Few to no studies have directly compared the relative classification accuracies of the memory-based (Brief Visuospatial Memory Test-Revised Recognition Discrimination [BVMT-R RD] and Rey Auditory Verbal Learning Test Forced Choice [RAVLT FC]) and non-memory based (Reliable Digit Span [RDS] and Stroop Color and Word Test Word Reading trial [SCWT WR]) embedded performance validity tests (PVTs). This study’s main objective was to evaluate their relative classification accuracies head-to-head, as well as examine how their psychometric properties may vary among subgroups with and without genuine memory impairment.

This cross-sectional study included 293 adult patients who were administered the BVMT-R, WAIS-IV Digit Span, RAVLT and SCWT during outpatient neuropsychological evaluation at a Midwestern academic medical center. The overall sample was 58.0% female, 36.2% non-Hispanic White, 41.3% non-Hispanic Black, 15.7% Hispanic, 4.8% Asian/Pacific Islander, and 2.0% other, with a mean age of 45.7 (SD=15.8) and a mean education of 13.9 years (SD=2.8). Three patients had missing data, resulting in a final sample size of 290. Two hundred thirty-three patients (80%) were classified as having valid neurocognitive performance and 57 (20%) as having invalid neurocognitive performance based on performance across four independent, criterion PVTs (i.e., Test of Malingering Memory Trial 1, Word Choice Test, Dot Counting Test, Medical Symptom Validity Test). Of those with valid neurocognitive performance, 76 (48%) patients were considered as having genuine memory impairment through a memory composite band score (T<37 for (RAVLT Delayed Recall T-score + BVMT-R Delay Recall T-score/2).

The average memory composite band score for valid neurocognitive scores was T = 49.63 as compared to T = 27.57 for genuine memory impairment individuals. Receiver operating characteristic [ROC] curve analyses yielded significant areas under the curve (AUCs=.79-.87) for all four validity indices (p’s < .001). When maintaining acceptable specificity (91%-95%), all validity indices demonstrated acceptable yet varied sensitivities (35%-65%). Among the subgroup with genuine memory impairment, ROC curve analyses yielded significantly lower AUCs (.64-.69) for three validity indices (p’s < .001), except RDS (AUC=.644). At acceptable specificity (88%-93%), they yielded significantly lower sensitivities across indices (19%-39%). In the current sample, RAVLT FC and BVMT-R RD had the largest changes in sensitivities, with 19% and 26% sensitivity/90%-92% specificity at optimal cut-scores of <10 and <2, respectively, for individuals with memory impairment, compared to 65% and 61% sensitivity/94% specificity at optimal cut-scores of <13 and <4, respectively, for those without memory impairment.

Of the four validity scales, memory-based embedded PVTs yielded higher sensitivities while maintaining acceptable specificity compared to non-memory based embedded PVTs. However, they were also susceptible to the greatest declines in sensitivity among the subgroup with genuine memory impairment. As a result, careful consideration should be given to using memory-based embedded PVTs among individuals with clinically significant memory impairment based on other sources of information (e.g., clinical history, behavioral observation).

The Explosive Ordinance Disposal (EOD) community within the US Military is a specialized force in charge of the most fundamental aspects of the military operations in combat which include disarming and safely disposing explosive threats. EOD technicians have provided critical protection for our military and civilians exposed to improvised explosive devices (IEDs), which became the signature threat of both Afghan and Iraq wars. The nature of the job puts EOD technicians at high risk for blast exposures (from training and combat) resulting in traumatic brain injury (TBI) and sub-concussive head impact. Further, this population is exposed to high levels of combat with psychologically traumatic events. Given the groups neurological and psychological risk factors as well as their critical role in combat, we hypothesized that EOD technicians will present with increased psychological and neurobehavioral symptoms as well decreased cognitive functioning compared to other military personnel.

Participants were recruited from a military hospital with at least one diagnosed mild traumatic brain injury (MTBI). Exclusion criteria included TBI greater then mild severity and invalid performance on the Rey-15. Final sample included 10 EOD and 90 other military.

CognCognitive measures included Hopkins Verbal Learning Test-Reviseitive measures included Hopkins Verbal Learning Test-Revised (HVLT-R); DKEFS Color Word Condition 4 Switching (CW4), Trail Making Condition 3 Letter Sequencing (TM3) and Condition 4 Switching (TM4), and Paced Auditory Serial Addition Test (PASAT). Self-report measures included the Neurobehavioral Symptom Inventory (NSI), Key Behaviors Change Inventory (KBCI), Post-Traumatic Stress Disorder Checklist (PCL-M), Patient Health Questionnaire (PHQ), Combat Exposure Scale (CES) and Blast Exposure Threshold Survey (BETS). The Ohio State University Traumatic Brain Injury Identification Method (OSU) assessed TBI history.

EOD were older (EOD M=38.4, SD=4.06; Others M=33.32, SD=8.08; p=0.05), had a higher pre-morbid IQ (EOD M=110.90, SD=7.64; Other M=101.59, SD=10.55; p=0.008), more combat deployments (EOD M=5.5, SD=2.37; Others M=3.55, SD=2.98; p=0.049) and exposure to wartime atrocities (CES, p=0.003). They had greater number of MTBI (OSU EOD M=6.67, SD=3.33; Other M=3.67, SD=2.34; p=0.007), blast related MTBI (OSU-TBI EOD M=2.33, SD=1.63; Other M=0.67, SD=0.91; p<0.001), and exposure to large explosives (BETS p<0.0001). EOD reported better attention skills (KBCI Inattention, p=0.016, d=0.82; Impulsivity p=0.047, d=0.67). There was a trend for EOD to have lower neurobehavioral symptoms (NSI Total, d=0.32), post-traumatic stress (PCL d=0.39), and depression (PHQ d=0.50); however, despite the moderate effect sizes (p’s >0.05). EOD presented with significantly better scores on DKEFS TMT3 (p=0.037, d=0.70), HVLT-R-Total (p=0.001, d=1.10), HVLT-R-Delayed (p=0.03, d=0.74), and attention/executive functioning skills (PASAT p=0.001, d=1.12). DKEFTS CW4 Switching (d=0.51) and TMT4 Switching were approaching significance (d=0.61) with EOD performing better.

As expected, the EOD sample in this study had higher number of combat deployments, greater exposure to combat atrocities (e.g., death), higher levels of exposure to large explosives, as well as a higher number of MTBI. Inconsistent with our hypotheses, despite these psychological and neurological risk factors, EOD performed better on cognitive measures of memory, attention and executive functioning. They also reported less problems with inattention and impulsivity. Results may reflect the impact of psychological and cognitive resiliency.

Research evaluating mindfulness and cognition has produced mixed results. However, variability in mindfulness has not been previously evaluated as a predictor of cognitive ability. This study evaluated the relation between intra-individual variability (IIV) in mindfulness and cognitive performance.

274 university participants (M=19 years old, SD=1.5; 72.6% female, 67.2% White, 25.6% African American, 3.3% Asian American, 1.1% Hispanic American) completed the Five Facet Mindfulness Questionnaire (FFMQ) and the CNS Vital Signs computerized test battery. IIV was computed from the FFMQ facet T-scores. Additionally, high and low cognitive performance groups were formed from the top and bottom 16% of the sample using the neurocognition index (NCI) score from CNS Vital Signs (N=52 high NCI performance and N=46 low NCI performance).

Pearson r correlations were used to evaluate the relation between mindfulness IIV and CNS Vital Signs domains. Mindfulness IIV was negatively associated with performance on the domains of psychomotor speed [r=-.18; p=.003], composite memory [r=-.14; p=.023] and verbal memory [r=-.15; p=.015]. For the high NCI group, IIV mindfulness was positively associated with cognitive flexibility [r=.31; p=.024], executive functioning [r=.33; p=.016] and was negatively related to visual memory [r=-.28; p=.043]. For the low NCI group, IIV mindfulness was negatively related to psychomotor speed [r=-.49; p<.001], composite memory [r=-.32; p=.033] and verbal memory [r=-.31; p=.038]. There was no relation found for individual FFMQ facet scores and CNS Vital Sign domains.

Increased consistency in self-reported mindfulness (lower IIV) was associated with greater processing speed and memory performance in the overall sample. However, the relation been mindfulness IIV and cognitive performance changed greatly in high NCI performers compared to low NCI performers. The low NCI group may be a proxy for poor effort which would explain why more variable self-reported mindfulness was associated with worse performance for processing speed and memory and this could be driving the results for the overall sample. However, our findings for the high NCI performance group are unique and suggest an association between increased variability in mindfulness facets and improved cognitive flexibility and executive functioning. Further study of mindfulness variability and aspects of executive functioning is warranted.

Prior studies have presented demographic adjustment as beneficial because it helps equalize, across demographic groups, the percentage of participants (recruited from the general population without prior diagnosis) who fell beneath the test impairment cutoff (e.g., Smith, et al., 2008). This methodology ignores the possibility that group differences in those falling beneath an impairment cutoff could reflect cognitive impairment prevalence differences between demographic groups in the undiagnosed general population. Demographic group differences in cognitive test scores reflect a mixture of two categories of influences: measurement bias (item/test/examiner bias, language/cultural bias, stereotype threat, etc.) and factors which differentially increase the number of low scores in one group by increasing relative risk (RR) for cognitive impairment (biological aging processes, cognitive reserve, social determinants of health [SDoH], etc.). The current simulation study examined how the effect of demographic adjustment on the diagnostic accuracy of a hypothetical test (operationalized as the area under the curve [AUC] in an ROC analysis) varied as the mixture of influences which caused demographic differences in scores were varied.

215,040 samples were randomly generated. Each sample consisted of two demographic groups, with Group 0 always representing the lower scoring group. Across samples, Group 1's baseline risk of impairment and Group 0's relative risk were varied, and these determined the prevalence of cognitive impairment in the groups. Three facets of measurement bias were varied in the simulation: how much lower Group 0's average score was than Group 1's, the degree of non-homogeneity of variance between groups, and how much less reliable the measure was for Group 0. Additional parameters were included and varied to ensure the robustness of findings across a variety of situations. Samples reflected all possible combinations of all varied parameters. For each sample, a baseline AUC was calculated when impairment was regressed on the unadjusted test score. Then, test scores were adjusted for demographic group and difference in adjusted and unadjusted AUC was calculated. This adjusted/unadjusted AUC difference was then regressed on the simulation parameters to quantify their relative influence.

The more Group 0's average score was reduced by measurement bias, the more improvement in AUC was seen after adjustment (ß = 1.76). Trivial but significant main effects of variance non-homogeneity (ß = .09), increased relative risk (ß = -.08), and reduced reliability (ß = .02) were also found, but more importantly, each of these predictors significantly interacted with Group 0 mean score reduction, such that higher relative risks (ß = -1.22), lower reliability (ß = .36), and higher variance (ß = -.15) in Group 0 compared to Group 1 each reduced the association between Group 0 mean score reduction and improvement in AUC.

Demographic adjustment only improves AUC when the mean reduction in scores due to measurement bias is sufficiently high while risk for impairment, test reliability and test score variances are sufficiently equivalent among the demographic groups. When this is not the case, demographic adjustment can be counter-productive, reducing the AUC of the test. We conclude by proposing a novel method for adjusting test scores.

Judgment, defined as the capacity to make decisions carefully after consideration of available information, which may entail a variety of sources, has come to be regularly assessed within neuropsychology, and impairment of judgment has been demonstrated across multiple disorders (Rabin, Borgos, & Saykin, 2008). This study aimed to re-examine the relationship between judgment and performance on measure of cognitive functioning including (memory, attention, language, visuospatial abilities, speed, and aspects of executive functioning) in a mixed-clinical sample of older adult veterans.

Data for this study was collected from the Cognitive Functioning in Older Adult Veteran’s database repository (CFOAV) at a large Veteran Affairs Healthcare System (VAHCS). Participants were veterans seeking treatment in the Neuropsychology Assessment Clinic. Inclusion criteria were that participants must have answered the nine questions from the TOP-J and received a score based on the specific criteria. Participants were excluded if they appeared to lack adequate test engagement or had a serious mental illness. The final sample for the current study consisted of 83 veterans (73% male, n = 76), ranging from 50 to 89 years (m = 72.01, SD = 9.70), with and average of 13 years of education (SD = 3.21). Of the sample, 75% reported that they were White, 7% African American/Black, and 1% Latino/Hispanic, and ICD-10 diagnoses ranged from age-related cognitive decline, mild cognitive impairment, vascular dementia, and dementia in other disease classified.

Using SPSS (Version 27), Pearson correlations were conducted to examine the relationship between the TOP-J raw score, demographic variables, and measures of cognitive functioning, including the WTAR, the RBANS index scores, WAIS-DS, TMT A, TMT B, COWAT, and ANT. Missing data were excluded pairwise in the analyses. Correlation analyses revealed a significant small-to-medium correlation between the TOP-J and the. There were small to medium correlations between the TOP-J, WTAR (r = .31, p = .01), TMT A (r = .27, p = .02), WAIS DS (r = .30, p = .01), and RBANS Attention index (r = .35, p = .04). There was a significant large relationship between the TOP-J and the RBANS Immediate Memory index (r = .52, p = .002). There were no significant associations between the TOP-J, demographic variables (e.g., biological sex, age, and education), TMT-B, COWAT, or ANT.

The study supported previous decision making research (Moye, Karel, Gurrera & Asar, 2006) that has found the ability to attend to and immediately retain information to be an important foundational component. While the present study did not fully replicate previous findings that the Top-J was correlated to measures of executive functioning, strong correlations did emerge with verbal memory and a measure of crystalized verbal abilities similar to Rabin et al. (2007). Such research informs the assessment practical judgment. It also indicates that one’s ability to acquire and encoded unstructured and contextual verbal information, as well as pre-morbid verbal abilities, may provide potential targets to improve or compensate from decrements in overall practical judgement. This is certainly an areas for future research.

Limitations of traditional neuropsychological assessment include testing in a highly controlled environment designed to minimize distraction. While informative, it may not fully capture real-world cognitive functioning. This may be particularly important for individuals with mild traumatic brain injury (mTBI), a subset of whom report subtle challenges with complex cognitive functioning that are not consistently captured by neuropsychological assessment. The objective of this study was to extend previous work examining cognitive correlates of performance on functional assessment tool, the Goal Processing Sale (GPS), in a larger sample of Veterans with mTBI.

46 Veterans with chronic mTBI completed GPS and neuropsychological measures (mean age = 43.5; education = 15 years; 89% male). 93% of participants had clinically significant PTSD (PCL-M > 31). The GPS is an ecologically valid assessment in which participants plan and execute a complex task following specified rules under a time constraint. Performance is rated on a 0 (not able) to 10 (absolutely not a problem) scale in 8 domains: 1) Planning, 2) Initiation, 3) Self-Monitoring, 4) Maintenance of Attention, 5) Sequencing and Switching of Attention, 6) Flexible Problem Solving, 7) Task Execution, and 8) Learning and Memory. The GPS Overall Performance is average of 8 domain scores. Neuropsychological assessment data were scored using standardized norms and transformed into z-scores. Scores were averaged into 2 domains: 1) Overall Attention/Executive Function (4 subdomains: Working Memory [Auditory Consonant Trigrams, WAIS-III Letter Number Sequencing], Sustained Attention [Digit Vigilance Test], Inhibition [D-KEFS Stroop Inhibition], Mental Flexibility [Trail Making Test B, D-KEFS Stroop Inhibition Switching, Design Fluency Switching, Verbal Fluency Switching]) and 2) Overall Memory (2 subdomains: Total Recall [HVLT-R, BVMT-R], and Delayed Recall [HVLT-R, BVMT-R]).

Pearson correlation coefficients were used to determine relation between overall GPS and overall executive function performance, as well as 8 GPS subdomain and 8 neuropsychological domain/subdomain scores. To adjust for multiple comparisons, p < .01 was used.

Overall GPS performance was statistically significantly related to Overall Attention/Executive Functioning and Overall Memory. Investigating further, multiple significant subdomain relations emerged. GPS Planning was related to Inhibition. GPS Self-Monitoring and GPS Task Execution were related to Mental Flexibility. GPS Maintenance of Attention and GPS Flexible Problem Solving were related to Mental Flexibility and Inhibition. GPS Sequencing and Switching of Attention was related to Mental Flexibility and Total Recall.

GPS Learning and Memory was related to Working Memory, Mental Flexibility, and Inhibition. GPS Initiation was not related to neuropsychological measures.

Current findings build upon prior work establishing validity of GPS functional assessment measure (Novakovic-Agopian et al., 2012). Seven of 8 GPS subdomains were related to at least one aspect of executive functioning assessed with neuropsychological measures, with the majority related to mental flexibility. Taken together, findings suggest that the GPS converges with traditional measures, offering a method to capture multiple aspects of executive functioning applied together. Further, it may also be useful tool capturing aspects of executive functioning in complex, ecologically-valid settings often not captured with traditional neuropsychological assessment.

Assessment of performance validity during neuropsychology evaluation is essential to reliably interpret cognitive test scores. Studies (Webber et al., 2018; Wisdom, et al., 2012) have validated the use of abbreviated measures, such as Trial 1 (T1) of the Test of Memory Malingering (TOMM), to detect invalid performance. Only one study (Bauer et al., 2007) known to these authors has examined the utility of Green’s Word Memory Test (WMT) immediate recall (IR) as a screening tool for invalid performance. This study explores WMT IR as an independent indicator of performance validity in a mild TBI (mTBI) veteran population.

Participants included 211 (Mage = 32.1, SD = 7.4; Medu = 13.1, SD = 1.64; 94.8% male; 67.8% White) OEF/OIF/OND veterans with a history of mTBI who participated in a comprehensive neuropsychological evaluation at one of five participating VA Medical Centers. Performance validity was assessed using validated cut scores from the following measures: WMT IR and delayed recall (DR); TOMM T1; WAIS-IV reliable digit span; CVLT-II forced choice raw score; Wisconsin Card Sorting Test failure to maintain set; and the Rey Memory for Fifteen Items test, combo score. Sensitivity and specificity were calculated for each IR score compared with failure on DR. In addition, sensitivity and specificity were calculated for each WMT IR score compared to failure of at least one additional performance validity measure (excluding DR), two or more measures, and three or more measures, respectively.

Results indicated that 46.8% participants failed to meet cut offs for adequate performance validity based on the standard WMT IR cut score (i.e., 82.5%; M = 81.8%, SD = 17.7%); however, 50.2% participants failed to meet criteria based on the standard WMT DR cut score (M = 79.8% SD = 18.6%). A cut score of 82.5% or below on WMT IR correctly identified 82.4% (i.e., sensitivity) of subjects who performed below cut score on DR, with a specificity of 94.2%. Examination of IR cutoffs compared to failure of one or more other PVTs revealed that the standardized cut score of 82.5% or below had a sensitivity of 78.2% and a specificity of 72.4%; whereas, a cut score of 65% or below had a sensitivity of 41% and a specificity of 91.3%. Similarly, examination of IR cutoffs compared to failure of two or more additional PVTs revealed that the cut score of 60% or below had a sensitivity of 45.7% and specificity of 93.1% ; whereas, a cut score of 57.5% or below had a sensitivity of 57.9% and specificity of 90.9% when using failure of three or more PVTs as the criterion.

Results indicated that a cut score of 82.5% or below on WMT IR may be sufficient to detect invalid performance when considering WMT DR as criterion. Furthermore, WMT IR alone, with adjustments to cut scores, appears to be a reasonable way to assess symptom validity compared to other PVTs. Sensitivity and specificity of WMT IR scores may have been adversely impacted by lower sensitivity of other PVTs to independently identify invalid performance.

The National Institutes of Health-Toolbox cognition battery (NIH-TCB) is widely used in cognitive aging studies and includes measures in cognitive domains evaluated for dimensional structure and psychometric properties in prior research. The present study addresses a current literature gap by demonstrating how NIH-TCB integrates into a battery of traditional clinical neuropsychological measures. The dimensional structure of NIH-TCB measures along with conventional neuropsychological tests is assessed in healthy older adults.

Baseline cognitive data were obtained from 327 older adults. The following measures were collected: NIH-Toolbox cognitive battery, Controlled Oral Word Association (COWA) letter and animals tests, Wechsler Test of Adult Reading (WTAR), Stroop Color-Word Interference Test, Paced Auditory Serial Addition Test (PASAT), Brief Visuospatial Memory Test (BVMT), Letter-Number Sequencing (LNS), Hopkins Verbal Learning Test (HVLT), Trail Making Test A&B, Digit Span. Hmisc, psych, and GPARotation packages for R were used to conduct exploratory factor analyses (EFA). A 5-factor solution was conducted followed by a 6-factor solution. Promax rotation was used for both EFA models.

The 6-factor EFA solution is reported here. Results indicated the following 6 factors: working memory (Digit Span forward, backward, and sequencing, PASAT trials 1 and 2, NIH-Toolbox List Sorting, LNS), speed/executive function (Stroop color naming, word reading, and color-word interference, NIH-Toolbox Flanker, Dimensional Change, and Pattern Comparison, Trail Making Test A&B), verbal fluency (COWA letters F-A-S), crystallized intelligence (WTAR, NIH-Toolbox Oral Recognition and Picture Vocabulary), visual memory (BVMT immediate and delayed), and verbal memory (HVLT immediate and delayed. COWA animals and NIH-Toolbox Picture Sequencing did not adequately load onto any EFA factor and were excluded from the subsequent CFA.

Findings indicate that in a sample of healthy older adults, these collected measures and those obtained through the NIH-Toolbox battery represent 6 domains of cognitive function. Results suggest that in this sample, picture sequencing and COWA animals did not load adequately onto the factors created from the rest of the measures collected. These findings should assist in interpreting future research using combined NIH-TCB and neuropsychological batteries to assess cognition in healthy older adults.

Performance validity (PVT) and symptom validity tests (SVT) have become standard practice in assessing credibility of neuropsychological profiles and symptom report. While PVTs assess cognitive task engagement, SVTs assess credibility of patient symptom report. Although prior research aimed to conceptualize the relationship between the two validity measure types, it generally focused on SVTs from the Minnesota Multiphasic Personality Inventory (MMPI-2 &RF) and the Structured Inventory of Malingered Symptoms (SIMS; Ord et al., 2021, MMPI-2; Van Dyke et al., 2013). Further studies have demonstrated mixed results, with many studies concluding that symptom and performance validity are separate but related constructs. The current study aimed to assess the relationship between PVTs and SVTs utilizing symptom validity measures from the Personality Assessment Inventory (PAI) across three samples, including neurodevelopmental, psychiatric, and traumatic brain injury groups.

Participants included 634 individuals consecutively referred for neuropsychological assessment who completed the Test of Memory Malingering (TOMM) and the PAI (mean Age = 41.7, SD = 15.7; mean Education = 13.7, SD = 2.7; 53% female; 89% Caucasian). Participants were divided into three groups based on referral, including neurodevelopmental (mean Age = SD = 10.7; mean Education = 13.4, SD = 2.5; 39% female; 79% Caucasian), psychiatric (mean Age = 44.7, SD = 15.0; mean Education = 13.8, SD = 2.8; 58% female; 90% Caucasian), and traumatic brain injury samples (mean Age = SD = 15.5; mean Education = 13.3, SD = 2.3; 50% female; 91% Caucasian). Four structural equation models (latent variable models) were constructed. The first model was fit across the entire sample while the remaining three were fit for the aforementioned subsamples. TOMM trials modeled the performance validity latent variable while SVTs from the PAI modeled the symptom validity latent variable (Positive Impression Management and Defensiveness Index modeled underreporting; Negative Impression Management, Malingering Index, and Cognitive Bias Scale modeled overreporting).

In the full sample model overreporting significantly predicted performance validity (p < 0.001, r = -0.31), indicating higher symptom overreporting related to poorer performance validity while symptom underreporting did not significantly predict performance validity (p = 0.09, r = 0.08). In the neurodevelopmental model overreporting did not significantly predict performance validity (p = 0.44, r = 0.10). Further, symptom underreporting did not significantly predict performance validity (p = 0.40, r = 0.10). Similarly, for the TBI model, overreporting did not significantly predict performance validity (p = 0.82, r = -0.02) and symptom underreporting did not significantly predict performance validity (p = 0.50, r = -0.08). For the psychiatric sample symptom underreporting did not significantly predict performance validity (p = 0.06, r = 0.11); however, symptom overreporting significantly predicted performance validity (p < 0.001, r = - 0.39).

The current study expands on prior research comparing the relationship between SVTs and PVTs in neuropsychological evaluation utilizing SVTs from the PAI. Results of the present study suggest the relationship between the SVTs and PVTs varies by referral type and further supports using both PVTs and SVTs in neuropsychological assessment.

Cognitively healthy individuals who complete a neuropsychological test battery can obtain very low scores. These very low scores are not likely indicative of cognitive impairment but are rather considered spuriously low scores. The expected number of low scores varies based on number and type of neuropsychological tests. Typically, base rates have been determined from normative samples, which could differ from samples seen in clinical settings. The current study reports on base rates of spuriously low cognitive scores in older adults presenting to a memory clinic who were diagnosed with subjective cognitive impairment after interprofessional assessment and information from collateral informants ruled out objective cognitive impairment.

Base rates of spuriously low scores for a neuropsychological battery of 12 scores were based on 92 cognitively healthy older adults presenting to a specialist memory clinic (M(age) = 61.00, SD = 12.00; M(edu) = 12.00, SD = 2.74). Crawford’s Monte Carlo simulation algorithm was used to estimate multivariate base rates by calculating the percentage of cognitively healthy memory clinic patients who produced age and education normed scores at or below the 5th percentile. The following tests were used to produce the 12 scores: block design, digit span backwards, and coding from the WAIS-IV; logical memory I and II from the WMS-IV; immediate and delayed memory scores from the California Verbal Learning Test Second Edition short form; immediate and delayed memory scores from the Brief Visuospatial Memory Test Revised; category switching, letter number sequencing, and inhibition switching from the Delis Kaplin Executive Functioning System.

An estimated 33.58% of the cognitively healthy memory clinic population would have one or more low scores (5th percentile cutoff),14.7% would have two or more low scores, 6.55% would have three or more, 2.94% would have four or more, and 1.31% percent would have 5 or more very low scores due to chance.

Determining base rates of spuriously low scores on a neuropsychological battery in a clinical sample of referred older adults with subjective memory complaints could assist in the diagnostic process. By understanding base rates of clinical samples, clinicians can use empirical data to adjust for expected low scores rather than using conventional corrections (such as 1/20 test scores expected to be low). In a memory clinic sample, three or more low test scores out of 12 is expected to be relatively rare in those who were later determined to have no objective evidence of cognitive impairment based on interprofessional assessment. Understanding normal frequency of low scores will prevent undue conclusions of cognitive impairment which will minimize false positives in diagnosis.

The MMPI-2-RF contains scales that assess different types of invalid response styles, especially potential symptom over-reporting (e.g., F-r, Fs, Fp-r, FBS-r, RBS). However, these scales are not designed to specifically capture noncredible symptoms reports associated with Attention-Deficit/Hyperactivity Disorder (ADHD). Robinson & Rogers (2018) proposed the experimental Dissimulation ADHD validity scale (Ds-ADHD) on the MMPI-2-RF that was effective in distinguishing credible and non-credible ADHD diagnoses via a simulator-based study. Within the current study, the Ds-ADHD scale was compared to the established MMPI-2-RF validity scales within a mixed sample of U.S. Military Veterans.

173 Veterans (Mage = 36.18, SDage = 11.10, Medu = 14.01, SDedu = 2.11, 88% male, 81% White, 17% Black) completed a neuropsychological evaluation which included an internally consistent MMPI-2-RF profile and up to 10 performance validity tests (PVTs) as well as a question about a possible ADHD diagnosis. The credible group was determined if participants passed all PVTs (n=146) and completed at least 2 PVTs. The non-credible group was determined by failing two or more PVTs (n=27). Group assignment was clinically confirmed. The Ds-ADHD scale was calculated according to Robinson & Rogers’ (2018); responses of “true” (i.e., erroneous stereotypes) were coded as 1 and “false” answers were coded 2, creating a 10- to 20-point scale. Thus, lower scores would be associated with a higher likelihood of a feigned ADHD presentation. Other MMPI-2-RF validity scales of interest included F-r, Fs, Fp-r, FBS-r, and RBS.

The established MMPI-2-RF validity scales were significantly correlated with PVT group membership, but correlations were weak to moderately strong (rS ranged from -.43 to -.18; ps < .05). A series of stepwise regression models were completed with the Ds-ADHD scale and one of the MMPI-2-RF validity scales as independent variables, with group membership as the dependent variable. Ds-ADHD) contributed uniquely to each model (CÜ ranged from .03 to .04, ps < .05). The established MMPI-2-RF validity scales effectively classified group membership (AUC values ranged from .57 to .68), and the Ds-ADHD scale had a marginally higher AUC (.69); however, it was not statistically significantly stronger than any of the established scales (ps > .05).

Clinicians interested in identifying potentially simulated ADHD presentations with the MMPI-2-RF may desire to calculate the Ds-ADHD scale, which previously only had support from a simulator-based study. The Ds-ADHD scale significantly contributed to each model, suggesting that it helped explain groups over and above each of the traditional MMPI-2-RF validity scales. However, it only had a marginally stronger ability to classify participants, indicating that there may be diminishing returns for clinicians. Among the traditional validity scales, RBS and F-r best classified groups, and FBS-r was the least effective. This study employed a cross-sectional design in a mixed sample of Veterans undergoing a neuropsychological evaluation. Future research should focus on replicating the findings using a credible sample that was limited to an independently verified diagnosis of ADHD.

The global prevalence of persons living with dementia will soon exceed 50 million. Most of these individuals reside in low- and middle-income countries (LMICs). In South Africa, one such LMIC, the physician-to-patient ratio of 9:10 000 severely limits the capacity of clinicians to screen, assess, diagnose, and treat dementias. One way to address this limitation is by using mobile health (mHealth) platforms to scale-up neurocognitive testing. In this paper, we describe one such platform, a brief tablet-based cognitive assessment tool (NeuroScreen) that can be administered by lay health-providers. It may help identify patients with cognitive impairment (related, for instance, to dementia) and thereby improve clinical care and outcomes. However, there is a lack of data regarding (a) the acceptability of this novel technology for delivery of neurocognitive assessments in LMIC-resident older adults, and (b) the influence of technology-use experience on NeuroScreen performance of LMIC-resident older adults. This study aimed to fill that knowledge gap, using a sample of cognitively impaired South African older adults.

Participants were 60 older adults (63.33% female; 91.67% right-handed; age M = 68.90 years, SD = 9.42, range = 50-83), all recruited from geriatric and memory clinics in Cape Town, South Africa. In a single 1-hour session, they completed the entire NeuroScreen battery (Trail Making, Number Speed, Finger Tapping, Visual Discrimination, Number Span Forward, Number Span Backward, List Learning, List Recall) as well as a study-specific questionnaire assessing acceptability of NeuroScreen use and overall experience and comfort with computer-based technology. We summed across 11 questionnaire items to derive a single variable capturing technology-use experience, with higher scores indicating more experience.

Almost all participants (93.33%) indicated that NeuroScreen was easy to use. A similar number (90.00%) indicated they would be comfortable completing NeuroScreen at routine doctor's visits. Only 6.67% reported feeling uncomfortable using a tablet, despite about three-quarters (76.67%) reporting never having used a tablet with a touchscreen before. Almost one in five participants (18.33%) reported owning a computer, 10.00% a tablet, and 70.00% a smartphone. Correlations between test performance and technology-use experience were statistically significant (or strongly tended toward significance) for most NeuroScreen subtests that assessed higherorder cognitive functioning and that required the participant to manipulate the tablet themselves: Trail Making 2 (a measure of cognitive switching ability), r = .24, p = .05; Visual Discrimination A (complex processing speed [number-symbol matching]), r = .38, p = .002; Visual Discrimination B (pattern recognition), r = .37, p = .004; Number Speed (simple information processing speed), r = .36, p = .004. For the most part, there were no such significant associations when the NeuroScreen subtest required only verbal input from the participant (i.e., on the list learning and number span tasks).

NeuroScreen, a tablet-based neurocognitive screening tool, appears feasible for use among older South Africans, even if they are cognitively impaired and have limited technological familiarity. However, test performance might be influenced by amount of technology-use experience; clinicians using the battery must consider this in their interpretations.

Executive functions (EFs) refer to a set of top-down cognitive processes that are fundamental for the control of goal directed behaviours (Lezak et al., 2004). Inhibition (the capacity to ignore irrelevant information) and selective attention (the capacity to selectively focus on relevant information) are considered as the core components of EFs (Barkley, 2001; Veer et al., 2017). EFs can be impaired following brain damage (Chung et al., 2013) and they are traditionally assessed individually, using paper-and-pencil tests that have long been criticized for their ecological and sensitivity limitations (Dugbartey et al., 1999; Miyake et al., 2000). Here we developed a serious game in immersive virtual reality to measure inhibition and selective attention based on the go/no-go paradigm and the D2 Test.

Sixty healthy participants were asked to perform a series of tasks, where in each task, the target was a mole wearing a coloured helmet. In task A, either the target or a distractor bomb was presented. The participants had to respond to the target and inhibit a response to the bomb. In task B, the target was presented with distractor moles wearing different coloured helmets. The two tasks could also be combined, task AB, where the target was presented with distractors (as in task B) versus the bomb was presented with distractor moles. All the stimuli appeared from four molehills aligned to sagittal axis (near to far from the participant). Responses were made with the dominant hand in task A and with both tasks in tasks B and AB. The participants were instructed to hit the target with a virtual hammer.

Response time analysis showed that in tasks A, B and AB, participants were slower to respond to the far compared to near targets. In task B and AB, participants were additionally slower to respond to the left compared right targets. Significant interactions between laterality and proximity for tasks B and AB showed that the participants were significantly slower to response to left vs right target in both far and near conditions. All participants were able to inhibit responses to the bomb and distractor stimuli.

In conclusion, we have developed a novel serious game in immersive virtual reality for the assessment of inhibition and selective attention, both as individual tests and as a combined test. Future studies will test patients with executive dysfunction to test the validity of this new serious game.

Risk factors that contribute to brain pathology and cognitive decline among older adults include demographic factors (e.g., age, educational attainment), genetic factors, health factors, and depression (Plassman et al., 2010). Variability within an individual’s performance across cognitive tasks is referred to as dispersion (Hultsch et al., 2002), which appears sensitive to subtle cognitive impairments associated with neurodegenerative pathology in older adults (Bangen et al., 2019; Kälin et al., 2014). Thaler and colleagues (2015) found that dispersion across domains of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was a useful indicator of cognitive changes associated with cardiovascular disease and mortality. Also, research by Manning and colleagues (2021) found that elevated ratings of depression and anxiety in older adults was associated with greater dispersion across neuropsychological testing. The present study aimed to replicate findings that greater dispersion in neuropsychological performance is associated with impaired neurocognitive performance and greater self-reported depression among older adults who present for neuropsychological evaluation with cognitive concerns.

Neuropsychological testing data was obtained from a university hospital. Chart reviews were conducted on 369 participants who met initial criteria (60 years or older with testing data from the RBANS Form A, Wechsler Test of Adult Reading, and Geriatric Depression Scale [GDS]). Retrospective analyses were conducted on a final sample of 293 participants from 60 to 94 years old (Mage = 74.41, SDage = 7.43; 179 females, 114 males). Diagnoses were used for group comparisons between cognitively intact individuals with subjective cognitive complaints (SCC, n = 49), persons with Mild Neurocognitive Disorder (mND, n =137), and persons with Major Neurocognitive Disorder (MND, n = 107).

As expected, results indicated that higher dispersion was related to lower Total RBANS Scores (r = -0.54, p < .001) and significant differences across diagnostic groupings (F(2, 289) = 29.19, p < 0.001; SCC, mND, MND) indicated that variability in performance was an indicator of greater neurocognitive impairment. Contrary to expectations, greater dispersion was very weakly associated with lower reported depressive symptomatology (r = -0.13, p = 0.03). A three-stage hierarchical linear regression was conducted with the RBANS Coefficient of Variation (CoV) as the dependent variable and three predictor variables (Age, Total RBANS, Total GDS). The regression analysis results indicated that age was not a significant predictor, but both Total RBANS and GDS Scores were. The most important predictor was Total RBANS Scores which uniquely explained 21% of the variation in dispersion.

This study adds to the current literature regarding the clinical utility of dispersion in neuropsychological performance as an indicator of early and subtle neurocognitive impairment. Depressive symptom reporting was expected to help predict the degree of variability, but this factor was only weakly associated with the RBANS CoV.

Limitations of this study include its retrospective use of archival data and the restricted range on some variables of interest. Further research is needed to examine the relative utility of different measures of dispersion and why increased cognitive performance variability is related to neurocognitive impairment and decline.

Determine the classification concordance between a standalone performance validity test (PVT) and embedded PVTs from multiple cognitive domains.

Participants were 106 patients (49.1% female; 69% white) that underwent neuropsychological evaluation at an outpatient university doctoral clinical psychology training and research clinic (M/SD: age = 32.38/11.95; education = 13.7/2.75). A comprehensive neuropsychological battery included the Medical Symptom Validity Test (MSVT) and embedded PVTs from different cognitive domains: attention - Wechsler Adult Intelligence Scale - Fourth Edition Reliable Digit Span and Digit Span age-corrected scaled score (DS ACSS); memory - California Verbal Learning Test, 3rd Edition (CVLT-3) Forced-Choice Recognition (FCR), executive functions -Wisconsin Card Sorting Test (WCST) Failure to Maintain Set (FMS); visual-spatial/construction -Rey Complex Figure Test (RCFT) Copy raw score; language - Boston Diagnostic Aphasia Examination Complex Ideation Material (CIM); and motor functions - Finger Tapping Test (FTT). All participants were administered the MSVT but not all participants were administered all seven embedded PVTs. Credible/noncredible classification concordance rates and kappa correlations (i.e., percentage of agreement) were computed for each pairwise PVT combination.

Twenty-two percent (n = 23) of the sample failed at least one PVT, with 17.0% (n = 18) failing at least two. DS ACSS was the embedded PVT with the highest MSVT concordance rate at 92.4% and a fair kappa coefficient of .39; WCST FMS had the lowest concordance with MSVT at 82.9% and a slight kappa coefficient of .19. The highest concordance among embedded PVTs from different cognitive domains was CVLT-3 FCR and RCFT Copy raw score at 89.7% with a fair kappa coefficient of .35; the lowest agreement among embedded PVTs was WCST FMS and FTT at 74.0% with a kappa coefficient of -.02. More conservative kappa coefficients among all pair-wise embedded PVT combinations from different cognitive domains ranged from -.02 to .36. For all standalone and embedded PVT pairwise concordance rates, only two fell below the recommended minimum agreement of 80%: FCR vs. FMS = 79.3% and FMS vs. FTT = 74.0%.

Embedded PVTs across various cognitive domains have high agreement with a standalone PVT to aid in classifying noncredible performance, in the 83-92% range. Embedded PVTs from different cognitive domains also have mostly high agreement classification rates amongst themselves in aiding to determine noncredible performance, in the 74-90% range, with the lowest agreement rate between executive function and motor tests at 74%. More conservative kappa-based agreements between PVT pair-wise combinations were fairly consistent with other studies, with most being in the fair range. Finally, these findings indicate about a 17% base rate of noncredible cognitive performance in an outpatient university-based clinic.

There are two forms of intra-individual variability (IIV) in the literature: inconsistency, or variability on one task across many time points, and dispersion, or variability across many tasks at one time point. These forms of IIV are often lumped together into one construct, but there is limited evidence supporting this practice, as few studies have examined the relationship between these measures. Additionally, it is not clear how stable these constructs are over time. Therefore, the goal of the present study was (1) to explore the relationship between (a) inconsistency and dispersion and (b) IIV and mean performance, and (2) to determine whether these relationships are stable over a one- to two-year follow-up interval.

A total of 123 community-dwelling older adults (Mage=69.5, Meducation=15.6 years) from an archival database completed the Push-Turn-Taptap task to assess inconsistency and the Delis-Kaplan Executive Functioning System (D-KEFS) to assess dispersion. These measures were selected because both are highly executive, thereby allowing us to hold the cognitive domain constant across forms of IIV. Dispersion was calculated by taking the standard deviation of the executive conditions of four D-KEFS subtests (Verbal Fluency, Design Fluency, Trail Making, and Color Word Interference). Follow-up data were collected one to two and a half years after baseline. Bivariate and partial correlations controlling for time to follow-up were examined.

Inconsistency and dispersion were not correlated at baseline but were weakly correlated at follow-up (r=.281, p=.012). Additionally, both forms of IIV were moderately correlated with themselves across the follow-up interval (inconsistency: r=.450, p<.001; dispersion: r=.448, p<.001). The partial correlations were nearly identical to bivariate correlations.

Additionally, inconsistency was correlated with poorer mean executive functioning (EF) performance on both the PTT (baseline: r=.281, p<.001, follow-up: r=.435, p<.001) and D-KEFS (baseline: r= -.270, p=.003, follow-up: r=-.573, p<.001). In contrast, dispersion was correlated with mean EF performance only on the D-KEFS at baseline (r= -.292, p<.001) but with both measures at follow-up (PTT: r=.232, p=.039; D-KEFS: r= -.378, p<.001). When controlling for follow-up interval, inconsistency was no longer correlated with baseline mean PTT performance, but all other relationships remained the same (i.e., dispersion and inconsistency displayed the same pattern of correlations with mean EF).

Although inconsistency and dispersion are both forms of IIV, they are weakly related. In other words, although they may have shared mechanisms, these two methods of measuring IIV likely represent different constructs. In the future, authors should take care to specify the form of IIV being investigated in their publications rather than referring to either form as IIV generally. Additionally, both forms of IIV are weakly to moderately correlated with mean EF performance, indicating that IIV is related to but separate from mean-level performance. Interestingly, IIV and mean performance were more strongly correlated at follow-up, which may be suggestive of incipient cognitive decline. Lastly, it seems that both inconsistency and dispersion are somewhat stable across a one- to two-year follow-up interval, suggesting that IIV may be a trait-level construct to some extent. However, IIV may also be influenced by state-level contextual factors, and more research examining the stability of and contributors to IIV is necessary.

Assessing one’s functional capacity

– in addition to neuropsychological performance

– is essential for determining neurocognitive status, and functional assessment is often provided via informant report. While informant characteristics have been shown to influence reports of participant functioning, the degree to which they moderate relationships between reported functioning and participant performance on neuropsychological testing is unclear. Moreover, associations among informant characteristics, reported functioning, and neuropsychological performance have not been directly examined with non-Hispanic Black (NHB) samples, despite this population’s disproportionately high risk for dementia.

In this cross-sectional observational study, we examined the influence of informant characteristics on (1) informant reports of participant functioning (assessed via the Functional Activity Questionnaire [FAQ]), and (2) associations between reported functioning and participant performance on neuropsychological testing, among NHB adult participants in the National Alzheimer’s Coordinating Center cohort (n=1024).

Younger age, female sex/gender, higher education, longer relationships with participants, and cohabitation were informant characteristics associated with poorer reported functioning (ps<.01). Moreover, poorer reported functioning was associated with poorer performance on (1) memory and language tests, particularly for participants with male (versus female) informants, and (2) the Multilingual Naming Test, particularly for participants with cohabitating (versus non-cohabitating) informants (ps<.01).

Within the context of neurocognitive evaluation of NHB adults, informant age, sex/gender, education, relationship length, and cohabitation status influence informant reports of participant functioning, and informant sex/gender and cohabitation status in turn moderate associations between reported functioning and participant performance on comprehensive neuropsychological testing.

Craft Story 21 is a practical, comprehensive, and freely available tool to assess logical memory in patients with memory impairment. Currently, the test does not have normative values in Spanish that adjust to our specific population. Furthermore, the original test does not have a recognition phase to increase the specificity of the memory profile by allowing a distinction between different amnesic profiles. Therefore, this study has two main aims: 1) the generation of normative data for the Craft Story 21 memory test, adjusting to the characteristics of our Spanish-speaking country according to sex, age, and educational level; and 2) the design and validation of the recognition phase of the test and the assessment of its psychometric properties.

The baremization sample comprised 81 healthy participants aged 41 to 91, assessed through the Uniform Data Set III (UDS III) battery of the National Alzheimer’s Coordinating Center (NACC). The design of the recognition phase included three steps: (1) construction of the scale and review by experts, (2) pilot study, and (3) analysis of its psychometric properties. In the latter, 190 participants were recruited and classified into two groups matched by age, sex, and educational level: Mild Cognitive Impairment (MCI n=96) according to Petersen’s (1999) criteria and healthy controls (HC n=94). In addition, the diagnostic accuracy of the test was studied by the ROC curve method, its concurrent validity by correlation with other memory tests (RAVLT), and its internal consistency with Cronbach’s alpha test.

The Baremization sample was divided into 16 groups: 4 age groups (41-51, 51-61, 6171 and >72 years), two educational levels (6-12 years and >12 years), and sex (male and female). Performance was significantly different between age groups (p < 0.003**). No significant differences were found in Craft Story 21 performance between education (p > 0.09) or sex (p > 0.56) groups within the same age group. Normative values in terms of means and standard deviations are presented for each group. Regarding the design of the recognition phase, the groups did not show significant differences in age (p= 0.13), sex (p= 0.88), or schooling (p= 0.33). The overall score of Craft Story 21 test showed the ability to discriminate between healthy controls from patients with MCI (sensitivity = 81.6% and specificity = 72.4%). Its diagnostic accuracy by phase (immediate AUC= 0.86; delayed AUC= 0.86 and recognition AUC= 0.75) was superior than Rey Auditory and Verbal Learning Test (RAVLT): immediate (AUC= 0.79), delayed (AUC= 0.82) and recognition (AUC= 0.74). It presented evidence of concurrent validity with RAVLT in its immediate (r=0.56, p<0.001), delayed (r= 0.66, p<0.001) and recognition (r= 0.37, p<0.001) trails. The instrument also presented evidence of reliability (a= 0.82).

The Craft Story 21 test is a practical, brief and multicultural scale. Thus having appropriate scales for the specific population to be assessed to a more accurate and precise description of the memory profile. Additionally, the new Recognition phase of the test showed evidence of validity and reliability for assessing memory processes.

Global neurocognitive impairment (NCI) has been reported in white people living with HIV/AIDS (PLWHA) in 40%. In Latino populations there have been variable rates described from 30 to 77%. This variation has to do with the lack of normative data for Latino population and the application of norms for English-speakers, increasing the probability of misidentification of NCI. Thus, recognizing which are the best norms available for the Mexican population is important for the accurate identification of NCI. The aim of the present study was to investigate the rate and pattern of HIV associated neurocognitive impairment (NCI) and to compare rates of NCI between rates calculated using norms for the Latin-American population (NLAP) and norms for the US-Mexico border region (NP-NUMBRS).

CIOMS international ethical guidelines for the participation of human subjects in health research were followed. 82 PLWHA living in Tijuana (Mexico) participated in the study (Age: Mean=39.6, SD=10.9; 28.3% Female; Years of education: Mean=8.5, SD=3.6). PLWHA were recruited from the board-and-care home “Las Memorias” (73.4% on antiretroviral therapy; Years since HIV diagnosis: Mean=9.9, SD=7.1). Participants completed a neuropsychological test battery sensitive to detect HIV associated NCI that assessed four cognitive domains (verbal fluency, speed of information processing, executive function and learning/memory). Raw scores in these tests were transformed to percentiles using LAPN and transformed to T-scores using NP-NUMBRS. T-scores were averaged across tests to compute domain specific and global impairment scores. NCI was defined as percentile scores <16 and T-scores < 40. McNemar’s tests were used to compare the rate of NCI utilizing NLAP vs NP-NUMBRS.

According to NLAP, rates of global NCI were about 13.4%. Utilizing NP-NUMBRS rates of global NCI were about 34.1%. However, there is a positive and significant correlation between Global Neurocognitive Function score in PLWHA according to NLAP and NP-NUMBRS (r=0.66, p<.05). Rates of global NCI in PLWHA were significantly lower when using LAP norms (McNemar Chi-Square=29.89; p<.001). Regarding the pattern of NCI according both norms learning and memory was the most affected cognitive domain with 34% of impairment according to NLAP vs 51% of impairment according to NP-NUMBRs.

Utilizing NP-NUMBRS, rates of NCI are consistent with findings of prior studies. Employing norms for LAP the rates of NCI are lower that the ones reported in the literature. This is an important finding since PLWHA included in the sample have several vulnerable factors such as deportation, prostitution, drug abuse and discrimination for sexual preference, factor that could impact cognition. The pattern of neurocognitive function was also similar to those of prior studies in HIV. To accurately make NCI diagnosis it is important to use norms that consider specific characteristics of the population. The diagnosis of NCI is important since these deficits present a strong risk of concurrent problems in a wide range of health behaviors like medication non-adherence in PLWHA.

Education is known to impact neuropsychological test performance, and self-reported years of education is often used in stratifying normative data. However, this variable does not always reflect education quality, particularly among underrepresented populations, and may overestimate cognitive impairment in individuals with low education quality. This cross-sectional study evaluated relative contributions of years of education and reading level to several verbally mediated assessments to improve interpretation of neuropsychological performance.

Data was obtained from the Vanderbilt Memory and Aging Project. Cognitively-unimpaired participants (n=175, 72±7 years, 59% male, 87% Non-Hispanic White, 16±2 years of education) completed a comprehensive neuropsychological protocol. Stepwise linear regressions were calculated using education and Wide Range Achievement Test (WRAT)-3 Reading subtest scores as predictors and letter fluency (FAS, CFL), category fluency (Vegetable and Animal Naming), the Boston Naming Test (BNT), and California Verbal Learning Test (CVLT)-II as outcomes to assess increase in variance explained by educational quality. Models covaried for age and sex. The False Discovery Rate (FDR) based on the Benjamini-Hochberg procedure (Benjamini & Hochberg, 1995) was used to correct for multiple comparisons.

The mean WRAT-3 score was 51±4 (range:37-57), indicating post-high school reading level. Education and WRAT-3 scores were moderately correlated (r=0.36, p<0.01). Both WRAT-3 and years of education independently predicted letter fluency (WRAT-3 p<0.001; education p<0.02), category fluency (WRAT-3 p<0.001; education p<0.05), and CVLT-II performance (WRAT-3 p-values<0.005; education p-values<0.02) in single predictor models. On BNT, WRAT-3 (p<0.001), but not education (p=0.06), predicted performance in single predictor models. In combined models with both WRAT-3 and education, WRAT-3 scores remained a significant predictor of FAS (WRAT-3 b=1.21, p<0.001; education b=0.006, p=0.99) and CFL performance (WRAT-3 b=1.02, p<0.001; education b=0.51, p=0.14). Both WRAT-3 (b=0.21, p=0.01) and years of education (b=0.35, p=0.03) predicted Animal Naming, while WRAT-3 (b=0.16,p=0.008), but not years of education (p=0.37), predicted Vegetable Naming. WRAT-3 was a significant predictor of BNT performance (b=0.21, p<0.001) but not years of education (p=0.65). WRAT-3 predicted CVLT-II learning (b=0.32, p=0.04), immediate recall (b=0.16, p=0.005), and delayed recall performances (b=0.15, p=0.005), while education did not (p-values>0.14). All significant results persisted after FDR correction. WRAT-3 scores explained an additional level of variance beyond the covariates and education alone for FAS (AR=18%), CFL (AR=13%), Animal Naming and Vegetable Naming (AR= 3%), BNT (AR=18%), and CVLT-II learning (AR=2%), immediate recall (AR=4%), and delayed recall (AR=3%).

Reading level more strongly associated with performance on several verbally mediated neuropsychological measures than years of education. For all measures, the addition of reading level significantly increased the amount of variance explained by the model compared to covariates and education alone, which aligns with existing research. However, most of this past work looks at individuals with lower levels of educational quality. Because our cohort was highly educated and at the upper end of the reading spectrum, our results suggest that reading level is important to consider even for more highly educated individuals. Therefore, reading level is a critical variable to consider when interpreting verbally mediated neuropsychological measures for individuals across the educational spectrum.