Literature DB >> 30422045

Neuropsychological tests of the future: How do we get there from here?

Robert M Bilder1,2, Steven P Reise2.   

Abstract

OBJECTIVE: This article reviews current approaches to neuropsychological assessment, identifies opportunities for development of new methods using modern psychometric theory and advances in technology, and suggests a transition path that promotes application of novel methods without sacrificing validity.
METHODS: Theoretical/state-of-the-art review.
CONCLUSIONS: Clinical neuropsychological assessment today does not reflect advances in neuroscience, modern psychometrics, or technology. Major opportunities for improving practice include both psychometric and technological strategies. Modern psychometric approaches including item response theory (IRT) enable linking procedures that can place different measures on common scales; adaptive testing algorithms that can dramatically increase efficiency of assessment; examination of differential item functioning (DIF) to detect measures that behave differently in different groups; and person fit statistics to detect aberrant patterns of responding of high value for performance validity testing. Opportunities to introduce novel technologies include computerized adaptive testing, Web-based assessment, healthcare- and bio-informatics strategies, mobile platforms, wearables, and the 'internet-of-things'. To overcome inertia in current practices, new methods must satisfy requirements for back-compatibility with legacy instrumentation, enabling us to leverage the wealth of validity data already accrued for classic procedures. A path to achieve these goals involves creation of a global network to aggregate item-level data into a shared repository that will enable modern psychometric analyses to refine existing methods, and serve as a platform to evolve novel assessment strategies, which over time can revolutionize neuropsychological assessment practices world-wide.

Entities:  

Keywords:  Neuropsychology; clinical decision-making; diagnostic techniques and procedures; information science; psychological tests; psychometrics

Mesh:

Year:  2018        PMID: 30422045      PMCID: PMC6422683          DOI: 10.1080/13854046.2018.1521993

Source DB:  PubMed          Journal:  Clin Neuropsychol        ISSN: 1385-4046            Impact factor:   3.535


  11 in total

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2.  Attaining the recesses of the cognitive space.

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Journal:  Cogn Neurodyn       Date:  2021-11-20       Impact factor: 3.473

3.  cCOG: A web-based cognitive test tool for detecting neurodegenerative disorders.

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Journal:  Alzheimers Dement (Amst)       Date:  2020-08-25

4.  Rationale and Design of the National Neuropsychology Network.

Authors:  David W Loring; Russell M Bauer; Lucia Cavanagh; Daniel L Drane; Laura Glass Umfleet; Dustin Wahlstrom; Fiona Whelan; Keith F Widaman; Robert M Bilder; Kristen D Enriquez; Steven P Reise; KuoChung Shih
Journal:  J Int Neuropsychol Soc       Date:  2021-03-04       Impact factor: 2.892

5.  Distributed functional connectivity predicts neuropsychological test performance among older adults.

Authors:  Seyul Kwak; Hairin Kim; Hoyoung Kim; Yoosik Youm; Jeanyung Chey
Journal:  Hum Brain Mapp       Date:  2021-05-07       Impact factor: 5.038

6.  The Wisconsin Card Sorting Test: Split-Half Reliability Estimates for a Self-Administered Computerized Variant.

Authors:  Alexander Steinke; Bruno Kopp; Florian Lange
Journal:  Brain Sci       Date:  2021-04-21

7.  Utility of Machine Learning Approach with Neuropsychological Tests in Predicting Functional Impairment of Alzheimer's Disease.

Authors:  Seyul Kwak; Dae Jong Oh; Yeong-Ju Jeon; Da Young Oh; Su Mi Park; Hairin Kim; Jun-Young Lee
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Review 8.  Neuroergonomics: A Perspective from Neuropsychology, with a Proposal about Workload.

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Journal:  Brain Sci       Date:  2021-05-15

9.  How do we measure attention? Using factor analysis to establish construct validity of neuropsychological tests.

Authors:  Melissa Treviño; Xiaoshu Zhu; Yi Yi Lu; Luke S Scheuer; Eliza Passell; Grace C Huang; Laura T Germine; Todd S Horowitz
Journal:  Cogn Res Princ Implic       Date:  2021-07-22

10.  The Montreal Cognitive Assessment (MoCA): updated norms and psychometric insights into adaptive testing from healthy individuals in Northern Italy.

Authors:  Edoardo Nicolò Aiello; Chiara Gramegna; Antonella Esposito; Valentina Gazzaniga; Stefano Zago; Teresa Difonzo; Ottavia Maddaluno; Ildebrando Appollonio; Nadia Bolognini
Journal:  Aging Clin Exp Res       Date:  2021-07-27       Impact factor: 3.636

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