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

Michelle Olaithe, Michael Weinborn, Talitha Lowndes, Amanda Ng, Erica Hodgson, Lara Aishling Fine, Denise Parker, Maria Pushpanathan, Donna Bayliss, Michael Anderson, Romola Bucks

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Abstract

Objective
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.

Method
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.

Results
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.

Conclusions
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.
Original languageEnglish
JournalArchives of Clinical Neuropsychology
DOIs
Publication statusPublished - 4 Jan 2019

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Education
Western Australia
Neuropsychological Tests
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Cite this

@article{5bd686f461f84384947ab949f0673b22,
title = "Repeatable Battery for the Assessment of Neuropsychological Status (RBANS): Normative Data for Older Adults",
abstract = "ObjectiveProvide 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.MethodParticipants (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.ResultsDifferences 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.ConclusionsThese 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.",
author = "Michelle Olaithe and Michael Weinborn and Talitha Lowndes and Amanda Ng and Erica Hodgson and Fine, {Lara Aishling} and Denise Parker and Maria Pushpanathan and Donna Bayliss and Michael Anderson and Romola Bucks",
year = "2019",
month = "1",
day = "4",
doi = "10.1093/arclin/acy102",
language = "English",
journal = "Archives of Clinical Neuropsychology",
issn = "0887-6177",
publisher = "OXFORD UNIV PRESS UNITED KINGDOM",

}

Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) : Normative Data for Older Adults. / Olaithe, Michelle; Weinborn, Michael; Lowndes, Talitha; Ng, Amanda; Hodgson, Erica; Fine, Lara Aishling; Parker, Denise; Pushpanathan, Maria; Bayliss, Donna; Anderson, Michael; Bucks, Romola.

In: Archives of Clinical Neuropsychology, 04.01.2019.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Repeatable Battery for the Assessment of Neuropsychological Status (RBANS)

T2 - Normative Data for Older Adults

AU - Olaithe, Michelle

AU - Weinborn, Michael

AU - Lowndes, Talitha

AU - Ng, Amanda

AU - Hodgson, Erica

AU - Fine, Lara Aishling

AU - Parker, Denise

AU - Pushpanathan, Maria

AU - Bayliss, Donna

AU - Anderson, Michael

AU - Bucks, Romola

PY - 2019/1/4

Y1 - 2019/1/4

N2 - ObjectiveProvide 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.MethodParticipants (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.ResultsDifferences 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.ConclusionsThese 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.

AB - ObjectiveProvide 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.MethodParticipants (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.ResultsDifferences 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.ConclusionsThese 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.

U2 - 10.1093/arclin/acy102

DO - 10.1093/arclin/acy102

M3 - Article

JO - Archives of Clinical Neuropsychology

JF - Archives of Clinical Neuropsychology

SN - 0887-6177

ER -