Cargando…
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...
Autores principales: | , , , , , , , , , |
---|---|
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 |
_version_ | 1784875719134806016 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9864969 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT junghaeneldoerteu inferringcognitiveabilitiesfromresponsetimestowebadministeredsurveyitemsinapopulationrepresentativesample AT schneiderstefan inferringcognitiveabilitiesfromresponsetimestowebadministeredsurveyitemsinapopulationrepresentativesample AT orriensbart inferringcognitiveabilitiesfromresponsetimestowebadministeredsurveyitemsinapopulationrepresentativesample AT jinhaomiao inferringcognitiveabilitiesfromresponsetimestowebadministeredsurveyitemsinapopulationrepresentativesample AT leepeyjiuan inferringcognitiveabilitiesfromresponsetimestowebadministeredsurveyitemsinapopulationrepresentativesample AT kapteynarie inferringcognitiveabilitiesfromresponsetimestowebadministeredsurveyitemsinapopulationrepresentativesample AT meijererik inferringcognitiveabilitiesfromresponsetimestowebadministeredsurveyitemsinapopulationrepresentativesample AT zelinskielizabeth inferringcognitiveabilitiesfromresponsetimestowebadministeredsurveyitemsinapopulationrepresentativesample AT hernandezraymond inferringcognitiveabilitiesfromresponsetimestowebadministeredsurveyitemsinapopulationrepresentativesample AT stonearthura inferringcognitiveabilitiesfromresponsetimestowebadministeredsurveyitemsinapopulationrepresentativesample |