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The Factor Structure of Cognitive Functioning in Cognitively Healthy Participants: a Meta-Analysis and Meta-Analysis of Individual Participant Data
Many neuropsychologists are of the opinion that the multitude of cognitive tests may be grouped into a much smaller number of cognitive domains. However, there is little consensus on how many domains exist, what these domains are, nor on which cognitive tests belong to which domain. This incertitude...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7089912/ https://www.ncbi.nlm.nih.gov/pubmed/32008158 http://dx.doi.org/10.1007/s11065-019-09423-6 |
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author | Agelink van Rentergem, Joost A. de Vent, Nathalie R. Schmand, Ben A. Murre, Jaap M. J. Staaks, Janneke P. C. Huizenga, Hilde M. |
author_facet | Agelink van Rentergem, Joost A. de Vent, Nathalie R. Schmand, Ben A. Murre, Jaap M. J. Staaks, Janneke P. C. Huizenga, Hilde M. |
author_sort | Agelink van Rentergem, Joost A. |
collection | PubMed |
description | Many neuropsychologists are of the opinion that the multitude of cognitive tests may be grouped into a much smaller number of cognitive domains. However, there is little consensus on how many domains exist, what these domains are, nor on which cognitive tests belong to which domain. This incertitude can be solved by factor analysis, provided that the analysis includes a broad range of cognitive tests that have been administered to a very large number of people. In this article, two such factor analyses were performed, each combining multiple studies. However, because it was not possible to obtain complete multivariate data on more than the most common test variables in the field, not all possible domains were examined here. The first analysis was a factor meta-analysis of correlation matrices combining data of 60,398 healthy participants from 52 studies. Several models from the literature were fitted, of which a version based on the Cattell-Horn-Carroll (CHC) model was found to describe the correlations better than the others. The second analysis was a factor analysis of the Advanced Neuropsychological Diagnostics Infrastructure (ANDI) database, combining scores of 11,881 participants from 54 Dutch and Belgian studies not included in the first meta-analysis. Again, the model fit was better for the CHC model than for other models. Therefore, we conclude that the CHC model best characterizes both cognitive domains and which test belongs to each domain. Therefore, although originally developed in the intelligence literature, the CHC model deserves more attention in neuropsychology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11065-019-09423-6) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7089912 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-70899122020-03-26 The Factor Structure of Cognitive Functioning in Cognitively Healthy Participants: a Meta-Analysis and Meta-Analysis of Individual Participant Data Agelink van Rentergem, Joost A. de Vent, Nathalie R. Schmand, Ben A. Murre, Jaap M. J. Staaks, Janneke P. C. Huizenga, Hilde M. Neuropsychol Rev Review Many neuropsychologists are of the opinion that the multitude of cognitive tests may be grouped into a much smaller number of cognitive domains. However, there is little consensus on how many domains exist, what these domains are, nor on which cognitive tests belong to which domain. This incertitude can be solved by factor analysis, provided that the analysis includes a broad range of cognitive tests that have been administered to a very large number of people. In this article, two such factor analyses were performed, each combining multiple studies. However, because it was not possible to obtain complete multivariate data on more than the most common test variables in the field, not all possible domains were examined here. The first analysis was a factor meta-analysis of correlation matrices combining data of 60,398 healthy participants from 52 studies. Several models from the literature were fitted, of which a version based on the Cattell-Horn-Carroll (CHC) model was found to describe the correlations better than the others. The second analysis was a factor analysis of the Advanced Neuropsychological Diagnostics Infrastructure (ANDI) database, combining scores of 11,881 participants from 54 Dutch and Belgian studies not included in the first meta-analysis. Again, the model fit was better for the CHC model than for other models. Therefore, we conclude that the CHC model best characterizes both cognitive domains and which test belongs to each domain. Therefore, although originally developed in the intelligence literature, the CHC model deserves more attention in neuropsychology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11065-019-09423-6) contains supplementary material, which is available to authorized users. Springer US 2020-02-01 2020 /pmc/articles/PMC7089912/ /pubmed/32008158 http://dx.doi.org/10.1007/s11065-019-09423-6 Text en © The Author(s) 2020 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/. |
spellingShingle | Review Agelink van Rentergem, Joost A. de Vent, Nathalie R. Schmand, Ben A. Murre, Jaap M. J. Staaks, Janneke P. C. Huizenga, Hilde M. The Factor Structure of Cognitive Functioning in Cognitively Healthy Participants: a Meta-Analysis and Meta-Analysis of Individual Participant Data |
title | The Factor Structure of Cognitive Functioning in Cognitively Healthy Participants: a Meta-Analysis and Meta-Analysis of Individual Participant Data |
title_full | The Factor Structure of Cognitive Functioning in Cognitively Healthy Participants: a Meta-Analysis and Meta-Analysis of Individual Participant Data |
title_fullStr | The Factor Structure of Cognitive Functioning in Cognitively Healthy Participants: a Meta-Analysis and Meta-Analysis of Individual Participant Data |
title_full_unstemmed | The Factor Structure of Cognitive Functioning in Cognitively Healthy Participants: a Meta-Analysis and Meta-Analysis of Individual Participant Data |
title_short | The Factor Structure of Cognitive Functioning in Cognitively Healthy Participants: a Meta-Analysis and Meta-Analysis of Individual Participant Data |
title_sort | factor structure of cognitive functioning in cognitively healthy participants: a meta-analysis and meta-analysis of individual participant data |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7089912/ https://www.ncbi.nlm.nih.gov/pubmed/32008158 http://dx.doi.org/10.1007/s11065-019-09423-6 |
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