Brief digital cognitive assessment for detection of cognitive impairment in low‐ and middle‐income countries. (31st December 2021) - Rodriguez‐Salgado, Ana M; Llibre‐Guerra, Jorge J; Peñalver, Ana Ibis; Tsoy, Elena; Bringas, Giosmany; Guerra, Juan C Llibre; Erlhoff, Sabrina J; Allen, Isabel Elaine; Valcour, Victor; Kramer, Joel H; Miller, Bruce L; Possin, Kate L; et al.
Abstract: Background: Rapid technological advances offer a possibility to develop cost‐effective digital cognitive assessment tools. However, it is unclear whether these measures are suitable for application in populations from Low and Middle‐Income Countries (LMIC). Methods: In this cross‐sectional study, we examined the accuracy and validity of the Brian Health Assessment (BHA) in detecting cognitive impairment in a Cuban population; 146 participants (cognitively healthy=53, MCI=46, dementia=47) were recruited at primary care and tertiary clinics. The main outcomes included: accuracy of the BHA in discriminating between controls and cognitively impaired groups (MCI and dementia) and correlations between the BHA subtests of memory, executive functions, and visuospatial skills and criterion‐standard paper‐and‐pencil tests in the same domains. Results: The BHA had an AUC of .95 (95% CI: .91‐ .98) in discriminating between controls and cognitively impaired groups (MCI and dementia, combined) with .91 sensitivity at .85 specificity. In discriminating between control and MCI groups only, the BHA tests had an AUC of .94 (95% CI: .90‐ .99) with .71 sensitivity at .85 specificity. Performance was superior to the MoCA across all diagnostic groups. Concurrent and discriminant validity analyses showed moderate to strong correlations between the BHA tests and standard paper‐and‐pencil measures in the same domain and weak correlations with standard measures in unrelated domains. Conclusions: The BHA has excellent performance characteristics in detecting cognitive impairment including dementia and MCI in a Hispanic population in Cuba and outperformed the MoCA. These results support potential application of digital cognitive assessment for older adults in LMIC.