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An iterative approach for estimating domain-specific cognitive abilities from large scale online cognitive data

Title: An iterative approach for estimating domain-specific cognitive abilities from large scale online cognitive data
Authors: Giunchiglia, V; Gruia, DC; Lerede, A; Trender, W; Hellyer, P; Hampshire, A
Publisher Information: Nature Portfolio
Publication Year: 2024
Collection: Imperial College London: Spiral
Description: Online cognitive tasks are gaining traction as scalable and cost-effective alternatives to traditional supervised assessments. However, variability in peoples’ home devices, visual and motor abilities, and speed-accuracy biases confound the specificity with which online tasks can measure cognitive abilities. To address these limitations, we developed IDoCT (Iterative Decomposition of Cognitive Tasks), a method for estimating domain-specific cognitive abilities and trial-difficulty scales from task performance timecourses in a data-driven manner while accounting for device and visuomotor latencies, unspecific cognitive processes and speed-accuracy trade-offs. IDoCT can operate with any computerised task where cognitive difficulty varies across trials. Using data from 388,757 adults, we show that IDoCT successfully dissociates cognitive abilities from these confounding factors. The resultant cognitive scores exhibit stronger dissociation of psychometric factors, improved cross-participants distributions, and meaningful demographic’s associations. We propose that IDoCT can enhance the precision of online cognitive assessments, especially in large scale clinical and research applications.
Document Type: article in journal/newspaper
Language: unknown
Relation: npj Digital Medicine; http://hdl.handle.net/10044/1/115932
DOI: 10.1038/s41746-024-01327-x
Availability: http://hdl.handle.net/10044/1/115932; https://doi.org/10.1038/s41746-024-01327-x
Rights: © The Author(s) 2024 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/
Accession Number: edsbas.46B49829
Database: BASE