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The predictors of general knowledge: Data from a Spanish megastudy

Studies on sociodemographic data and crystallized intelligence have often struggled to recruit enough participants to achieve sufficient validity. However, the advent of the internet now allows this problem to be solved through the creation of megastudies. Yet, this methodology so far has only been...

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Autores principales: Buades-Sitjar, Francisco, Boada, Roger, Guasch, Marc, Ferré, Pilar, Hinojosa, José Antonio, Duñabeitia, Jon Andoni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9046360/
https://www.ncbi.nlm.nih.gov/pubmed/34357543
http://dx.doi.org/10.3758/s13428-021-01669-4
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author Buades-Sitjar, Francisco
Boada, Roger
Guasch, Marc
Ferré, Pilar
Hinojosa, José Antonio
Duñabeitia, Jon Andoni
author_facet Buades-Sitjar, Francisco
Boada, Roger
Guasch, Marc
Ferré, Pilar
Hinojosa, José Antonio
Duñabeitia, Jon Andoni
author_sort Buades-Sitjar, Francisco
collection PubMed
description Studies on sociodemographic data and crystallized intelligence have often struggled to recruit enough participants to achieve sufficient validity. However, the advent of the internet now allows this problem to be solved through the creation of megastudies. Yet, this methodology so far has only been used in studies on vocabulary size, while general knowledge, another key component of crystallized intelligence, remains unexamined. In the present study, regression models were used to examine the impact of sociodemographic variables—gender, age, years of study and socioeconomic status—on general knowledge scores. The sample comprised 48,234 participants, each of whom answered 60 general knowledge questions, their data being fully available online. Men were found to score higher than women in general knowledge. Years of study and socioeconomic status acted as strong and weak positive predictors, respectively. Age acted as a strong positive predictor until the age of 50, where it became progressively detrimental. These results are discussed relative to other studies on crystallized intelligence, highlighting the need to study each of its components individually.
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spelling pubmed-90463602022-05-07 The predictors of general knowledge: Data from a Spanish megastudy Buades-Sitjar, Francisco Boada, Roger Guasch, Marc Ferré, Pilar Hinojosa, José Antonio Duñabeitia, Jon Andoni Behav Res Methods Article Studies on sociodemographic data and crystallized intelligence have often struggled to recruit enough participants to achieve sufficient validity. However, the advent of the internet now allows this problem to be solved through the creation of megastudies. Yet, this methodology so far has only been used in studies on vocabulary size, while general knowledge, another key component of crystallized intelligence, remains unexamined. In the present study, regression models were used to examine the impact of sociodemographic variables—gender, age, years of study and socioeconomic status—on general knowledge scores. The sample comprised 48,234 participants, each of whom answered 60 general knowledge questions, their data being fully available online. Men were found to score higher than women in general knowledge. Years of study and socioeconomic status acted as strong and weak positive predictors, respectively. Age acted as a strong positive predictor until the age of 50, where it became progressively detrimental. These results are discussed relative to other studies on crystallized intelligence, highlighting the need to study each of its components individually. Springer US 2021-08-06 2022 /pmc/articles/PMC9046360/ /pubmed/34357543 http://dx.doi.org/10.3758/s13428-021-01669-4 Text en © The Author(s) 2021 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
Buades-Sitjar, Francisco
Boada, Roger
Guasch, Marc
Ferré, Pilar
Hinojosa, José Antonio
Duñabeitia, Jon Andoni
The predictors of general knowledge: Data from a Spanish megastudy
title The predictors of general knowledge: Data from a Spanish megastudy
title_full The predictors of general knowledge: Data from a Spanish megastudy
title_fullStr The predictors of general knowledge: Data from a Spanish megastudy
title_full_unstemmed The predictors of general knowledge: Data from a Spanish megastudy
title_short The predictors of general knowledge: Data from a Spanish megastudy
title_sort predictors of general knowledge: data from a spanish megastudy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9046360/
https://www.ncbi.nlm.nih.gov/pubmed/34357543
http://dx.doi.org/10.3758/s13428-021-01669-4
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