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Network-based validation of the psychometric questionnaire EDI-3 for the assessment of eating disorders
Assessing the validity of a psychometric test is fundamental to ensure a reliable interpretation of its outcomes. Few attempts have been made recently to complement classical approaches (e.g., factor models) with a novel technique based on network analysis. The objective of the current study is to c...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9884211/ https://www.ncbi.nlm.nih.gov/pubmed/36709357 http://dx.doi.org/10.1038/s41598-023-28743-5 |
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author | Punzi, Clara Tieri, Paolo Girelli, Laura Petti, Manuela |
author_facet | Punzi, Clara Tieri, Paolo Girelli, Laura Petti, Manuela |
author_sort | Punzi, Clara |
collection | PubMed |
description | Assessing the validity of a psychometric test is fundamental to ensure a reliable interpretation of its outcomes. Few attempts have been made recently to complement classical approaches (e.g., factor models) with a novel technique based on network analysis. The objective of the current study is to carry out a network-based validation of the Eating Disorder Inventory 3 (EDI-3), a questionnaire designed for the assessment of eating disorders. Exploiting a reliable, open source sample of 1206 patients diagnosed with an eating disorder, we set up a robust validation process encompassing detection and handling of redundant EDI-3 items, estimation of the cross-sample psychometric network, resampling bootstrap procedure and computation of the median network of the replica samples. We then employed a community detection algorithm to identify the topological clusters, evaluated their coherence with the EDI-3 subscales and replicated the full validation analysis on the subpopulations corresponding to patients diagnosed with either anorexia nervosa or bulimia nervosa. Results of the network-based analysis, and particularly the topological community structures, provided support for almost all the composite scores of the EDI-3 and for 2 single subscales: Bulimia and Maturity Fear. A moderate instability of some dimensions led to the identification of a few multidimensional items that should be better located in the intersection of multiple psychological scales. We also found that, besides symptoms typically attributed to eating disorders, such as drive for thinness, also non-specific symptoms like low self-esteem and interoceptive deficits play a central role in both the cross-sample and the diagnosis-specific networks. Our work adds insights into the complex and multidimensional structure of EDI-3 by providing support to its network-based validity on both mixed and diagnosis-specific samples. Moreover, we replicated previous results that reinforce the transdiagnostic theory of eating disorders. |
format | Online Article Text |
id | pubmed-9884211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98842112023-01-30 Network-based validation of the psychometric questionnaire EDI-3 for the assessment of eating disorders Punzi, Clara Tieri, Paolo Girelli, Laura Petti, Manuela Sci Rep Article Assessing the validity of a psychometric test is fundamental to ensure a reliable interpretation of its outcomes. Few attempts have been made recently to complement classical approaches (e.g., factor models) with a novel technique based on network analysis. The objective of the current study is to carry out a network-based validation of the Eating Disorder Inventory 3 (EDI-3), a questionnaire designed for the assessment of eating disorders. Exploiting a reliable, open source sample of 1206 patients diagnosed with an eating disorder, we set up a robust validation process encompassing detection and handling of redundant EDI-3 items, estimation of the cross-sample psychometric network, resampling bootstrap procedure and computation of the median network of the replica samples. We then employed a community detection algorithm to identify the topological clusters, evaluated their coherence with the EDI-3 subscales and replicated the full validation analysis on the subpopulations corresponding to patients diagnosed with either anorexia nervosa or bulimia nervosa. Results of the network-based analysis, and particularly the topological community structures, provided support for almost all the composite scores of the EDI-3 and for 2 single subscales: Bulimia and Maturity Fear. A moderate instability of some dimensions led to the identification of a few multidimensional items that should be better located in the intersection of multiple psychological scales. We also found that, besides symptoms typically attributed to eating disorders, such as drive for thinness, also non-specific symptoms like low self-esteem and interoceptive deficits play a central role in both the cross-sample and the diagnosis-specific networks. Our work adds insights into the complex and multidimensional structure of EDI-3 by providing support to its network-based validity on both mixed and diagnosis-specific samples. Moreover, we replicated previous results that reinforce the transdiagnostic theory of eating disorders. Nature Publishing Group UK 2023-01-28 /pmc/articles/PMC9884211/ /pubmed/36709357 http://dx.doi.org/10.1038/s41598-023-28743-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 | Article Punzi, Clara Tieri, Paolo Girelli, Laura Petti, Manuela Network-based validation of the psychometric questionnaire EDI-3 for the assessment of eating disorders |
title | Network-based validation of the psychometric questionnaire EDI-3 for the assessment of eating disorders |
title_full | Network-based validation of the psychometric questionnaire EDI-3 for the assessment of eating disorders |
title_fullStr | Network-based validation of the psychometric questionnaire EDI-3 for the assessment of eating disorders |
title_full_unstemmed | Network-based validation of the psychometric questionnaire EDI-3 for the assessment of eating disorders |
title_short | Network-based validation of the psychometric questionnaire EDI-3 for the assessment of eating disorders |
title_sort | network-based validation of the psychometric questionnaire edi-3 for the assessment of eating disorders |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9884211/ https://www.ncbi.nlm.nih.gov/pubmed/36709357 http://dx.doi.org/10.1038/s41598-023-28743-5 |
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