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Inferring Cognitive Abilities from Response Times to Web-Administered Survey Items in a Population-Representative Sample

Monitoring of cognitive abilities in large-scale survey research is receiving increasing attention. Conventional cognitive testing, however, is often impractical on a population level highlighting the need for alternative means of cognitive assessment. We evaluated whether response times (RTs) to on...

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Autores principales: Junghaenel, Doerte U., Schneider, Stefan, Orriens, Bart, Jin, Haomiao, Lee, Pey-Jiuan, Kapteyn, Arie, Meijer, Erik, Zelinski, Elizabeth, Hernandez, Raymond, Stone, Arthur A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9864969/
https://www.ncbi.nlm.nih.gov/pubmed/36662133
http://dx.doi.org/10.3390/jintelligence11010003
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author Junghaenel, Doerte U.
Schneider, Stefan
Orriens, Bart
Jin, Haomiao
Lee, Pey-Jiuan
Kapteyn, Arie
Meijer, Erik
Zelinski, Elizabeth
Hernandez, Raymond
Stone, Arthur A.
author_facet Junghaenel, Doerte U.
Schneider, Stefan
Orriens, Bart
Jin, Haomiao
Lee, Pey-Jiuan
Kapteyn, Arie
Meijer, Erik
Zelinski, Elizabeth
Hernandez, Raymond
Stone, Arthur A.
author_sort Junghaenel, Doerte U.
collection PubMed
description Monitoring of cognitive abilities in large-scale survey research is receiving increasing attention. Conventional cognitive testing, however, is often impractical on a population level highlighting the need for alternative means of cognitive assessment. We evaluated whether response times (RTs) to online survey items could be useful to infer cognitive abilities. We analyzed >5 million survey item RTs from >6000 individuals administered over 6.5 years in an internet panel together with cognitive tests (numerical reasoning, verbal reasoning, task switching/inhibitory control). We derived measures of mean RT and intraindividual RT variability from a multilevel location-scale model as well as an expanded version that separated intraindividual RT variability into systematic RT adjustments (variation of RTs with item time intensities) and residual intraindividual RT variability (residual error in RTs). RT measures from the location-scale model showed weak associations with cognitive test scores. However, RT measures from the expanded model explained 22–26% of the variance in cognitive scores and had prospective associations with cognitive assessments over lag-periods of at least 6.5 years (mean RTs), 4.5 years (systematic RT adjustments) and 1 year (residual RT variability). Our findings suggest that RTs in online surveys may be useful for gaining information about cognitive abilities in large-scale survey research.
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spelling pubmed-98649692023-01-22 Inferring Cognitive Abilities from Response Times to Web-Administered Survey Items in a Population-Representative Sample Junghaenel, Doerte U. Schneider, Stefan Orriens, Bart Jin, Haomiao Lee, Pey-Jiuan Kapteyn, Arie Meijer, Erik Zelinski, Elizabeth Hernandez, Raymond Stone, Arthur A. J Intell Article Monitoring of cognitive abilities in large-scale survey research is receiving increasing attention. Conventional cognitive testing, however, is often impractical on a population level highlighting the need for alternative means of cognitive assessment. We evaluated whether response times (RTs) to online survey items could be useful to infer cognitive abilities. We analyzed >5 million survey item RTs from >6000 individuals administered over 6.5 years in an internet panel together with cognitive tests (numerical reasoning, verbal reasoning, task switching/inhibitory control). We derived measures of mean RT and intraindividual RT variability from a multilevel location-scale model as well as an expanded version that separated intraindividual RT variability into systematic RT adjustments (variation of RTs with item time intensities) and residual intraindividual RT variability (residual error in RTs). RT measures from the location-scale model showed weak associations with cognitive test scores. However, RT measures from the expanded model explained 22–26% of the variance in cognitive scores and had prospective associations with cognitive assessments over lag-periods of at least 6.5 years (mean RTs), 4.5 years (systematic RT adjustments) and 1 year (residual RT variability). Our findings suggest that RTs in online surveys may be useful for gaining information about cognitive abilities in large-scale survey research. MDPI 2022-12-23 /pmc/articles/PMC9864969/ /pubmed/36662133 http://dx.doi.org/10.3390/jintelligence11010003 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Junghaenel, Doerte U.
Schneider, Stefan
Orriens, Bart
Jin, Haomiao
Lee, Pey-Jiuan
Kapteyn, Arie
Meijer, Erik
Zelinski, Elizabeth
Hernandez, Raymond
Stone, Arthur A.
Inferring Cognitive Abilities from Response Times to Web-Administered Survey Items in a Population-Representative Sample
title Inferring Cognitive Abilities from Response Times to Web-Administered Survey Items in a Population-Representative Sample
title_full Inferring Cognitive Abilities from Response Times to Web-Administered Survey Items in a Population-Representative Sample
title_fullStr Inferring Cognitive Abilities from Response Times to Web-Administered Survey Items in a Population-Representative Sample
title_full_unstemmed Inferring Cognitive Abilities from Response Times to Web-Administered Survey Items in a Population-Representative Sample
title_short Inferring Cognitive Abilities from Response Times to Web-Administered Survey Items in a Population-Representative Sample
title_sort inferring cognitive abilities from response times to web-administered survey items in a population-representative sample
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9864969/
https://www.ncbi.nlm.nih.gov/pubmed/36662133
http://dx.doi.org/10.3390/jintelligence11010003
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