ArticleThe Clinical neuropsychologist2022
Demographically-corrected normative data for the RBANS learning ratio in a sample of older adults.
Article in The Clinical neuropsychologist, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Sensitivity of the African neuropsychology battery memory subtests and learning slopes in discriminating APOE 4 and amyloid pathology in adult individuals in the Democratic Republic of Congo.Frontiers in neurology · 2024Article
- Validation of and Demographically Adjusted Normative Data for the Learning Ratio Derived from the RAVLT in Robustly Intact Older Adults.Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists · 2022Article
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3 authors.
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Abstract
backgroundA novel learning slope score - the Learning Ratio (LR) - has recently been developed that appears to be sensitive to memory performance and AD pathology more optimally than traditional learning slope calculations. While promising, this research to date has been both experimental and based on group differences, and therefore does not aid in the interpretation of individual LR performance for either clinical or research settings. The objective of the current study was to develop demographically-corrected normative data on these LR learning slopes on verbal learning measures from the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS).
methodThe current study examined the influence of age and education on LR metrics for the List Learning, Story Memory, and an Aggregated RBANS score in 200 cognitively intact adults aged 65 or older using linear regression.
resultsAge and education correlated with most LR metrics, but no sex differences were observed. Linear regression permitted the prediction of LR values from age and education, which are then compared to observed LR values. The result is demographically-corrected
conclusionsBy comparing observed and predicted LR scores calculated from regression-based prediction equations, this represents the first step towards interpretation of individual performances on this metric for clinical decision making and treatment planning purposes. With future replication in diverse and heterogenous samples, we hope to offer a new clinical tool for the examination of learning slopes in older adults.
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