Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Agelink van Rentergem, Joost A., de Vent, Nathalie R., Schmand, Ben A., Murre, Jaap M. J., Staaks, Janneke P. C., Huizenga, Hilde M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2020
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
_version_ 1783509817737871360
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
work_keys_str_mv AT agelinkvanrentergemjoosta thefactorstructureofcognitivefunctioningincognitivelyhealthyparticipantsametaanalysisandmetaanalysisofindividualparticipantdata
AT deventnathalier thefactorstructureofcognitivefunctioningincognitivelyhealthyparticipantsametaanalysisandmetaanalysisofindividualparticipantdata
AT schmandbena thefactorstructureofcognitivefunctioningincognitivelyhealthyparticipantsametaanalysisandmetaanalysisofindividualparticipantdata
AT murrejaapmj thefactorstructureofcognitivefunctioningincognitivelyhealthyparticipantsametaanalysisandmetaanalysisofindividualparticipantdata
AT staaksjannekepc thefactorstructureofcognitivefunctioningincognitivelyhealthyparticipantsametaanalysisandmetaanalysisofindividualparticipantdata
AT thefactorstructureofcognitivefunctioningincognitivelyhealthyparticipantsametaanalysisandmetaanalysisofindividualparticipantdata
AT huizengahildem thefactorstructureofcognitivefunctioningincognitivelyhealthyparticipantsametaanalysisandmetaanalysisofindividualparticipantdata
AT agelinkvanrentergemjoosta factorstructureofcognitivefunctioningincognitivelyhealthyparticipantsametaanalysisandmetaanalysisofindividualparticipantdata
AT deventnathalier factorstructureofcognitivefunctioningincognitivelyhealthyparticipantsametaanalysisandmetaanalysisofindividualparticipantdata
AT schmandbena factorstructureofcognitivefunctioningincognitivelyhealthyparticipantsametaanalysisandmetaanalysisofindividualparticipantdata
AT murrejaapmj factorstructureofcognitivefunctioningincognitivelyhealthyparticipantsametaanalysisandmetaanalysisofindividualparticipantdata
AT staaksjannekepc factorstructureofcognitivefunctioningincognitivelyhealthyparticipantsametaanalysisandmetaanalysisofindividualparticipantdata
AT factorstructureofcognitivefunctioningincognitivelyhealthyparticipantsametaanalysisandmetaanalysisofindividualparticipantdata
AT huizengahildem factorstructureofcognitivefunctioningincognitivelyhealthyparticipantsametaanalysisandmetaanalysisofindividualparticipantdata