Clinical Manifestations

Determining the language of neuropsychological assessment in a bilingual patient population is difficult with implications for test performance and clinical interpretation. We compared two methods of identifying language dominance for neuropsychological testing in a sample of bilingual (English/Spanish) Hispanic/Latine patients in South Texas.

Research participants from the South Texas Alzheimer's Disease Research Center (STAC), who identified as bilingual were administered the CLS: Linguistic History Form, which asks individuals to provide a self-rating of their English and Spanish language proficiency, and verbal fluency tasks (F/L fluency in English, and P/M fluency in Spanish) to create a language dominance index (LDI) based on objective test performance.

N = 66 participants completed both measures of language proficiency at the time of data extraction (Table 1). Ratios were calculated for each measure to determine a standardized language proficiency score. Scores ≤ 0.49 were classified as Spanish-dominant, scores = 0.5 were classified as purely bilingual, and scores ≥ 0.51 were classified as English-dominant (Figures 1 and 2). Paired samples t-test comparing the language proficiency ratios revealed that both classification methods performed similarly (t(65)=0.175, p = .431). With the CLS, 5 participants were classified as Spanish-dominant, 9 as purely bilingual, and 52 as English-dominant. With the verbal fluency-derived LDI, 9 individuals were classified as Spanish-dominant, 4 as purely bilingual, and 53 as English-dominant.

Here, we saw subtle (non-statistically significant) differences in subjective rating of language proficiency and objective measurement of language dominance. CLS classified 13.6% and 7.6% of the sample as bilingual or Spanish-speaking, respectively, while LDI classified 6.1% and 13.6% as bilingual or Spanish-speaking. A high percentage of the sample was classified as English-dominant regardless of measure (80.3% and 78.8%), possibly due to demographic factors (e.g., recruitment site, education level, and country of origin). Future analyses will explore these additional demographic influences as well as cognitive testing outcomes in a larger sample across multiple sites in South Texas.