Repeatable Battery for the Assessment of Neuropsychological Status (RBANS): Normative Data for Older Adults.
Cognitive screening
Neuropsychology
Normative data
Older adults
RBANS
Journal
Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists
ISSN: 1873-5843
Titre abrégé: Arch Clin Neuropsychol
Pays: United States
ID NLM: 9004255
Informations de publication
Date de publication:
27 Nov 2019
27 Nov 2019
Historique:
received:
28
06
2018
revised:
12
02
2018
accepted:
27
12
2018
pubmed:
5
1
2019
medline:
12
3
2020
entrez:
5
1
2019
Statut:
ppublish
Résumé
Provide updated older adult (ages 60+) normative data for the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), Form A, using regression techniques, and corrected for education, age, and gender. Participants (aged 60-93 years; N = 415) were recruited through the Healthy Ageing Research Program (HARP), University of Western Australia, and completed Form A of the RBANS as part of a wider neuropsychological test battery. Regression-based techniques were used to generate normative data rather than means-based methods. This methodology allows for the control of demographic variables using continuous data. To develop norms, the data were assessed for: (1) normality; (2) associations between each subtest score and age, education, and gender; (3) the effect of age, education, and gender on subtest scores; and (4) residual scores which were converted to percentile distributions. Differences were noted between the three samples, some of which were small and may not represent a clinically meaningful difference. Younger age, more years of education, and female gender were associated with better scores on most subtests. Frequency distributions, means, and standard deviations were produced using unstandardized residual scores to remove the effects of age, education, and gender. These normative data expand upon past work by using regression-based techniques to generate norms, presenting percentiles, as well as means and standard deviations, correcting for the effect of gender, and providing a free-to-use Excel macro to calculate percentiles.
Identifiants
pubmed: 30608541
pii: 5272744
doi: 10.1093/arclin/acy102
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1356-1366Informations de copyright
© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.