Robert M Bilder1,2, Steven P Reise2. 1. a Departments of Psychiatry & Biobehavioral Science, Jane & Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles , Los Angeles , California , USA. 2. b Department of Psychiatry & Biobehavioral Science , Los Angeles , California , USA.
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.
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
Authors: Roos J Jutten; Sietske A M Sikkes; Wiesje M Van der Flier; Philip Scheltens; Pieter Jelle Visser; Betty M Tijms Journal: Neurology Date: 2021-06-01 Impact factor: 11.800
Authors: Hanneke F M Rhodius-Meester; Teemu Paajanen; Juha Koikkalainen; Shadi Mahdiani; Marie Bruun; Marta Baroni; Afina W Lemstra; Philip Scheltens; Sanna-Kaisa Herukka; Maria Pikkarainen; Anette Hall; Tuomo Hänninen; Tiia Ngandu; Miia Kivipelto; Mark van Gils; Steen Gregers Hasselbalch; Patrizia Mecocci; Anne Remes; Hilkka Soininen; Wiesje M van der Flier; Jyrki Lötjönen Journal: Alzheimers Dement (Amst) Date: 2020-08-25
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
Authors: Seyul Kwak; Dae Jong Oh; Yeong-Ju Jeon; Da Young Oh; Su Mi Park; Hairin Kim; Jun-Young Lee Journal: J Alzheimers Dis Date: 2022 Impact factor: 4.472
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