Cross-cultural validation of the stroke riskometer using generalizability theory

Abstract

Abstract The Stroke Riskometer mobile application is a novel, validated way to provide personalized stroke risk assessment for individuals and motivate them to reduce their risks. Although this app is being used worldwide, its reliability across different countries has not yet been rigorously investigated using appropriate methodology. The Generalizability Theory (G-Theory) is an advanced statistical method suitable for examining reliability and generalizability of assessment scores across different samples, cultural and other contexts and for evaluating sources of measurement errors. G-Theory was applied to the Stroke Riskometer data sampled from 1300 participants in 13 countries using two-facet nested observational design (person by item nested in the country). The Stroke Riskometer demonstrated strong reliability in measuring stroke risks across the countries with coefficients G relative and absolute of 0.84, 95%CI [0.79; 0.89] and 0.82, 95%CI [0.76; 0.88] respectively. D-study analyses revealed that the Stroke Riskometer has optimal reliability in its current form in measuring stroke risk for each country and no modifications are required. These results suggest that the Stroke Riskometer’s scores are generalizable across sample population and countries permitting cross-cultural comparisons. Further studies investigating reliability of the Stroke Riskometer over time in longitudinal study design are warranted.