Repeatable Battery for the Assessment of Neuropsychological Status (RBANS): Normative Data for Older Adults.


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
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

1356-1366

Informations de copyright

© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Auteurs

Michelle Olaithe (M)

School of Psychological Science, University of Western Australia, Perth, Western Australia.

Michael Weinborn (M)

School of Psychological Science, University of Western Australia, Perth, Western Australia.

Talitha Lowndes (T)

School of Psychological Science, University of Western Australia, Perth, Western Australia.

Amanda Ng (A)

School of Psychological Science, University of Western Australia, Perth, Western Australia.

Erica Hodgson (E)

School of Psychological Science, University of Western Australia, Perth, Western Australia.

Lara Fine (L)

School of Psychological Science, University of Western Australia, Perth, Western Australia.

Denise Parker (D)

School of Psychological Science, University of Western Australia, Perth, Western Australia.

Maria Pushpanathan (M)

School of Psychological Science, University of Western Australia, Perth, Western Australia.

Donna Bayliss (D)

School of Psychological Science, University of Western Australia, Perth, Western Australia.

Mike Anderson (M)

School of Psychology and Exercise Science, Murdoch University, Perth, Western Australia.

Romola S Bucks (RS)

School of Psychological Science, University of Western Australia, Perth, Western Australia.

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Classifications MeSH