In this work, we developed normative data for the neuropsychological assessment of independent and cognitively active Spanish older adults over 55 years of age. Method: Regression-based normative data were calculated from a sample of 103 non-depressed independent community-dwelling adults aged 55 or older (67% women). Raw data for Digit Span (DS), Letters and Numbers (LN), the Trail Making Test (TMT), and the Symbol Digit Modalities Test (SDMT) were regressed on age, sex, and education. The model predicting TMT-B scores also included TMT-A scores. Z-scores for the discrepancy between observed and predicted scores were used to identify low scores. The base rate of low scores for SABIEX normative data was compared to the base rate of low scores using published normative data obtained from the general population. Results: The effects of age, sex, and education varied across neuropsychological measures. Although the proportion of low scores was similar between normative datasets, there was no agreement in the identification of cognitively impaired individuals. Conclusions: Normative data obtained from the general population might not be sensitive to identify low scores in cognitively active older adults, incorrectly classifying them as cognitively normal compared to the less-active population. We provide a friendly calculator for use in neuropsychological assessment in cognitively active Spanish people aged 55 or older.
The aim of this work was to develop normative data for neuropsychological tests for the assessment of independent and cognitively active Spanish older adults over 55 years of age. Methods: regression-based normative data were calculated from a sample of 103 nondepressed independent community-dwelling adults aged 55 or older (66% women). The raw data for the Free and Cued Selective Reminding Test (FCSRT), the Rey–Osterrieth Complex Figure Test (ROCF) and the Judgement of Line Orientation Test (JLO) were regressed on age, sex and education. The model predicting the FCSRT delayed-recall (FCSRT-Del) scores also included the FCSRT immediate-recall (FCSRT-Imm) scores. The model predicting the ROCF immediate-recall (ROCF-Imm) scores included the ROCF copy-trial (ROCF-C) scores, and the model predicting the ROCF delayed-recall (ROCF-Del) scores included both the ROCF-C and the ROCF-Imm scores. In order to identify low scores, z-scores were used to determine the discrepancy between the observed and the predicted scores. The base rates of the low scores for both the SABIEX normative data and the published normative data obtained from the general population were compared. Results: the effects of the different sociodemographic variables (age, sex and education) varied throughout the neuropsychological measures. Despite finding similar proportions of low scores between the normative data sets, the agreement was irrelevant or only fair-to-good. Conclusions: the normative data obtained from the general population might not be sensitive enough to identify low scores in cognitively active older adults, incorrectly classifying them as cognitively normal compared to the less active population.
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