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The Response Bias Scale (RBS) is a measure of protocol validity that is composed of items from the Minnesota Multiphasic Personality Inventory − 2. The RBS has been successfully cross-validated as a whole, but the composition of the scale has not been reexamined until recently when three types of items were identified. In this study we sought to examine the reliability of the scale as a whole, as well as the items that are (a) empirically supported and conceptually similar (ES/CS), (b) empirically supported but not conceptually similar (ES/NS), and (c) not empirically supported (NES). Participants included 56 veterans undergoing neuropsychological evaluation for suspected traumatic brain injury. Results generally replicated Ratcliffe et al. finding that removing key NES items improved the internal consistency of the RBS from 0.706 to 0.747. Examined separately, ES/CS and ES/NS had internal consistencies of 0.629 and 0.605, respectively. One of the nine NES items had strong internal consistency, but none of the remaining eight had corrected item-total correlations above 0.194. NES items had an internal consistency of 0.177. Although the RBS is well-validated in detecting non-credible cognitive presentations, it may prove even more valuable after further item refinement whereby items detracting from its reliability and validity are excised. [ABSTRACT FROM AUTHOR]

The Response Bias Scale (RBS) was developed to predict non-credible cognitive presentations among disability claimants without head injury. Developers used empirical keying, which is independent of apparent content, to select items from the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) item pool that distinguished between individuals passing or failing performance validity tests (PVTs). No study has examined which of these items would have psychometric value when used in clinical neuropsychological evaluations. This study reexamined items comprising RBS with reference to manifest item content, internal consistency, PVTs, and a symptom validity test (SVT) in a sample of 173 predominately White male veterans (MAGE = 50.70, MEDU = 13.73) in a VA outpatient neuropsychology clinic. Participants completed the MMPI-2 Restructured Form (MMPI-2-RF), PVTs, and an SVT. The 28-item RBS appears to contain three types of items: those that manifestly address cognitive functioning, those that are supported but do not appear to address cognitive functioning, and nine items that were unrelated to cognition and not statistically supported. The 19 empirically supported items, or RBS-19, predicted PVT and SVT failures marginally better than the RBS. Both the RBS and RBS-19 had stronger relationships with SVTs relative to PVTs. Although the removal of the nine problematic items improved the diagnostic accuracy of the scale, it still did not reach the level that is generally considered to be clinically optimal. The RBS-19 offers a measure with improved internal consistency and predictive validity compared to the RBS and warrants additional research. [ABSTRACT FROM AUTHOR]

Objective The Montreal Cognitive Assessment (MoCA) is among the most frequently administered cognitive screening tests, yet demographically diverse normative data are needed for repeated administrations. Method Data were obtained from 18,410 participants using the National Alzheimer's Coordinating Center Uniform Data Set. We developed regression-based norms using Tobit regression to account for ceiling effects, explored test–retest reliability of total scores and by domain stratified by age and diagnosis with Cronbach's alpha, and reported the cumulative change frequencies for individuals with serial MoCA administrations to gage expected change. Results Strong ceiling effects and negative skew were observed at the total score, domain, and item levels for the cognitively normal group, and performances became more normally distributed as the degree of cognitive impairment increased. In regression models, years of education was associated with higher MoCA scores, whereas older age, male sex, Black and American Indian or Alaska Native race, and Hispanic ethnicity were associated with lower predicted scores. Temporal stability was adequate and good at the total score level for the cognitively normal and cognitive disorders groups, respectively, but fell short of reliability standards at the domain level. Conclusions MoCA total scores are adequately reproducible among those with cognitive diagnoses, but domain scores are unstable. Robust regression-based norms should be used to adjust for demographic performance differences, and the limited reliability, along with the ceiling effects and negative skew, should be considered when interpreting MoCA scores. [ABSTRACT FROM AUTHOR]

The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) is frequently used as a cognitive screening measure or as part of a comprehensive neuropsychological battery. Augmenting the current memory subtests of the RBANS to reflect clinically meaningful distinctions in memory performance may improve its clinical utility, allowing users to generate additional hypotheses and refine clinical interpretations. We pilot four supplementary memory measures to use with the RBANS, adapted from paradigms commonly used by other neuropsychological tests. We also provide several new theoretically derived memory indices to supplement the standard Delayed Memory Index. The new subtests correlated significantly with the standard memory measures, and the new indices demonstrated good reliability and diagnostic accuracy. This study provides preliminary support for supplementing the RBANS to allow for more nuanced interpretations of memory performance. [ABSTRACT FROM AUTHOR]

Background: Factors predicting the growth or rupture of unruptured intracranial aneurysms (UIAs) remain under debate. Increased availability of neuro-imaging has led to increasing incidental findings, therefore understanding the natural history is vital to make appropriate management and follow-up decisions. We analysed a large dataset of UIAs to better identify patients at increased risk, therefore requiring enhanced monitoring and/or prophylactic intervention. Methods: Electronic patient records were reviewed from consecutive patients regarding the following data: baseline demographics; past medical and smoking history; indication for imaging detecting the UIA(s); size, location and morphology of UIA(s), duration of imaging follow-up, detection of growth and rupture. Logistic regression was used to identify risk factors for UIA growth or rupture. Subgroup analysis was performed for 'small' aneurysms (<7mm). Results: 445 UIAs in 274 patients were analysed. Total imaging follow-up was 2268 aneurysm-years (median 3.8 years/UIA). 27 UIAs grew (1.2% annually), and 15 ruptured (0.46%). 70.1% of UIAs were detected incidentally. Mean aneurysm diameter was 4.1mm. Results: Logistic regression identified age < 50, autosomal dominant polycystic kidney disease (ADPKD), hypertension and diameter > 7mm as significant risk factors for growth/rupture. Additionally, previous smoking compared to current smoking was a protective factor against growth or rupture, but no significant difference was seen when comparing current- with non-smokers. Small aneurysm subgroup analysis identified diameter > 5mm, age < 50, ADPKD, and ongoing smoking as risk factors. No significant difference was observed in risk between those with and without previous SAH. Conclusions: This study underlines the need for imaging surveillance of even small UIAs. Smoking is a modifiable risk factor for growth/rupture of pre-existing aneurysms, while ADPKD is a particularly strong risk factor. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was developed to briefly measure a broad range of cognitive abilities, but it initially lacked a scale to evaluate executive functioning. Robert Spencer and colleagues recently created an Executive Errors scale (RBANS-EE) that quantified executive functioning (EF) errors committed during four RBANS subtests: List Learning, Semantic Fluency, Coding, and List Recall. In the present paper we cross-validated the RBANS-EE with a sample of 234 U.S. military veterans (M AGE = 67.2, SD = 11.5 years; M EDUCATION = 13.3, SD = 2.4 years) who completed the RBANS and various EF criterion measures as part of neuropsychological assessments they underwent during their clinical care. We found the RBANS-EE to be significantly correlated with most of the criterion EF measures. The RBANS-EE scale demonstrated modest ability to classify EF impairment at mild and severe levels; and, similarly, the RBANS-EE was modestly capable of accurately classifying those veteran respondents who were determined to have or to not have a neurocognitive disorder. Overall, the RBANS-EE can be quickly calculated, adds no administration time to an RBANS assessment, and yields useful scores to screen for EF dysfunction without replacing standalone EF tests. [ABSTRACT FROM AUTHOR]

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. 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. 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. 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Compared to its alternatives (e.g., Mini-Mental State Examination [MMSE] and Montreal Cognitive Assessment [MoCA]), little is known about the psychometric properties and factor structure of the Saint Louis University Mental Status (SLUMS) Examination. The purpose of the current study is to describe the internal consistency, factor structure, and temporal stability of the SLUMS, a widely used cognitive screening measure. We examined the SLUMS of 108 mostly White male Veterans seen for home-based primary care services, 101 of whom had complete data and 28 who completed retesting approximately one year later. At time one, Veterans averaged 76.44 (SD = 9.88) years of age and 13.07 (SD = 2.26) years of formal education. Results indicated that the SLUMS had acceptable internal consistency (α =.709) and temporal stability (ρ =.723), with strongest evidence for a one-factor structure. The SLUMS appears to have adequate reliability and clear one-factor structure in this sample. Additional research with diverse samples is needed to characterize the psychometrics of the SLUMS more comprehensively. The SLUMS appears to be an efficient method for approximating global cognitive functioning among medically complex older adults. [ABSTRACT FROM AUTHOR]

Logistic regression (LR) is recognized as a promising method for making decisions about neuropsychological performance validity by integrating information across multiple measures. However, this method has yet to be widely adopted in clinical practice, likely because several open questions remain about its utility relative to simpler methods, its effectiveness across different clinical contexts, and its feasibility at sample sizes common in the field. The current study addresses these questions by assessing classification performance of logistic regression and alternative methods across an array of simulated data sets. We simulated scores of valid and invalid performers on 6 tests designed to mimic the psychometric and distributional properties of real performance validity measures. Out-of-sample predictive performance of LR and a commonly used alternative ("vote counting") was assessed across different base rates, validity measure properties, and sample sizes. LR improved classification accuracy by 2%–12% across simulation conditions, primarily by improving sensitivity. False positives and negatives can be further reduced when LR predictions are interpreted as continuous, rather than binary. LR made robust predictions at sample sizes feasible for neuropsychology research (N = 307) and when as few as 2 tests with good psychometric properties were used. Although training and test data sets of at least several hundred individuals may be required to develop and evaluate LR models for use in clinical practice, LR promises to be an efficient and powerful tool for improving judgements about performance validity. We offer several recommendations for model development and LR interpretation in a clinical setting. [ABSTRACT FROM AUTHOR]

Objective: While Spencer's verbal incidental learning (IL) task—from Vocabulary and Similarities subtests of the WAIS—has been validated relative to traditional memory measures and Alzheimer's disease (AD) pathology, the effectiveness of the particular scoring method used has not been assessed relative to alternative scoring weightings. The purpose of this study was to compare original and alternative scoring methods of this IL task by using an AD biomarker-benchmark to arrive at an optimal approach. Methods: Fifty-five memory-clinic patients aged 59–87 received neuropsychological assessment, measures of IL, and quantitative brain imaging. Partial correlation coefficients with total hippocampal volume—controlling for age, sex, and intracranial volume—were assessed across several IL scoring methods, and partial correlations with measures of memory were examined to evaluate convergent validity. Results: IL scoring methods maximizing the contribution of paired-associate-recall-performance were significantly correlated with both hippocampal volumes and traditional memory measures, whereas discrimination-emphasized scoring methods were not. Conclusions: IL scoring methods emphasizing memory paired-associate recall appeared to be preferable to those emphasizing memory discrimination. Administration of the IL- Similarities subtest alone, without IL- Vocabulary, may strike a balance between strength of relationships with both hippocampal volumes and standard memory measures, while also limiting administration time. [ABSTRACT FROM AUTHOR]

Identify factors influencing service delivery changes during COVID-19 and examine barriers and provider satisfaction with teleneuropsychology (teleNP). Licensed clinical neuropsychologists within the United States recruited via neuropsychology-specific listservs (July–August 2020) to complete an online survey. A total of 261 individuals completed the survey. Most (76%) reported delivering in-person testing in some capacity at the time of our survey. Relatively more private practitioners identified concerns with privacy/confidentiality (45.2% vs. 17.9%; χ2(2) = 6.99, p < 0.05), legal issues (47.6% vs. 17.9%; χ2(2) = 8.06, p < 0.05), and an undesirable precedent for legal/forensic cases (59.5% vs. 15.4%; χ2(2) = 17.54, p < 0.001) compared to hospital or other medical (non-VA) practitioners. Multiple resources informed teleNP protocols, such as organization guidelines (87.6%), literature review (75.9%), webinars (72.4%), and consultation (68%). Several factors influenced test selection, including availability of normative data (70.1%), test familiarity (66.4%), administration time (63.5%), and evidence base (60.6%). Reported barriers to continuing teleNP after COVID-19 included need for improved teleNP norms (85.9%), domain coverage (84.7%), improved patient access to technology (74.1%) and further validation studies (84.1%). TeleNP may not be feasible in all settings and/or referrals. Respondents employed multiple resources in aggregating teleNP protocols and considered several factors when selecting tests. Results highlight the complex and varied decision-making processes utilized by respondents to adapt to service delivery changes. Considering the many benefits of teleNP, future research addressing some of the potentially modifiable factors (e.g., technology access, attitudes regarding teleNP) and significant development needs for teleNP itself (i.e., improved teleNP norms, further validation studies, etc.) is warranted. [ABSTRACT FROM AUTHOR]

A 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). The 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. Age 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 T scores for these LR metrics. By 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. [ABSTRACT FROM AUTHOR]

The Learning Ratio (LR) is a novel learning score examining the proportion of information learned over successive learning trials relative to information available to be learned. Validation is warranted to understand LR's sensitivity to Alzheimer's disease (AD) pathology. One-hundred twenty-three participants across the AD continuum underwent memory assessment, quantitative brain imaging, and genetic analysis. LR scores were calculated from the HVLT-R, BVMT-R, RBANS List Learning, and RBANS Story Memory, and compared to total hippocampal volumes,18F-Flutemetamol composite SUVR uptake, and APOE ε4 status. Lower LR scores were consistently associated with smaller total hippocampal volumes, greater cerebral β-amyloid deposition, and APOE ε4 positivity. This LR score outperformed a traditional learning slope calculation in all analyses. LR is sensitive to AD pathology along the AD continuum – more so than a traditional raw learning score – and reducing the competition between the first trial and subsequent trials can better depict learning capacity. [ABSTRACT FROM AUTHOR]

Initial learning and learning slope are often acknowledged as important qualitative aspects of learning, but the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) contains discrete indices for neither. The traditional method of calculating learning slope involves a difference score between the last trial and first trial, which is referred to as raw learning score (RLS). However, this method does not account for initial Trial One performance and produces a ceiling effect that penalizes efficient first learners. We propose an alternative method of calculating learning score that accounts for initial learning performance, called learning ratio (LR), and we compared the psychometric and predictive properties of these methods. Performances from the List Learning and Story Memory subtests were used to create the indices, and composite learning scores were calculated by combining List Learning and Story Memory. The sample included 289 military veterans (mean age = 65.9 [12.6], education = 13.3 [2.4]), most of whom were male, undergoing neuropsychological assessments that included the RBANS. Results indicated that LR demonstrated superior correlations with criterion measures of memory when compared with RLS, and the LR composite score better discriminated between those with and without a neurocognitive diagnosis, AUC = 0.81 (0.76-0.87), than the RLS composite, AUC = 0.70 (0.64-0.76). We concluded that scores from the RBANS can be computed for initial learning and learning slope and that the LR method of calculating learning is superior to RLS in this older veteran sample. [ABSTRACT FROM AUTHOR]