Neuropsychiatric/behavioral-psychological symptoms of dementia (BPSD) frequently contribute to worse prognosis of patients with neurodegenerative conditions. BPSD are commonly measured via a brief, informant-rated version of the Neuropsychiatric Inventory (NPI), the NPI-Q. Previously (see our other submission to this conference), we established optimal latent structures by comparing different factor models in the literature using confirmatory factor analyses (CFAs). However, questions remain as to why so many different models were found in the literature. One possibility is sampling differences, including different proportions of individuals across cognitive stages (e.g., mild cognitive impairment, moderate dementia) or syndromes (e.g., Alzheimer’s amnestic syndrome, Dementia with Lewy Bodies). We tested this hypothesis by subjecting candidate models to measurement invariance (MI) analyses stratified by cognitive stage and syndrome.

Individuals were included if they had completed an NPI-Q during their first visit at an Alzheimer Disease Research Center reporting to the National Alzheimer Coordinating Center (NACC). This resulted in 20,500 individuals (57% female; 80% White, 13% Black, 8% Hispanic), with a mean age of 71 (SD = 10.41) and 15 average years of education (SD = 3.43). Regarding staging, 75.9% of individuals did not meet criteria for all-cause dementia, whereas 24.1% individuals had all-cause dementia. Regarding syndromes, 35.6% had an Alzheimer’s presentation (“AD-type”) and 5.6% had either a behavioral variant frontotemporal dementia or Lewy-Body dementia presentation (“behavioral-type”). A 3-factor and 4-factor model were subject to MI across these groupings. We conducted MI analyses for equal forms, equal loadings, and equal intercepts using the lavaan R package with a diagonally weighted least squares (DWLS) estimator.

The 3-factor model demonstrated good fit among individuals experiencing (CFI = 0.965, TLI = 0.955) and not experiencing (CFI = 0.984, TLI = 0.979) dementia, as well as among AD-type (CFI = 0.983, TLI = 0.978) presentations, but had borderline poor fit for behavioral-type (CFI = 0.932, TLI = 0.912) presentations. The 4-factor model had better fit among those experiencing (CFI = 0.985, TLI = 0.977) and not experiencing (CFI = 0.995, TLI = 0.992) dementia. Additionally, the 4-factor model demonstrated good of fit for AD-type (CFI = 0.993, TLI = 0.989) and poorer fit for behavioral-type (CFI = 0.949, TLI = 0.922) syndromes. Chi-square differences suggested that equal loading and equal intercept hypotheses should be rejected for both 3- and 4-factor models, for both staging and syndromal groupings. However, relative fit indices suggested that the equal form, equal loading, and equal intercept hypotheses could be adequate for only the 4-factor model.

The variability of factor structures in the BPSD literature appears, at least partially, explained by sampling variability among cognitive stages and dementia syndromes. The best models in the literature appear to have good fit in non-demented individuals and, among those who have dementia, in those with an AD syndrome. Only Sayegh & Knight’s 4-factor model had adequate (albeit, not optimal) fit among those with all-cause dementia and, more specifically, among those with a behavioral-type dementia syndrome. These findings inform BPSD theory and practical implementation of NPI-Q subscales.

Visuospatial skills are frequently assessed with drawing tests. Research has suggested that the use of drawing tasks in low educated groups may lack the ability to discriminate healthy individuals from clinical populations. The aims of this study were to investigate the validity of visuoconstructional tests in a sample of older Greek Australian immigrants and compare their performances to a matched sample of patients with Alzheimer’s disease (AD).

We assessed visuoconstructional performances in a sample of 90 healthy older Greek Australians, with a primary school level of education, and compared performances to a demographically matched sample of 20 Greek Australians with a diagnosis of AD on four visuoconstructional drawing tests: Greek cross, four-pointed star, intersecting pentagons, and the Necker Cube.

While healthy participants tended to outperform the AD group on most copy tasks, high fail rates within the healthy sample were observed for the intersecting pentagons and Necker cube (78% and 73% fail rates respectively) when using established clinical cutoff scores. High rates of curved angle, omission, distorted relation between elements, spatial disorganization and three-dimensional design errors were found across the four-pointed star, intersecting pentagons, and the Necker cube in both healthy participants and those with AD. Exploratory receiver operating characteristic curve analysis revealed that, with perhaps the exception of the Greek cross, meaningful sensitivity and specificity could not be reached for the four-pointed star, intersecting pentagons, and Necker cube.

Cognitively healthy immigrants with low education appear to be at a disadvantage when completing visuoconstructional drawing tests, as their performance may be misinterpreted as indicating cognitive impairment. Future research is needed to identify alternative approaches to assess visuoconstructional ability in low education older cohorts.

Population studies have shown that Black individuals are at higher risk for MCI and dementia than White individuals but are more likely to be underdiagnosed or misdiagnosed. Although multiple contributory factors have been identified in relation to neurocognitive diagnostic disparities among persons of color, few studies have investigated race-associated differences in MCI and dementia classification across diagnostic methods. The current study examined the agreement of cognitive classification made via semi-structured interview and neuropsychological assessment.

Only participants assigned normal cognitive status or cognitive impairment with presumed Alzheimer’s etiology were included in the study. Baseline visit data in the National Alzheimer’s Coordinating Center (NACC) dataset was collected to compare correspondence of cognitive classification (normal cognition, MCI, dementia) via semi-structured interview (Clinical Dementia Rating; CDR) with formal NACC diagnostic determination. NACC diagnostic determination was further separated by single clinician and consensus diagnostic methods. Inter-rater agreement was evaluated using chi-squared tests, and respective analyses were stratified for race (Black vs White), ethnicity (Hispanic vs Non-Hispanic), and education (<12 years vs. >12 years).

The sample size included 4,739 Black and 26,393 White participants across 43 Alzheimer’s Disease Research Centers (ADRCs). Inter-rater analyses between CDR (semi-structured interview) versus single-clinician and formal consensus NACC diagnostic methods showed strong (all (pc>.70) consistency in cognitive diagnoses overall, irrespective of race, ethnicity, and education. The percentage of agreement between diagnostic methods was nearly 100% for those categorized as cognitively normal or with dementia. However, the agreement for MCI was considerably lower (ranging from 28-74%) and revealed a disparity in diagnostic method between Black and White individuals. White individuals diagnosed with MCI via CDR (CDR total =0.5) were more likely to be labeled as having dementia regardless of NACC diagnostic method. However, Black individuals diagnosed with MCI via CDR were equally likely to be diagnosed as cognitively normal or with dementia via the formal consensus method.

Irrespective of race and other demographic variables, diagnostic methods had high agreement for groups labeled with normal cognition and dementia. Agreement was consistently lower for the group labeled with MCI, with Black individuals having greater variability in diagnostic differentials when diagnosed via formal consensus method. The results of the study suggest that neuropsychological assessment continues to be an integral component of diagnosing individuals with MCI, reducing possible sources of bias.

Socioeconomic disadvantage is a chronic stressor associated with several biological markers of health (e.g., inflammation) as well as early-onset cognitive aging. Studies examining socioeconomic status (SES) and its link with health outcomes exhibit no uniformity in the way in which SES is measured and defined. Also, studies have found that subjective socioeconomic status (SSES), defined by a subjective SES scale, was more consistently and strongly related to psychological functioning and health-related outcomes than objective socioeconomic status (OSES), defined by a composite score of education, household income, and occupation. The goal of the current study was to assess whether SSES mediates the relationship between OSES and neuropsychological test performance similarly across racial and ethnic groups.

Participants were 1,912 middle-aged older adults (13% non-Hispanic white, 17% non-Hispanic Black, 69% Hispanic/Latinx) from the Offspring study. Participants are the adult children of participants in the Washington Heights Inwood Columbia Aging Project, a community-based cohort study of aging and dementia representing the ethnic/racial diversity of upper Manhattan. Participants on average were 56.5 years of age and 67% were women. Measures of verbal learning and memory (SRT immediate and delayed recall), verbal fluency (animal and letter fluency), and attention/working memory (digit span forward and backward) were administered. OSES was characterized by years of formal education completed. SSES was measured by the MacArthur Scale of Subjective Social Status. The scale measures perceptions of one’s social standing relative to others. We conducted separate stratified mediation analyses for each neuropsychological outcome across each racial and ethnic group. All models were adjusted for age.

Participants with higher OSES demonstrated higher neuropsychological test scores (effect size associations ranged from .29 to .45) and reported higher SSES (b=.109 95% CI: .08, .14). Lower SSES was associated with lower neuropsychological test scores (effect-size range .06 to .13). In stratified analyses, the relationship between OSES and SSES was strongest for White participants (b=.13 [.01, .24]) compared with Latinx (b=.06 [.02, .11]) and Black (b=.06 [-.03, .16]) participants. Associations between SSES and neuropsychological outcomes were only reliable for White participants on SRT Immediate and Delayed Recall and Animal Fluency and for Black participants on Digit Span Forward. In mediation analyses, SSES mediated the relationship between OSES and Immediate Recall (indirect effect b=.18 [.001, .45]; 39% mediated), Delayed Recall (indirect effect b=.05 [.004, .09]; 44% mediated), and Animal Fluency (indirect effect b=.09 [.01, .20]; 22% mediated) for White participants. There was no evidence of mediation in Black or Latinx participants.

The relationship between OSES and SSES was strongest for White participants compared to Black and Latinx participants. Even though perception of social status predicted lower cognitive test scores among Black and Latinx adults, it is only a part of the indirect pathway linking OSES to cognitive function among White adults. It is likely that mechanisms related to tangible resources that benefit health (as opposed to perceived inequity) are in the pathway linking education to cognition among Black and Latinx, and thus intervening on systems of inequality throughout the life course has the most promise for improving brain health in those communities.

Subjective cognitive decline (SCD) is increasingly being considered one of the earliest clinical signs of Alzheimer’s Disease (AD). Certain characteristics of early life, such as childhood socioeconomic status (SES), have been associated with late life cognitive performance. Here we examine the extent to which childhood SES predicts SCD.

The current sample consisted of 55 healthy older adults (17 Male, 39 Female), aged 51 to 88 (M=73.14, SD=6.23) with a mean education of 16 years (SD=2.1 years). 21.5% of the sample self-reported as race/ethnic minorities (e.g., Hispanic or Non-Hispanic African American, Asian, Other.) Participants completed a 20-item SCD questionnaire assessing perceived cognitive difficulties in comparison to same aged peers, and objective cognitive testing. Childhood SES was assessed using two items. The first item asked the participant to utilize a modified MacArthur Scale of Subjective Social Status to identify where on the ladder they felt their family would have been placed during their childhood relative to others in the United States. This ladder has 10 rungs, with rung 1 associated with being the “worst off” and rung 10 associated with being the “best off”. The second item asked the participant to rate their family’s difficulty paying bills during their childhood. Linear regression models were used to examine the extent to which childhood SES predicted SCD. Models were adjusted for education, referral source (clinical versus non-clinical), and objective cognitive testing. Age and gender were not associated with childhood SES or SCD, and as a result were not adjusted for in these models.

On the MacArthur Scale, 20% of participants placed their family at rung 5, 38.2% placed their families at a rung lower than 5, and 41.8% placed their family at a rung higher than 5. When rating the difficulty their family faced paying bills, 3.6% of participants responded “extremely difficult”, 16.4% responded “very difficult”, 20% responded “somewhat difficult”, 23.6% responded “slightly difficult”, and 36.4% responded “not difficult”. Linear regression models revealed a significant effect of childhood SES on SCD (β=-.29, p=.045, SE=.90; β=-.35, p=.015, SE=1.68).

Childhood SES, measured by subjective social status and family’s difficulty paying the bills in childhood, was predictive of SCD in this study of cognitively healthy adults. This result highlights another characteristic of early life that may shape the path of cognitive aging. The predictive utility of childhood SES for SCD may also provide clinicians and researchers with further insight into the populations that may be more susceptible to experiencing SCD in later life. Future studies should utilize a larger sample size among a population with a greater range of childhood SES, to most accurately capture the effectiveness of childhood SES to predict SCD.

Craft story recall test in the National Alzheimer’s Coordinating Center Uniformed Data Set 3 (NACC UDS3) neuropsychological battery has been employed to assess verbal memory and assist clinical diagnosis of mild cognitive impairment (MCI) and dementia. While a Chinese version of the test was adapted, no existing literature has examined the diagnostic validity of the test in Chinese Americans. This study aimed to evaluate the predictive validity of both immediate and delayed recall.

The Chinese version of Craft Story was administered in to 78 Chinese participants per their language preference of Mandarin or Cantonese. Outcome measures were verbatim and paraphrase recall of the story immediately and after a 20-minute delay. A multiple linear regression was performed to investigate the association of each outcome measure with age, education, gender, age when moved to the U.S., years in the U.S., and testing language. To assess its diagnostic value, cutoff standard deviation scores of -1.5 and -2.0 from the mean of the clinically cognitive normal participants were generated for MCI and dementia diagnoses, respectively. Due to the small sample size, a normative group fitting the mean age (73 years), years of education (12 years), and the majority gender (female) of the current sample were used to identify standard cut points. A receiver-operating characteristic analysis was used to compare predicted diagnosis with actual clinical diagnosis obtained through patients’ overall performance and a consensus meeting by licensed clinicians.

Younger age (p < 0.05) and being tested in Mandarin (p < .01) were positively associated with immediate and delayed recall. Strong positive correlations between each measure were observed (all p < .001), indicating a significant relationship between information encoded and retained. Among all the participants, 15 (19.2%) were diagnosed with MCI and 22 (28.2%) with dementia. For MCI diagnosis, the standard cutoff scores demonstrated adequate sensitivity (verbatim=82%, paraphrase=91%) but low specificity (verbatim=44%, paraphrase=67%) in all outcome measures. For dementia diagnosis, delayed recall showed strong sensitivity (100%) and adequate specificity (75%) in both verbatim and paraphrasing scores. Immediate recall paraphrase (sensitivity = 95%, specificity = 50%) showed a better sensitivity but lower specificity than verbatim scoring (sensitivity = 86%, specificity = 58%). The accuracy was higher in delayed recall for both MCI and dementia diagnosis. A preliminary analysis on the optimal cut points indicated higher cutoff scores to distinguish MCI and dementia from clinically cognitive normal population, and from each other (e.g., the optimal cut point for delayed verbatim in distinguishing MCI from normal is 8.0 (sensitivity=89%, specificity=73%, AUC=84.3%)).

Consistent with previous literature, Craft Story delayed recall served as a more accurate diagnostic tool for both MCI and dementia compared to immediate recall in older Chinese Americans. However, poor specificity might increase the chance of following false positive subjects in clinical trials. In addition, testing language appeared to impact performance on verbal memory recall of constructed information. Thus, future studies should focus on developing normative scores that address both the overall cultural differences of Chinese Americans and the heterogeneity within this population.

Learning curve patterns on list-learning tasks can help clinicians determine the nature of memory difficulties, as an “impaired” score may actually reflect attention and/or executive difficulties rather than a true memory impairment. Though such pattern analysis is often qualitative, there are quantitative methods to assess these concepts that have been generally underutilized. This study aimed to develop a model that decomposes learning over repeated trials into separate cognitive processes and then include other testing data to predict performance at each trial as a function of general cognitive functioning.

Data for CVLT-II learning trials were obtained from an outpatient neuropsychology service within an academic medical center referred for clinical reasons. Participants with a cognitive diagnosis of non-demented (ND) or probable Alzheimer’s disease (AD) were included. The final sample consisted of 323 ND [Mage = 58.6 (14.8); Medu = 15.4 (2.7); 55.7% female] and 915 AD [Mage = 72.6 (9.0); Medu = 14.2 (3.1); 60.1% female cases. A Bayesian non-linear beta-binomial multilevel model was used, which uses three parameters to predict CVLT-II recall-by-trial: verbal attention span (VAS), maximal learning potential (MLP), and learning rate (LR). Briefly, VAS predicts expected first trial performance while MLP, conversely, predicts the expected best performance as trials are repeated, and LR weights the influence of VAS versus MLR over repeated trials. Predictors of these parameters included age, education, sex, race, and clinical diagnosis, in addition to raw scores on Trail Making Test Parts A and B, phonemic (FAS) fluency, animal fluency, Boston Naming Test, Wisconsin Card Sorting Test (WCST) Categories Completed, and then age-adjusted scaled scores from WAIS-IV Digit Span, Block Design, Vocabulary, and Coding. Random intercepts were included for each parameter and extracted for comparison of residual differences by diagnosis.

The model explained 84% of the variance in CVLT-II raw scores. VAS reduced with age and time-to-complete Trails B but improved with both verbal fluencies and confrontation naming. MLP increased as a function of WAIS Digit Span, animal fluency, confrontation naming, and WCST categories completed. Finally, LR was greater for females and WAIS-IV Coding and Vocabulary performances but reduced with age. Participants with AD had lower estimates of all three parameters: Cohen’s d = 2.49 (VAS) - 3.48 (LR), though including demographic and neuropsychological tests attenuated differences, Cohen’s d = 0.34 (LR) - 0.95 (MLP).

The resulting model highlights how non-memory neuropsychological deficits affect list-learning test performance. At the same time, the model demonstrated that memory patterns on the CVLT-II can still be identified beyond other confounding deficits since having AD affected all parameters independent of other cognitive impairments. The modeling approach can generate conditional learning curves for individual patient data, and when multiple diagnoses are included in the model, a person-fit statistic can be computed to return the mostly likely diagnosis for an individual. The model can also be used in research to quantify or adjust for the effect of other patient data (e.g., neuroimaging, biomarkers, medications).

There is a dearth of an appropriate standardized tool to assess neuropsychological functions in rural population, which has low literacy rates, are culturally diverse, and have limited access to healthcare resources. The NIREH Neuropsychological Battery for Rural Population (NINB-RP) is a relatively brief and easy-to-administer battery comprising multiple tests that are modified or adopted as per rural community settings to evaluate verbal learning, fine coordination, attention efficiency, executive task, concentration, and visual attention, mental flexibility, and motor coordination in rural populations. The present study aimed to examine the clinical validity and establish cut-off scores for impairment of neuropsychological functions for different age, gender, and education levels of NINB-RP in a rural community in central India.

This was a prospective cross-sectional study conducted in participants aged > 18 years (n=2952, M: F=1407:1545) recruited through a stratified sampling technique from 23 randomly selected villages from central India. The data of nine neuropsychological tests [(Finger and Tweezer dexterity test (FDT, TDT); Digit Forward and Backward test (DFT, DBT); Serial subtraction test (SST); Trail Making-A and B; Finger Tapping test (FTT); and Letter Digit Substitution test, LDST)] from 215 cognitively impaired and 2737 healthy control subjects were analyzed. The tests were performed in a village school/community hall or an outdoor camp. Independent sample t-test, Chi-square test, and Receiver Operating Characteristic (ROC) curve were used to calculate the area under the curve (AUC), cut-off scores, and sensitivity (ST)/specificity (SP) values for seven conditions, i.e., gender (male vs. female), age groups (up to 49 years and above 50 years); and educational levels (illiterate, intermediate and college). For those variables where ST/SP values were lower than 0.70, a unique cut-off score was calculated for the entire sample, adjusting by age and educational levels.

A significant difference in mean (median) scores between the healthy control and cognitively impaired groups were observed in all tests except Trail Making A and B and LDST. The AUC for most of the tests ranged from 0.70 to 0.81, and the ST/SP values ranged from 69-73% and 65-75%, respectively. The results showed that most tests of NINB-RP reached moderate to good sensitivity and specificity for gender, age and education levels, except for DBT for females, above 50 years, and illiterate and intermediate education groups. FDT for males [AUC: 0.85 (95%CI0.80-0.91], ST/SP=76/82%] and females [(AUC=0.78 (95%CI0.74-0.82), ST/SP=71/70%], TDT for intermediate education group [AUC=0.82 (95%CI0.60-1.00), ST/SP=86/83%] and FTT for less than 49 years age group [AUC=0.75 (95%CI0.67-0.84), ST/SP=71/76%] were the most useful tests to discriminate among healthy control and cognitively impaired rural population.

The present study is an attempt to establish the cut-off scores of a neuropsychological battery for a large rural population in the community setting. The proposed cut-off values might be helpful in clinical assessment in rural areas where clinical neuropsychology services are not readily available. NINB-RP can be a valuable tool for clinical research studies in rural communities. Further studies on similar samples in other countries need to be undertaken.