Algorithms for Operationalizing Mild Cognitive Impairment Using the Spanish-Language NIH Toolbox Cognition Battery.

OBJECTIVE

Neuropsychologists would benefit from flexible methods for operationalizing psychometric cognitive impairment in Spanish-speaking examinees that vary in association with intelligence, education, and sociocultural characteristics. The current study combined low and high score base rates (BRs) for the Spanish-language NIH Toolbox Cognition Battery (NIHTB-CB) to identify score combinations that are uncommon within different stratifications of the normative sample and may indicate cognitive impairment.

METHOD

The Spanish-language NIHTB-CB normative sample included 250 healthy Latinx adults with complete data on two crystallized and five fluid cognitive tests (M = 38.8 ± 13.7 years old, 72.0% women). Test performances were converted into age-adjusted and demographically adjusted normed scores, adjusting for age, gender, and education. The frequencies at which participants obtained one or more low scores or few to no high scores on fluid cognitive tests were combined into algorithms that occurred at BRs approximately 1 SD (16%) or 1.5 SDs (7%) below the mean.

RESULTS

Algorithms are provided for age-adjusted and demographically adjusted scores, with BRs stratified by crystallized ability, education, and sociocultural characteristics. Using demographically adjusted norms, the BR of obtaining any one of the following, 5 scores <50th, 4+ scores ≤25th, 3+ scores ≤16th, or 2+ scores ≤9th percentile, approximates 1 SD below the mean in participants born (BR = 16.2%) or educated abroad (BR = 18.6%), who are monolingual Spanish speakers (BR = 16.4%) or who reside in low-income households (BR = 13.6%).

CONCLUSIONS

These algorithms offer a flexible approach to operationalizing psychometric cognitive impairment, through which different definitions can be applied to different examinees based on varying crystallized ability, education, and sociocultural characteristics.