Advanced neuropsychological diagnostics infrastructure Improving neuropsychology

This dissertation describes the building and testing of the Advanced Neuropsychological Diagnostics Infrastructure (ANDI). ANDI consists of datasets of several research groups are combined into a single database, containing scores on neuropsychological tests from healthy participants. For most popular neuropsychological tests, the quantity, and range of these data surpasses that of traditional normative data, thereby enabling more accurate neuropsychological assessment. Because of the unique structure of the database, it facilitates normative comparison methods that were not feasible before, in particular those in which entire profiles of scores are evaluated. The applicability of the ANDI norms and multivariate normative comparisons was tested with a sample of longitudinal data from patients with Parkinson’s disease as well as a group of non-demented patients from the Amsterdam dementia cohort. This dissertation also looks at possible alternatives for ‘level of education’ as a proxy for premorbid IQ. It is of vital importance that neuropsychologists can compare heir patients to a relevant healthy norm population. This means that we compare to others who are equal in sex, age, and level of education. This promotes more reliable detection of patients who are cognitively abnormal and who require some form of intervention or care. The ANDI database has shown to improve the normative comparisons by providing more representative standards and by enabling an improvement of statistical tests.