Detecting cognitive decline in high-functioning older adults: The relationship between subjective cognitive concerns, frequency of high neuropsychological test scores, and the frontoparietal control network.

OBJECTIVE: Neuropsychologists have difficulty detecting cognitive decline in high-functioning older adults because greater neurological change must occur before cognitive performances are low enough to indicate decline or impairment. For high-functioning older adults, early neurological changes may correspond with subjective cognitive concerns and an absence of high scores. This study compared high-functioning older adults with and without subjective cognitive concerns, hypothesizing those with cognitive concerns would have fewer high scores on neuropsychological testing and lower frontoparietal network volume, thickness, and connectivity. METHOD: Participants had high estimated premorbid functioning (e.g., estimated intelligence ≥75th percentile or college-educated) and were divided based on subjective cognitive concerns. Participants with cognitive concerns (n = 35; 74.0 ± 9.6 years old, 62.9% female, 94.3% White) and without cognitive concerns (n = 33; 71.2 ± 7.1 years old, 75.8% female, 100% White) completed a neuropsychological battery of memory and executive function tests and underwent structural and resting-state magnetic resonance imaging, calculating frontoparietal network volume, thickness, and connectivity. RESULTS: Participants with and without cognitive concerns had comparable numbers of low test scores (≤16th percentile), p = .103, d = .40. Participants with cognitive concerns had fewer high scores (≥75th percentile), p = .004, d = .71, and lower mean frontoparietal network volumes (left: p = .004, d = .74; right: p = .011, d = .66) and cortical thickness (left: p = .010, d = .66; right: p = .033, d = .54), but did not differ in network connectivity. CONCLUSIONS: Among high-functioning older adults, subjective cognitive decline may correspond with an absence of high scores on neuropsychological testing and underlying changes in the frontoparietal network that would not be detected by a traditional focus on low cognitive test scores.

Performance Validity Testing on the NIH Toolbox Cognition Battery: Base Rates of Failed Embedded Validity Indicators in the Adult Normative Sample.

OBJECTIVE: The goal of this study was to determine the base rates of failing proposed embedded validity indicators (EVIs) for the National Institutes of Health Toolbox Cognition Battery (NIHTB-CB) in the normative sample. METHOD: Participants included adults in the NIHTB-CB normative sample with data to calculate age-adjusted standard scores (n = 855; ages: M(SD) = 46.9(17.3), range: 18-85; 65.0% women; education: M(SD) = 14.1(2.5) years) or demographically adjusted T-scores (n = 803; ages: M(SD) = 47.3(17.3), range: 18-85; 65.3% women; education: M(SD) = 14.2(2.5) years) for all tests. The NIHTB-CB includes two tests of crystallized cognition and five tests of fluid cognition. Individual norm-referenced test performances were categorized as falling above or below liberal and conservative cutoffs based on proposed univariate EVIs. The number of univariate EVI failures was summed to compute multivariable EVIs. EVI failure rates above 10% were considered high false-positive rates, indicating specificity < .90. Using chi-square analyses, the frequencies of EVI failures were compared based on gender, race/ethnicity, education, and crystallized composite. RESULTS: The multivariable EVIs had predominantly low false-positive rates in the normative sample. EVI failure rates were most common among participants with low crystallized composites. Using age-adjusted standard scores, EVI failure rates varied by education, race/ethnicity, and estimated premorbid intelligence. These differences were mostly eliminated when using demographically adjusted T-scores. CONCLUSIONS: Multivariable EVIs requiring ≥ 4 failures using liberal cutoffs or ≥ 3 failures using conservative cutoffs had acceptable false-positive rates (i.e., < 10%) using both age-adjusted standard scores and demographically adjusted T-scores. These multivariable EVIs could be applied to large data sets with NIHTB-CB data to screen for potentially invalid test performances.

Test-Retest Reliability and Reliable Change on the NIH Toolbox Cognition Battery.

OBJECTIVE: Researchers and practitioners can detect cognitive improvement or decline within a single examinee by applying a reliable change methodology. This study examined reliable change through test-retest data from the English-language National Institutes of Health Toolbox Cognition Battery (NIHTB-CB) normative sample. METHOD: Participants included adults (n = 138; age: M ± SD = 54.8 ± 20.0, range: 18-85; 51.4% men; 68.1% White) who completed test-retest assessments about a week apart on five fluid cognition tests, providing raw scores, age-adjusted standard scores (SS), and demographic-adjusted T-scores (T). RESULTS: The Fluid Cognition Composite (SS: ICC = 0.87; T-score: ICC = 0.84) and the five fluid cognition tests had good test-retest reliability (SS: ICC range = 0.66-0.85; T-score: ICC range = 0.64-0.86). The lower and upper bounds of 70%, 80%, and 90% confidence intervals (CIs) were calculated around change scores, which serve as cutoffs for determining reliable change. Using T-scores, 90% CI, and adjustment for practice effects, 32.3% declined on one or more tests, 9.7% declined on two or more tests, 36.6% improved on one or more tests, and 5.4% improved on two or more tests. CONCLUSIONS: It was common for participants to show reliable change on at least one test score, but not two or more test scores. Per an 80% CI, test-retest difference scores beyond these cutoffs would indicate reliable change: Dimensional Change Card Sort (SS ≥ 14/T ≥ 10), Flanker (SS ≥ 12/T ≥ 8), List Sorting (SS ≥ 14/T ≥ 10), Picture Sequence Memory (SS ≥ 19/T ≥ 13), Pattern Comparison (SS ≥ 11/T ≥ 8), and Fluid Cognition Composite (SS ≥ 10/T ≥ 7). The reliable change cutoffs could be applied in research or practice to detect within-person change in fluid cognition at the individual level.