and clustering methods were used in varied ways in intersectional approaches, and reflected differing matches between theory and methods. We highlight situations in which these methods may be advantageous, and missed opportunities for additional uses. Springer Berlin Heidelberg 2021-11-13 2022 /pmc/articles/PMC8784367/ /pubmed/34773462 http://dx.doi.org/10.1007/s00127-021-02195-6 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/) . |
spellingShingle | Review Bauer, Greta R. Mahendran, Mayuri Walwyn, Chantel Shokoohi, Mostafa Latent variable and clustering methods in intersectionality research: systematic review of methods applications |
title | Latent variable and clustering methods in intersectionality research: systematic review of methods applications |
title_full | Latent variable and clustering methods in intersectionality research: systematic review of methods applications |
title_fullStr | Latent variable and clustering methods in intersectionality research: systematic review of methods applications |
title_full_unstemmed | Latent variable and clustering methods in intersectionality research: systematic review of methods applications |
title_short | Latent variable and clustering methods in intersectionality research: systematic review of methods applications |
title_sort | latent variable and clustering methods in intersectionality research: systematic review of methods applications |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8784367/ https://www.ncbi.nlm.nih.gov/pubmed/34773462 http://dx.doi.org/10.1007/s00127-021-02195-6 |
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