Clinical validation of an aggregate learning ratio from the neuropsychological assessment battery.
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| Title: | Clinical validation of an aggregate learning ratio from the neuropsychological assessment battery. |
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| Authors: | Hall, Matthew G. (AUTHOR), Wollman, Scott C. (AUTHOR), Haines, Mary E. (AUTHOR), Katschke, Jessica L. (AUTHOR), Boyle, Mellisa A. (AUTHOR), Richardson, Hannah K. (AUTHOR), Hammers, Dustin B. (AUTHOR) |
| Source: | Applied Neuropsychology: Adult. Jan/Feb2026, Vol. 33 Issue 1, p55-64. 10p. |
| Subjects: | Mild cognitive impairment, Dementia, Early medical intervention, Cognitive ability, Memory disorders, Classification of mental disorders, Neuropsychological tests |
| Abstract: | Quantifying learning deficits provides valuable information in identifying and diagnosing mild cognitive impairment and dementia. Previous research has found that a learning ratio (LR) metric, derived from the list learning test from the Neuropsychological Assessment Battery (NAB), was able to distinguish between those with normal cognition versus memory impairment. The current study furthers the NAB LR research by validating a NAB story LR, as well as an aggregate LR. The aggregate LR was created by combining the individual list and story LRs. Participants were classified as those with normal cognition (n = 51), those with MCI (n = 39) and those with dementia (n = 35). Results revealed the story LR was able to accurately distinguish normal controls from those with mild cognitive impairment and those with dementia and offers enhanced discriminability beyond the story immediate recall score (sum of trial 1 and trial 2). Further, the aggregate LR provided superior discriminability beyond the individual list and story LRs and accounted for additional variance in diagnostic group classification. The NAB aggregate LR provides improved sensitivity in detecting declines in impaired learning, which may assist clinicians in making diagnoses earlier in a disease process, benefiting the individual through earlier interventions. [ABSTRACT FROM AUTHOR] |
| Copyright of Applied Neuropsychology: Adult is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | Quantifying learning deficits provides valuable information in identifying and diagnosing mild cognitive impairment and dementia. Previous research has found that a learning ratio (LR) metric, derived from the list learning test from the Neuropsychological Assessment Battery (NAB), was able to distinguish between those with normal cognition versus memory impairment. The current study furthers the NAB LR research by validating a NAB story LR, as well as an aggregate LR. The aggregate LR was created by combining the individual list and story LRs. Participants were classified as those with normal cognition (n = 51), those with MCI (n = 39) and those with dementia (n = 35). Results revealed the story LR was able to accurately distinguish normal controls from those with mild cognitive impairment and those with dementia and offers enhanced discriminability beyond the story immediate recall score (sum of trial 1 and trial 2). Further, the aggregate LR provided superior discriminability beyond the individual list and story LRs and accounted for additional variance in diagnostic group classification. The NAB aggregate LR provides improved sensitivity in detecting declines in impaired learning, which may assist clinicians in making diagnoses earlier in a disease process, benefiting the individual through earlier interventions. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 23279095 |
| DOI: | 10.1080/23279095.2024.2329974 |
