Validation of HVLT-R, BVMT-R, and RBANS Learning Slope Scores along the Alzheimer’s Continuum

Abstract

Background The learning ratio (LR) is a novel learning slope score that has been developed to reduce the inherent competition between the first trial and subsequent trials in traditional learning slopes. In essence, the LR is the number of items learned after the first trial divided by the number of items yet to be learned. Criterion and convergent validation of this LR score is warranted to understand its sensitivity along the Alzheimer’s disease (AD) continuum. Method The LR metric was calculated for 123 participants from standard measures of memory, including the Hopkins Verbal Learning Test—Revised, Brief Visuospatial Memory Test—Revised, Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) list learning, and RBANS story memory. All participants were categorized as normal cognition, mild cognitive impairment (MCI), or AD. LR performances were compared between groups, among other standard memory measures, and with regards to how well they discriminated cognitively impaired from unimpaired samples—and within diagnostic subgroups. Results Lower LR scores were observed for the MCI and AD groups than the normal cognition group, with the AD group performing worse than the MCI group for several slope calculations. Lower LR scores were also consistently associated with poorer performances on traditional memory measures. LR scores further displayed excellent receiver operator characteristics when differentiating those with and without cognitive impairment—and MCI from normal cognition. Overall, LR scores consistently outperformed traditional learning slope calculations across all analyses. Conclusions This LR score is sensitive to memory dysfunction along the AD continuum, and results offer criterion and convergent validity for use of the LR metric to understand learning capacity.

Performance on the African neuropsychology battery using the learning ratio in a sample of healthy Congolese

“…Although clinical applications of LR within the ANB require further investigation, it is encouraging that prior research in clinical samples using LR methodology in other learning tests has shown that LR differentiates between those with and without neurocognitive impairments (Spencer et al, 2020;Hammers et al, 2021aHammers et al, , 2021b with receiver operating characteristics area under the curve (AUC) in the acceptable to excellent range. Further, LR scores correlate significantly with other neuropsychological tests of memory, Alzheimer's-related biomarkers, hippocampal volume, and genetic risk for Alzheimer's (Hammers et al, 2021b(Hammers et al, , 2021cSpencer et al, 2020). Similarly, we would expect LR scores from the ANB to show similar clinical utility, but additional research is needed.…”

“…Using the RBANS List Learning and Story Memory subtests, Spencer et al (2020) demonstrated psychometric superiority of LR relative to the conventional RLS method. Follow-up investigations comparing LR with RLS suggest LR is more robustly correlated with traditional memory and learning measures, provides superior diagnostic differentiation of clinical groups, and is correlated more strongly with relevant neuroanatomic (i.e., hippocampal volume) and other biomarker data such as ApoE4 status (Hammers et al, 2021a(Hammers et al, , 2021b(Hammers et al, , 2021c. Recent studies have developed LR aggregates by combining learning slope measures (i.e., List Learning and Story Memory on the RBANS), stabilizing resultant metrics.…”

“…Recent studies have developed LR aggregates by combining learning slope measures (i.e., List Learning and Story Memory on the RBANS), stabilizing resultant metrics. In fact, among studies using LR, aggregate scores show more robust psychometric properties relative to subtest specific metrics (Hammers et al, 2021a(Hammers et al, , 2021b(Hammers et al, , 2021cSpencer et al, 2020). Such an aggregated measure was introduced by developers of the WMS-III, but the enterprise was limited by employing RLS.…”

“…That is, many results appearing to pertain to the concept of “learning slope” are contaminated by using RLS. Indeed, RLS-based methods, which only account for improvement past the first learning trial, negatively correlate with first trial scores (Spencer et al, 2020; Hammers et al, 2021c) and are minimally, inconsistently, and often inversely related to advanced age (e.g., see manuals for BVMT-R, CVLT 3, WMS-III). The lack of a clear correlation with age is surprising given that age is an established correlate of brain processes contributing to inefficient learning and memory (e.g., Small et al, 2002).…”

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

“…By eliminating confounds from ceiling effects, the LR may result in stronger associations and predictive ability for clinically relevant outcomes than the RLS, which typically produces weak to null findings when evaluated in the context of demographic characteristics and other performance characteristics. 10 When both scores are directly compared, LR performs equal to or better than RLS for correlations with memory tests, 3,17,18,22,23 diagnostic discrimination, 3,18,23 as well as other known risk factors for AD, including hippocampal volume, AD-specific biomarkers, and APOE4 status. [22][23][24] Thus, the LR score is a relatively new but promising metric that warrants additional examination, particularly in the context of detecting AD using non-invasive assessment methods.…”