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Modernizing clinical neuropsychology through advanced statistical and psychometric methods
Stroke patients often suffer from severe, persistent cognitive impairments and accurate assessment of these impairments is crucial for their care. This project has two main research aims. The primary aim is to advance evidence-based diagnosis of post-stroke cognitive impairments. To this end, we will investigate the contribution of Bayesian statistics and item-response analyses on diagnostic accuracy in the context of a post-stroke cognitive screening tool, the Oxford Cognitive Screen. In addition, we will evaluate the contribution of computational models to diagnosis of a specific post-stroke cognitive impairment (i.e., hemispatial neglect). A second aim is to translate new psychometric and statistical methods to clinical practice. To accomplish this aim, we will systematically document the needs of clinical neuropsychologists that work with the stroke population. Moreover, we will design a free-to-use online platform incorporating the newest statistical and psychometric developments for clinicians.
Date:1 Oct 2020 → 30 Sep 2021
Keywords:stroke, cognitive impairment, evidence-based practice, psychometrics, neuropsychology