RESUMEN
BACKGROUND: Cognitive screening tools enable the detection of cognitive impairment, facilitate timely intervention, inform clinical care, and allow long-term planning. The Montreal Cognitive Assessment for people with hearing impairment (MoCA-H) was developed as a reliable cognitive screening tool for people with hearing loss. Using the same methodology across four languages, this study examined whether cultural or linguistic factors affect the performance of the MoCA-H. METHODS: The current study investigated the performance of the MoCA-H across English, German, French, and Greek language groups (n = 385) controlling for demographic factors known to affect the performance of the MoCA-H. RESULTS: In a multiple regression model accounting for age, sex, and education, cultural-linguistic group accounted for 6.89% of variance in the total MoCA-H score. Differences between languages in mean score of up to 2.6 points were observed. CONCLUSIONS: Cultural or linguistic factors have a clinically significant impact on the performance of the MoCA-H such that optimal performance cut points for identification of cognitive impairment derived in English-speaking populations are likely inappropriate for use in non-English speaking populations. To ensure reliable identification of cognitive impairment, it is essential that locally appropriate performance cut points are established for each translation of the MoCA-H.
RESUMEN
BACKGROUND: The need for cognitive testing is increasing with the aging population and the advent of new Alzheimer disease therapies. To respond to the increased demand, the XpressO was developed as a self-administered digital cognitive prescreening tool that will help distinguish between populations of subjective and objective cognitive impairment according to the Montreal Cognitive Assessment (MoCA). METHODS: This is a prospective validation study. XpressO is composed of tasks that assess memory and executive functions. It is validated compared to the digital MoCA as a gold standard. Out of 118 participants screened from the MoCA Clinic and a family practice clinic, 88 met inclusion criteria, two participants had missing data due to incomplete tasks, 86 participants were included in the analysis; the mean age was 70.34 years. A logistic regression model was built, and its accuracy was evaluated by the sensitivity, specificity, and Area Under the Curve (AUC) of the Receiver Operating Characteristic. RESULTS: Analysis showed strong correlation between (1) XpressO memory tasks scores and the MoCA Memory Index Score (p-values < 0.001), and between (2) XpressO sub-test scores and MoCA total score (p-values < 0.005). The AUC for predicting MoCA performance is 0.845. To classify individuals with normal and abnormal MoCA scores, two threshold values were introduced for the total XpressO scores: sensitivity of 91% at a cutoff of 72, specificity of 90% at a cutoff of 42, and an undetermined range in between. CONCLUSION: XpressO demonstrated high AUC, high sensitivity and specificity to predict cognitive performance compared to the digital MoCA. It may provide efficient cognitive prescreening by identifying individuals who would benefit from further clinical assessments, potentially reducing waiting times and high burden on healthcare clinics.
