Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Punzi, Clara, Tieri, Paolo, Girelli, Laura, Petti, Manuela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
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
_version_ 1784879668562755584
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
work_keys_str_mv AT punziclara networkbasedvalidationofthepsychometricquestionnaireedi3fortheassessmentofeatingdisorders
AT tieripaolo networkbasedvalidationofthepsychometricquestionnaireedi3fortheassessmentofeatingdisorders
AT girellilaura networkbasedvalidationofthepsychometricquestionnaireedi3fortheassessmentofeatingdisorders
AT pettimanuela networkbasedvalidationofthepsychometricquestionnaireedi3fortheassessmentofeatingdisorders