Cross-Cultural Validation of the Stroke Riskometer Using Generalizability Theory

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aut.relation.endpage19064
aut.relation.issue1en_NZ
aut.relation.journalScientific Reportsen_NZ
aut.relation.startpage19064
aut.relation.volume11en_NZ
aut.researcherFeigin, Valery
dc.contributor.authorMedvedev, Oen_NZ
dc.contributor.authorTruong, Qen_NZ
dc.contributor.authorMerkin, Aen_NZ
dc.contributor.authorBorotkanics, Ren_NZ
dc.contributor.authorKrishnamurthi, Ren_NZ
dc.contributor.authorFeigin, Ven_NZ
dc.date.accessioned2021-09-29T03:09:55Z
dc.date.available2021-09-29T03:09:55Z
dc.date.copyright2021en_NZ
dc.date.issued2021en_NZ
dc.description.abstractThe 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.en_NZ
dc.identifier.citationScientific Reports 11, 19064 (2021). https://doi.org/10.1038/s41598-021-98591-8
dc.identifier.doi10.1038/s41598-021-98591-8en_NZ
dc.identifier.issn2045-2322en_NZ
dc.identifier.issn2045-2322en_NZ
dc.identifier.urihttps://hdl.handle.net/10292/14538
dc.languageengen_NZ
dc.publisherNature Publishing Groupen_NZ
dc.relation.urihttps://www.nature.com/articles/s41598-021-98591-8
dc.rights© The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
dc.rights.accessrightsOpenAccessen_NZ
dc.titleCross-Cultural Validation of the Stroke Riskometer Using Generalizability Theoryen_NZ
dc.typeJournal Article
pubs.elements-id440836
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Faculty of Health & Environmental Science
pubs.organisational-data/AUT/PBRF
pubs.organisational-data/AUT/PBRF/PBRF Health and Environmental Sciences
pubs.organisational-data/AUT/PBRF/PBRF Health and Environmental Sciences/HY Public Health & Psychosocial Studies 2018 PBRF
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