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Defeat and entrapment: more than meets the eye? Applying network analysis to estimate dimensions of highly correlated constructs

BACKGROUND: Defeat and entrapment have been shown to be of central relevance to the development of different disorders. However, it remains unclear whether they represent two distinct constructs or one overall latent variable. One reason for the unclarity is that traditional factor analytic techniqu...

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Autores principales: Forkmann, Thomas, Teismann, Tobias, Stenzel, Jana-Sophie, Glaesmer, Heide, de Beurs, Derek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5785844/
https://www.ncbi.nlm.nih.gov/pubmed/29370770
http://dx.doi.org/10.1186/s12874-018-0470-5
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author Forkmann, Thomas
Teismann, Tobias
Stenzel, Jana-Sophie
Glaesmer, Heide
de Beurs, Derek
author_facet Forkmann, Thomas
Teismann, Tobias
Stenzel, Jana-Sophie
Glaesmer, Heide
de Beurs, Derek
author_sort Forkmann, Thomas
collection PubMed
description BACKGROUND: Defeat and entrapment have been shown to be of central relevance to the development of different disorders. However, it remains unclear whether they represent two distinct constructs or one overall latent variable. One reason for the unclarity is that traditional factor analytic techniques have trouble estimating the right number of clusters in highly correlated data. In this study, we applied a novel approach based on network analysis that can deal with correlated data to establish whether defeat and entrapment are best thought of as one or multiple constructs. METHODS: Explanatory graph analysis was used to estimate the number of dimensions within the 32 items that make up the defeat and entrapment scales in two samples: an online community sample of 480 participants, and a clinical sample of 147 inpatients admitted to a psychiatric hospital after a suicidal attempt or severe suicidal crisis. Confirmatory Factor analysis (CFA) was used to test whether the proposed structure fits the data. RESULTS: In both samples, bootstrapped exploratory graph analysis suggested that the defeat and entrapment items belonged to different dimensions. Within the entrapment items, two separate dimensions were detected, labelled internal and external entrapment. Defeat appeared to be multifaceted only in the online sample. When comparing the CFA outcomes of the one, two, three and four factor models, the one factor model was preferred. CONCLUSIONS: Defeat and entrapment can be viewed as distinct, yet, highly associated constructs. Thus, although replication is needed, results are in line with theories differentiating between these two constructs.
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spelling pubmed-57858442018-02-07 Defeat and entrapment: more than meets the eye? Applying network analysis to estimate dimensions of highly correlated constructs Forkmann, Thomas Teismann, Tobias Stenzel, Jana-Sophie Glaesmer, Heide de Beurs, Derek BMC Med Res Methodol Research Article BACKGROUND: Defeat and entrapment have been shown to be of central relevance to the development of different disorders. However, it remains unclear whether they represent two distinct constructs or one overall latent variable. One reason for the unclarity is that traditional factor analytic techniques have trouble estimating the right number of clusters in highly correlated data. In this study, we applied a novel approach based on network analysis that can deal with correlated data to establish whether defeat and entrapment are best thought of as one or multiple constructs. METHODS: Explanatory graph analysis was used to estimate the number of dimensions within the 32 items that make up the defeat and entrapment scales in two samples: an online community sample of 480 participants, and a clinical sample of 147 inpatients admitted to a psychiatric hospital after a suicidal attempt or severe suicidal crisis. Confirmatory Factor analysis (CFA) was used to test whether the proposed structure fits the data. RESULTS: In both samples, bootstrapped exploratory graph analysis suggested that the defeat and entrapment items belonged to different dimensions. Within the entrapment items, two separate dimensions were detected, labelled internal and external entrapment. Defeat appeared to be multifaceted only in the online sample. When comparing the CFA outcomes of the one, two, three and four factor models, the one factor model was preferred. CONCLUSIONS: Defeat and entrapment can be viewed as distinct, yet, highly associated constructs. Thus, although replication is needed, results are in line with theories differentiating between these two constructs. BioMed Central 2018-01-25 /pmc/articles/PMC5785844/ /pubmed/29370770 http://dx.doi.org/10.1186/s12874-018-0470-5 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Forkmann, Thomas
Teismann, Tobias
Stenzel, Jana-Sophie
Glaesmer, Heide
de Beurs, Derek
Defeat and entrapment: more than meets the eye? Applying network analysis to estimate dimensions of highly correlated constructs
title Defeat and entrapment: more than meets the eye? Applying network analysis to estimate dimensions of highly correlated constructs
title_full Defeat and entrapment: more than meets the eye? Applying network analysis to estimate dimensions of highly correlated constructs
title_fullStr Defeat and entrapment: more than meets the eye? Applying network analysis to estimate dimensions of highly correlated constructs
title_full_unstemmed Defeat and entrapment: more than meets the eye? Applying network analysis to estimate dimensions of highly correlated constructs
title_short Defeat and entrapment: more than meets the eye? Applying network analysis to estimate dimensions of highly correlated constructs
title_sort defeat and entrapment: more than meets the eye? applying network analysis to estimate dimensions of highly correlated constructs
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5785844/
https://www.ncbi.nlm.nih.gov/pubmed/29370770
http://dx.doi.org/10.1186/s12874-018-0470-5
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