Performance of Hispanics and Non-Hispanic Whites on the NIH Toolbox Cognition Battery: the roles of ethnicity and language backgrounds

Abstract

Objective This study examined the influence of Hispanic ethnicity and language/cultural background on performance on the NIH Toolbox Cognition Battery (NIHTB-CB). Method Participants included healthy, primarily English-speaking Hispanic (n=93; Hispanic-English), primarily Spanish-speaking Hispanic (n=93; Hispanic-Spanish), and English speaking Non-Hispanic White (n=93; NH White) adults matched on age, sex, and education levels. All participants were in the NIH Toolbox national norming project and completed the Fluid and Crystallized components of the NIHTB-CB. T-scores (demographically-unadjusted) were developed based on the current sample and were used in analyses. Results Spanish-speaking Hispanics performed worse than English-speaking Hispanics and NH Whites on demographically-unadjusted NIHTB-CB Fluid Composite scores (ps<.01). Results on individual measures comprising the Fluid Composite showed significant group differences on tests of executive inhibitory control (p=.001), processing speed (p=.003), and working memory (p<.001), but not on tests of cognitive flexibility or episodic memory. Test performances were associated with language/cultural backgrounds in the Hispanic-Spanish group: better vocabularies and reading were predicted by being born outside the U.S., having Spanish as a first language, attending school outside the U.S., and speaking more Spanish at home. However, many of these same background factors were associated with worse Fluid Composites within the Hispanic-Spanish group. Conclusions On tests of Fluid cognition, the Hispanic-Spanish group performed the poorest of all groups. Socio-demographic and linguistic factors were associated with those differences. These findings highlight the importance of considering language/cultural backgrounds when interpreting neuropsychological test performances. Importantly, after applying previously published NIHTB-CB norms with demographic corrections, these language/ethnic group differences are eliminated.

Adolescent neurocognitive development and impacts of substance use: Overview of the adolescent brain cognitive development (ABCD) baseline neurocognition battery

“…The total time for administration of the NIH Toolbox ® Cognitive battery is approximately 35 minutes. Although there are both English ( Casaletto et al, 2015 ) and Spanish ( Casaletto et al, 2016 , Flores et al, 2017 ) language versions of the Toolbox ® available, the ABCD study administers only the English version to youth, as proficiency in English for the youth (but not the parent) is a requisite for study participation. Below, we briefly describe each task, the composite scores, and the performance of the ABCD sample to date.…”

Generalizability of demographically corrected Zambian neuropsychological norms to South African women

“…A substantial body of work has investigated the effects of age, educational back-ground, and race on neuropsychological (NP) test performance, and additional studies have been conducted to understand the influences of socioeconomic disadvantage and negative stereotypes (McKay, Doverspike, Bowen-Hilton, & McKay, 2003), multilin-gualism Flores et al, 2017), and resource attainment (Ostrosky-Solis, Canseco, Quintanar, Meneses, & Ardila, 1985) on neurocognitive functioning. South Africa has a history of neuropsychological research and assessment focused on the application of cross-cultural norms (Suchy, 2016), yet gaps still exist due to the many challenges associated with developing clinically useful norms for the complex cultural/racial/ethnic admixture of groups in this country (Nell, 1994;Watts, 2008;Watts & Shuttleworth-Edwards, 2016).…”

The NIH Toolbox: Overview of Development for Use with Hispanic Populations

“…Demographically corrected norms have been published for both the English (Casaletto et al, 2015) and Spanish (Casaletto et al, 2016) language versions of the NIH Toolbox Cognition Battery, and the impact of ethnicity and language on performance has been previously explored (I. Flores et al, 2017). Ultimately, 47 instruments were administered to a national sample ranging in age from 3-85 years (N = 4,859), with at least 150 persons included per age band (single-year age bands for children ages 3-17, and multiple-year age bands for adults ages 18-85).…”