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    Developing a Conceptually Equivalent Type 2 Diabetes Risk Score for Indian Gujaratis in the UK

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    Author
    Patel, N; Willis, A; Stone, M; Barber, S; Gray, L; Davies, M; Khunti, K
    Date
    2016-01-01
    Source Title
    Journal of Diabetes Research
    Publisher
    HINDAWI LTD
    University of Melbourne Author/s
    Khunti, Kamlesh
    Affiliation
    General Practice
    Metadata
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    Document Type
    Journal Article
    Citations
    Patel, N., Willis, A., Stone, M., Barber, S., Gray, L., Davies, M. & Khunti, K. (2016). Developing a Conceptually Equivalent Type 2 Diabetes Risk Score for Indian Gujaratis in the UK. JOURNAL OF DIABETES RESEARCH, 2016 (10), https://doi.org/10.1155/2016/8107108.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/256718
    DOI
    10.1155/2016/8107108
    Abstract
    Aims. To apply and assess the suitability of a model consisting of commonly used cross-cultural translation methods to achieve a conceptually equivalent Gujarati language version of the Leicester self-assessment type 2 diabetes risk score. Methods. Implementation of the model involved multiple stages, including pretesting of the translated risk score by conducting semistructured interviews with a purposive sample of volunteers. Interviews were conducted on an iterative basis to enable findings to inform translation revisions and to elicit volunteers' ability to self-complete and understand the risk score. Results. The pretest stage was an essential component involving recruitment of a diverse sample of 18 Gujarati volunteers, many of whom gave detailed suggestions for improving the instructions for the calculation of the risk score and BMI table. Volunteers found the standard and level of Gujarati accessible and helpful in understanding the concept of risk, although many of the volunteers struggled to calculate their BMI. Conclusions. This is the first time that a multicomponent translation model has been applied to the translation of a type 2 diabetes risk score into another language. This project provides an invaluable opportunity to share learning about the transferability of this model for translation of self-completed risk scores in other health conditions.

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