Objectives: The present study examined differences in neurocognitive outcomes among non-Hispanic Black and White stroke survivors using the NIH Toolbox-Cognition Battery (NIHTB-CB), and investigated the roles of healthcare variables in explaining racial differences in neurocognitive outcomes post-stroke. Methods: One-hundred seventy adults (91 Black; 79 White), who participated in a multisite study were included (age: M=56.4; SD=12.6; education: M=13.7; SD=2.5; 50% male; years post-stroke: 1–18; stroke type: 72% ischemic, 28% hemorrhagic). Neurocognitive function was assessed with the NIHTB-CB, using demographically corrected norms. Participants completed measures of socio-demographic characteristics, health literacy, and healthcare use and access. Stroke severity was assessed with the Modified Rankin Scale. Results: An independent samples t test indicated Blacks showed more neurocognitive impairment (NIHTB-CB Fluid Composite T-score: M=37.63; SD=11.67) than Whites (Fluid T-score: M=42.59, SD=11.54; p=.006). This difference remained significant after adjusting for reading level (NIHTB-CB Oral Reading), and when stratified by stroke severity. Blacks also scored lower on health literacy, reported differences in insurance type, and reported decreased confidence in the doctors treating them. Multivariable models adjusting for reading level and injury severity showed that health literacy and insurance type were statistically significant predictors of the Fluid cognitive composite (p<.001 and p=.02, respectively) and significantly mediated racial differences on neurocognitive impairment. Conclusions: We replicated prior work showing that Blacks are at increased risk for poorer neurocognitive outcomes post-stroke than Whites. Health literacy and insurance type might be important modifiable factors influencing these differences. (JINS, 2017, 23, 640–652)

Objective: This study evaluated the comparability of two 5-point symptom self-report rating scales: Intensity (from “not at all” to “very much”) and Frequency (from “none of the time” to “all of the time”). Questions from the Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue 13-item scale was examined.

Methods: Data from 161 patients (60 cancer, 51 stroke, 50 HIV) were calibrated separately to fit an item response theory-based rating scale model (RSM). The RSM specifies intersection parameters (step thresholds) between two adjacent response categories and the item location parameter that reflects the probability that a problem will be endorsed. Along with patient fatigue scores (“measures”), the spread of the step thresholds and between-threshold ranges were examined. The item locations were also examined for differential item functioning.

Results: There was no mean raw score difference between intensity and frequency rating scales (37.2 vs. 36.4, p = n.s.). The high correlation (r = .86, p < .001) between the intensity versus frequency scores indicated their essential equivalence. However, frequency step thresholds covered more of the fatigue measurement continuum and were more equidistant, and therefore reduced floor and ceiling effects.

Significance of results: These two scaling methods produce essentially equivalent fatigue estimates; it is difficult to justify assessing both. The frequency response scaling may be preferable in that it provides fuller coverage of the fatigue continuum, including slightly better differentiation of people with relatively little fatigue, and a small group of the most fatigued patients. Intensity response scaling offers slightly more precision among the patients with significant fatigue.