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Neuropsychological Assessment Using Virtual Environments: Enhanced Assessment Technology for Improved Ecological Validity

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 337))

Abstract

Although today’s neuropsychological assessment procedures are widely used, neuropsychologists have been slow to embrace technological advancements. Two essential limitations have resulted from this refusal of technological adaptation: First, current neuropsychological assessment procedures represent a technology that has barely changed since the first scales were developed in the early 1900s. Second, while the historical purpose of clinical neuropsychology was differential diagnosis of brain pathology, technological advances in other clinical neurosciences have changed the neuropsychologist’s role to that of making ecologically valid predictions about the impact of a given patient’s neurocognitive abilities and disabilities on everyday functioning. After a brief discussion of current applications of computer-based neuropsychological assessment, there is a discussion of an increasingly important topic in recent decades—the design of ecologically valid neuropsychological instruments to address real world outcomes. Finally, there is an exploration of virtual reality environments for ecologically valid neuropsychological assessments that make use of current technological advances. It is concluded that a future possible virtual reality-based neuropsychological assessment battery will combine the control and rigor of technologically advanced computerized laboratory measures, the psychometric rigor (i.e., veridicality) of traditional paper-and-pencil assessments, and verisimilitude approximating real life situations.

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Parsons, T.D. (2011). Neuropsychological Assessment Using Virtual Environments: Enhanced Assessment Technology for Improved Ecological Validity. In: Brahnam, S., Jain, L.C. (eds) Advanced Computational Intelligence Paradigms in Healthcare 6. Virtual Reality in Psychotherapy, Rehabilitation, and Assessment. Studies in Computational Intelligence, vol 337. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17824-5_13

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  • DOI: https://doi.org/10.1007/978-3-642-17824-5_13

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