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Batista ITP, Queiroz KM, Souza Menezes CED, Peixoto Junior AA, Marçal E. Development of a digital memory and learning test for elderly individuals. BMC Geriatr 2025; 25:3. [PMID: 39754031 PMCID: PMC11697838 DOI: 10.1186/s12877-024-05421-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Accepted: 09/30/2024] [Indexed: 01/07/2025] Open
Abstract
BACKGROUND Population aging and the increase in memory-related diseases have motivated the search for accessible cognitive screening instruments. To develop a digital memory and learning test (DMLT) based on Rey's Auditory Verbal Learning Test (RAVLT) principles to assess cognition in the elderly and identify early cognitive decline. METHODS The research was divided into two phases: developing the digital test and the experimental phase of comparison with a reference test. The test was designed to assess episodic declarative memory through auditory-verbal learning. The experimental procedure involved 18 elderly participants and aimed to compare the performance on the digital test with the traditional RAVLT, followed by an evaluation of participant satisfaction. RESULTS Performance on the digital test and the RAVLT was comparable, with no significant statistical differences, indicating convergent validity between the instruments. Electroencephalographic activity analyses revealed correlations between wave patterns and test performance, suggesting that the digital test may provide additional insights into the neurophysiological processes underlying cognitive performance. Satisfaction assessment revealed high participant acceptance. CONCLUSION The DMLT is a promising tool for cognitive assessment in the elderly, offering an accessible alternative. The high acceptance among elderly participants suggests that the test has potential for clinical and research use, although further studies are needed to validate its effectiveness in broader clinical settings.
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Affiliation(s)
| | | | | | - Arnaldo Aires Peixoto Junior
- Christus University Centre, Fortaleza, Brazil
- Department of Clinical Medicine, Faculty of Medicine, Federal University of Ceará, Fortaleza, Brazil
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Boscarino JJ, Weitzner DS, Bailey EK, Kamper JE, Vanderbleek EN. Utility of learning ratio scores from the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word List Memory Test in distinguishing patterns of cognitive decline in veterans referred for neuropsychological evaluation. Clin Neuropsychol 2024; 38:1967-1979. [PMID: 38494420 DOI: 10.1080/13854046.2024.2330144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 03/07/2024] [Indexed: 03/19/2024]
Abstract
Background: The Learning Ratio (LR) is a novel learning score that has shown improved utility over other learning metrics in detecting Alzheimer's disease (AD) across multiple memory tasks. However, its utility on the Consortium to Establish a Registry for Alzheimer's Disease Word List Memory Test (CERAD WLMT), a widely used list learning measure sensitive to decline in neurodegenerative disease, is unknown. The goal of the current study was to determine the utility of LR on the CERAD WLMT in differentiating between diagnostic (MiNCD vs MaNCD) and etiologic groups (VaD vs AD) in a veteran sample. Methods: Raw learning slope (RLS) and LR scores were examined in 168 veterans diagnosed with major neurocognitive disorder (MaNCD), mild neurocognitive disorder (MiNCD), or normal aging following neuropsychological evaluation. Patients with MaNCD were further classified by suspected etiology (i.e. microvascular disease vs AD). Results: Whereas RLS scores were not significantly different between MiNCD and MaNCD, LR scores were significantly different between all diagnostic groups (p's < .05). Those with AD had lower LR scores and RLS scores compared to those with VaD (p's < .05). LR classification accuracy was acceptable for MiNCD (AUC = .76), excellent for MaNCD (AUC = .86) and VaD (AUC = .81), and outstanding for AD (AUC = .91). Optimal cutoff scores for WLMT LR were derived from Youden's index. Conclusion: Results support the use of LR scores over RLS when interpreting the CERAD WLMT and highlight the clinical utility of LR in differentiating between diagnostic groups and identifying suspected etiology.
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Affiliation(s)
- Joseph J Boscarino
- Mental Health and Behavioral Service, James A. Haley Veterans' Hospital, Tampa, Florida, USA
| | - Daniel S Weitzner
- Mental Health and Behavioral Service, James A. Haley Veterans' Hospital, Tampa, Florida, USA
| | - Erin K Bailey
- Mental Health and Behavioral Service, James A. Haley Veterans' Hospital, Tampa, Florida, USA
- Department of Psychiatry, University of South Florida Morsani College of Medicine, Tampa, Florida, USA
| | - Joel E Kamper
- Mental Health and Behavioral Service, James A. Haley Veterans' Hospital, Tampa, Florida, USA
| | - Emily N Vanderbleek
- Mental Health and Behavioral Service, James A. Haley Veterans' Hospital, Tampa, Florida, USA
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Ikanga J, Patrick SD, Schwinne M, Patel SS, Epenge E, Gikelekele G, Tshengele N, Kavugho I, Mampunza S, Yarasheski KE, Teunissen CE, Stringer A, Levey A, Rojas JC, Chan B, Lario Lago A, Kramer JH, Boxer AL, Jeromin A, Alonso A, Spencer RJ. 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. Front Neurol 2024; 15:1320727. [PMID: 38601333 PMCID: PMC11004441 DOI: 10.3389/fneur.2024.1320727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 03/14/2024] [Indexed: 04/12/2024] Open
Abstract
Background The current study examined the sensitivity of two memory subtests and their corresponding learning slope metrics derived from the African Neuropsychology Battery (ANB) to detect amyloid pathology and APOEε4 status in adults from Kinshasa, the Democratic Republic of the Congo. Methods 85 participants were classified for the presence of β-amyloid pathology and based on allelic presence of APOEε4 using Simoa. All participants were screened using CSID and AQ, underwent verbal and visuospatial memory testing from ANB, and provided blood samples for plasma Aβ42, Aβ40, and APOE proteotype. Pearson correlation, linear and logistic regression were conducted to compare amyloid pathology and APOEε4 status with derived learning scores, including initial learning, raw learning score, learning over trials, and learning ratio. Results Our sample included 35 amyloid positive and 44 amyloid negative individuals as well as 42 without and 39 with APOEε4. All ROC AUC ranges for the prediction of amyloid pathology based on learning scores were low, ranging between 0.56-0.70 (95% CI ranging from 0.44-0.82). The sensitivity of all the scores ranged between 54.3-88.6, with some learning metrics demonstrating good sensitivity. Regarding APOEε4 prediction, all AUC values ranged between 0.60-0.69, with all sensitivity measures ranging between 53.8-89.7. There were minimal differences in the AUC values across learning slope metrics, largely due to the lack of ceiling effects in this sample. Discussion This study demonstrates that some ANB memory subtests and learning slope metrics can discriminate those that are normal from those with amyloid pathology and those with and without APOEε4, consistent with findings reported in Western populations.
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Affiliation(s)
- Jean Ikanga
- Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, GA, United States
- Department of Psychiatry, School of Medicine, University of Kinshasa and Catholic University of Congo, Kinshasa, Democratic Republic of Congo
| | - Sarah D. Patrick
- Veteran Affairs Ann Arbor Healthcare System, Ann Arbor, MI, United States
| | - Megan Schwinne
- Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, United States
| | - Saranya Sundaram Patel
- Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, GA, United States
| | - Emmanuel Epenge
- Department of Neurology, University of Kinshasa, Kinshasa, Democratic Republic of Congo
| | - Guy Gikelekele
- Department of Psychiatry, School of Medicine, University of Kinshasa and Catholic University of Congo, Kinshasa, Democratic Republic of Congo
| | - Nathan Tshengele
- Department of Psychiatry, School of Medicine, University of Kinshasa and Catholic University of Congo, Kinshasa, Democratic Republic of Congo
| | | | - Samuel Mampunza
- Department of Psychiatry, School of Medicine, University of Kinshasa and Catholic University of Congo, Kinshasa, Democratic Republic of Congo
| | | | - Charlotte E. Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Neurodegeneration, Amsterdam University Medical Centers, Vrije Universiteit, Amsterdam, Netherlands
| | - Anthony Stringer
- Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, GA, United States
| | - Allan Levey
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA, United States
| | - Julio C. Rojas
- Department of Neurology, University of San Francisco, Memory and Aging Center, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Brandon Chan
- Department of Neurology, University of San Francisco, Memory and Aging Center, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Argentina Lario Lago
- Department of Neurology, University of San Francisco, Memory and Aging Center, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Joel H. Kramer
- Department of Neurology, University of San Francisco, Memory and Aging Center, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Adam L. Boxer
- Department of Neurology, University of San Francisco, Memory and Aging Center, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | | | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Robert J. Spencer
- Veteran Affairs Ann Arbor Healthcare System, Ann Arbor, MI, United States
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Hall MG, Wollman SC, Haines ME, Katschke JL, Boyle MA, Richardson HK, Hammers DB. Clinical validation of an aggregate learning ratio from the neuropsychological assessment battery. APPLIED NEUROPSYCHOLOGY. ADULT 2024:1-10. [PMID: 38527375 DOI: 10.1080/23279095.2024.2329974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
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.
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Affiliation(s)
- Matthew G Hall
- PM&R, The University of Toledo - Health Science Campus, Toledo, OH, USA
| | | | - Mary E Haines
- PM&R, The University of Toledo - Health Science Campus, Toledo, OH, USA
| | | | - Mellisa A Boyle
- PM&R, The University of Toledo - Health Science Campus, Toledo, OH, USA
| | | | - Dustin B Hammers
- Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
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Spencer RJ, Williams TF, Kordovski VM, Patrick SD, Lengu K, Gradwohl BD, Hammers DB. A quantitative review of competing learning slope metrics: effects of age, sex, and clinical diagnosis. J Clin Exp Neuropsychol 2023; 45:744-757. [PMID: 38357915 DOI: 10.1080/13803395.2024.2314741] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 12/27/2023] [Indexed: 02/16/2024]
Abstract
INTRODUCTION In learning and memory tests that involve multiple presentations of the same material, learning slope refers to the degree to which examinees improve performances over successive learning trials. We aimed to quantitatively review the traditional raw learning slope (RLS), and the newly created learning ratio (LR) to understand the effects of demographic variables and clinical diagnoses on learning slope (e.g., limited improvement over multiple trials), and to develop demographically sensitive norms. METHOD A systematic literature search was conducted to evaluate the potential for these aims to be examined across the most popular contemporary multi-trial learning tests. Two databases were searched. Following this, hierarchical linear modeling was used to examine how demographic variables predict learning slope indices. These results were in turn used to contrast the performance of clinical groups with the predicted performance of demographically similar healthy controls. Finally, preliminary normative estimates for learning slope indices were presented. RESULTS A total of 82 studies met criteria for inclusion in this study. However, the Rey Auditory Verbal Learning Test (RAVLT) was the only test to have sufficient trial-level learning and demographic data. Fifty-eight samples from 19 studies were quantitatively examined. Hierarchical linear models provided evidence of sex differences and a curvilinear decline in learning slope with age, with strongest and most consistent effects for LR relative to RLS. Regression-based norms for demographically corrected RLS and LR scores for the RAVLT are presented. The effect of clinical diagnoses was consistently stronger for LR, and Alzheimer's disease had the strongest effect, followed by invalid performances, severe traumatic brain injury, and seizures/epilepsy. CONCLUSION Overall, LR enjoys both conceptual and demonstrated psychometric advantages over RLS. Replication of these findings can be completed by reanalyzing existing datasets. Further work may focus on the utility of using LR in diagnosis and prediction of clinical prognosis.
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Affiliation(s)
- Robert J Spencer
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan Health System, Ann Arbor, MI, USA
| | - Trevor F Williams
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - Victoria M Kordovski
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- Department of Physical Medicine and Rehabilitation, SUNY Upstate Medical University, Syracuse, NY, USA
| | - Sarah D Patrick
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Ketrin Lengu
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- Department of Physical Medicine and Rehabilitation, The MetroHealth System, Cleveland, OH, USA
| | - Brian D Gradwohl
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- Trinity Health Hauenstein Neurosciences, Trinity Health, Muskegon, MI, USA
| | - Dustin B Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
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Hammers DB, Pentchev JV, Kim HJ, Spencer RJ, Apostolova LG. The relationship between learning slopes and Alzheimer's Disease biomarkers in cognitively unimpaired participants with and without subjective memory concerns. J Clin Exp Neuropsychol 2023; 45:727-743. [PMID: 37676258 PMCID: PMC10916703 DOI: 10.1080/13803395.2023.2254444] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 08/29/2023] [Indexed: 09/08/2023]
Abstract
OBJECTIVE Learning slopes represent serial acquisition of information during list-learning tasks. Although several calculations for learning slopes exist, the Learning Ratio (LR) has recently demonstrated the highest sensitivity toward changes in cognition and Alzheimer's disease (AD) biomarkers. However, investigation of learning slopes in cognitively unimpaired individuals with subjective memory concerns (SMC) has been limited. The current study examines the association of learning slopes to SMC, and the role of SMC in the relationship between learning slopes and AD biomarkers in cognitively unimpaired individuals. METHOD Data from 950 cognitively unimpaired participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 89) were used to calculate learning slope metrics. Learning slopes among those with and without SMC were compared with demographic correction, and the relationships of learning slopes with AD biomarkers of bilateral hippocampal volume and β-amyloid pathology were determined. RESULTS Learning slopes were consistently predictive of hippocampal atrophy and β-amyloid deposition. Results were heightened for LR relative to the other learning slopes. Additionally, interaction analyses revealed different associations between learning slopes and hippocampal volume as a function of SMC status. CONCLUSIONS Learning slopes appear to be sensitive to SMC and AD biomarkers, with SMC status influencing the relationship in cognitively unimpaired participants. These findings advance our knowledge of SMC, and suggest that LR - in particular - can be an important tool for the detection of AD pathology in both SMC and in AD clinical trials.
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Affiliation(s)
- Dustin B. Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Julian V. Pentchev
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
- Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, South Korea
| | - Robert J. Spencer
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor MI, USA, 48105
- Michigan Medicine, Department of Psychiatry, Neuropsychology Section, Ann Arbor MI, USA, 48105
| | - Liana G. Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA, 46202
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA, 46202
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Hammers DB, Kostadinova RV, Spencer RJ, Ikanga JN, Unverzagt FW, Risacher SL, Apostolova LG. Sensitivity of memory subtests and learning slopes from the ADAS-Cog to distinguish along the continuum of the NIA-AA Research Framework for Alzheimer's Disease. NEUROPSYCHOLOGY, DEVELOPMENT, AND COGNITION. SECTION B, AGING, NEUROPSYCHOLOGY AND COGNITION 2023; 30:866-884. [PMID: 36074015 PMCID: PMC9992455 DOI: 10.1080/13825585.2022.2120957] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 08/30/2022] [Indexed: 10/14/2022]
Abstract
Despite extensive use of the Alzheimer's Disease (AD) Assessment Scale - Cognitive Subscale (ADAS-Cog) in AD research, exploration of memory subtests or process scores from the measure has been limited. The current study sought to establish validity for the ADAS-Cog Word Recall Immediate and Delayed Memory subtests and learning slope scores by showing that they are sensitive to AD biomarker status. Word Recall subtest and learning slope scores were calculated for 441 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90). All participants were categorized using the NIA-AA Research Framework - based on PET-imaging of β-amyloid (A) and tau (T) deposition - as Normal AD Biomarkers (A-T-), Alzheimer's Pathologic Change (A + T-), or Alzheimer's disease (A + T+). Memory subtest and learning slope performances were compared between biomarker status groups, and with regard to how well they discriminated samples with (A + T+) and without (A-T-) biomarkers. Lower Word Recall memory subtest scores - and scores for a particular learning slope calculation, the Learning Ratio - were observed for the AD (A + T+) group than the other biomarker groups. Memory subtest and Learning Ratio scores further displayed fair to good receiver operator characteristics when differentiating those with and without AD biomarkers. When comparing across learning slopes, the Learning Ratio metric consistently outperformed others. ADAS-Cog memory subtests and the Learning Ratio score are sensitive to AD biomarker status along the continuum of the NIA-AA Research Framework, and the results offer criterion validity for use of these subtests and process scores as unique markers of memory capacity.
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Affiliation(s)
- Dustin B. Hammers
- Indiana University School of Medicine, Department of Neurology, Indianapolis, IN, USA
| | | | - Robert J. Spencer
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor MI, USA
- Michigan Medicine, Department of Psychiatry, Neuropsychology Section, Ann Arbor MI, USA
| | - Jean N. Ikanga
- Emory University, School of Medicine, Department of Rehabilitation Medicine, GA, USA
- University of Kinshasa, Department of Psychiatry, Democratic Republic of Congo (DRC)
| | | | - Shannon L. Risacher
- Indiana University School of Medicine, Department of Radiology, Indianapolis, IN, USA
| | - Liana G. Apostolova
- Indiana University School of Medicine, Department of Neurology, Indianapolis, IN, USA
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Hall MG, Wollman SC, Haines ME, Boyle MA, Richardson HK, Hammers DB. Novel learning ratio from the NAB list learning test distinguishes between clinical groups: clinical validation and sex-related differences. J Clin Exp Neuropsychol 2023; 45:715-726. [PMID: 37477412 DOI: 10.1080/13803395.2023.2236772] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 07/09/2023] [Indexed: 07/22/2023]
Abstract
List-learning tasks provide a wealth of information about an individual's cognitive abilities: attention, encoding, storage, retrieval, recognition. A more recently developed metric, the Learning Ratio (LR), supplements information about cognitive ability and can assist the clinician in determining whether an individual has cognitive impairment. The LR is calculated by taking the difference between the individuals' raw score on the first learning trial and their raw score on the last learning trial, which is then divided by the number of words left to be learned after the first learning trial. A LR derived from the list-learning task from the Neuropsychological Assessment Battery (NAB) was evaluated to determine ability to distinguish those with normal cognition from those with mild cognitive impairment (MCI) and dementia. Results from the present study indicate the NAB LR is able to distinguish between clinical groups; recommended cutoffs for the NAB LR scores are provided. We also found a significant female sex-advantage for the NAB LR in those with normal memory ability and demonstrated the female sex advantage decreased with increasing memory impairment. Taken together, the NAB LR may assist clinicians in making an accurate and early diagnosis and may be helpful for tracking learning and functioning across multiple assessments. .
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Affiliation(s)
- Matthew G Hall
- University of Toledo Medical Center Rehabilitation Services, Toledo, Ohio, USA
| | | | - Mary E Haines
- University of Toledo Medical Center Rehabilitation Services, Toledo, Ohio, USA
| | - Mellisa A Boyle
- University of Toledo Medical Center Rehabilitation Services, Toledo, Ohio, USA
| | | | - Dustin B Hammers
- Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA
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Hammers DB, Spencer RJ, Apostolova LG. Validation of and Demographically Adjusted Normative Data for the Learning Ratio Derived from the RAVLT in Robustly Intact Older Adults. Arch Clin Neuropsychol 2022; 37:981-993. [PMID: 35175287 PMCID: PMC9618160 DOI: 10.1093/arclin/acac002] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/04/2022] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The learning ratio (LR) is a novel learning slope score that was developed to identify learning more accurately by considering the proportion of information learned after the first trial of a multi-trial learning task. Specifically, LR is the number of items learned after trial one divided by the number of items yet to be learned. Although research on LR has been promising, convergent validation, clinical characterization, and demographic norming of this LR metric are warranted to understand its clinical utility when derived from the Rey Auditory Verbal Learning Test (RAVLT). METHOD Data from 674 robustly cognitively intact older participants from the Alzheimer's Disease Neuroimaging Initiative (aged 54- 89) were used to calculate the LR metric. Comparison of LR's relationship with standard memory measures was undertaken relative to other traditional learning slope metrics. In addition, retest reliability at 6, 12, and 24 months was examined, and demographically adjusted normative comparisons were developed. RESULTS Lower LR scores were associated with poorer performances on memory measures, and LR scores outperformed traditional learning slope calculations across all analyses. Retest reliability exceeded acceptability thresholds across time, and demographically adjusted normative equations suggested better performance for cognitively intact participants than those with mild cognitive impairment. CONCLUSIONS These results suggest that this LR score possesses sound retest reliability and can better reflect learning capacity than traditional learning slope calculations. With the added development and validation of regression-based normative comparisons, these findings support the use of the RAVLT LR as a clinical tool to inform clinical decision-making and treatment.
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Affiliation(s)
- Dustin B Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Robert J Spencer
- Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor MI, USA
- Department of Psychiatry, Michigan Medicine, Neuropsychology Section, Ann Arbor MI, USA
| | - Liana G Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
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