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Abstract INTRODUCTION Recent research has suggested increased sensitivity of Alzheimer's disease (AD)‐negative neuropsychological norms; concurrently, generalized additive models for location, scale, and shape (GAMLSS) have emerged as a promising alternative to traditional norming approaches. Here, we developed amyloid β‐negative (Aβ−) next‐generation norms (NGN) for a comprehensive neuropsychological battery using GAMLSS. METHODS We included N = 987 cognitively normal (CN) individuals from a Spanish multicenter study with extensive neuropsychological data and cerebrospinal fluid AD biomarker assessment. NGN were developed using GAMLSS based on the performance of n = 774 Aβ− CN individuals aged 30–90 years. RESULTS Age‐, education‐, and sex‐adjusted z ‐scores were obtained for 14 measures covering the main cognitive domains (memory, language, attention/executive, and visuospatial functions). A user‐friendly calculator for the z ‐scores was made available in an open‐access ShinyApp to facilitate their application. DISCUSSION NGN may improve the detection of objective cognitive impairment in clinical and research settings. Highlights Brain amyloid β (Aβ) is associated with poorer performance in cognitively normal individuals. We provide GAMLSS‐based Aβ‐negative norms for 14 neuropsychological measures. Age, education, and often sex significantly influence cognitive performance. An online calculator for the demographically adjusted z ‐scores is freely available.
Rubio‐Guerra et al. (Wed,) studied this question.