Risk Perception Survey on Developing Diabetes Questionnaire: Translation and Validation of the Malay Version

Autor: Fatin Aina Abu Bakar, Tengku Alina Tengku Ismail, Suhaily Mohd Hairon, Siti Suhaila Mohd Yusoff
Rok vydání: 2023
Předmět:
Zdroj: IIUM Medical Journal Malaysia. 22
ISSN: 2735-2285
1823-4631
DOI: 10.31436/imjm.v22i2.2086
Popis: INTRODUCTION: The Risk Perception Survey on Developing Diabetes questionnaire identifies how women with gestational diabetes mellitus (GDM) perceived the risk of developing diabetes after their pregnancy has ended. The objective of this study was to translate and validate an English questionnaire into Malay. MATERIALS AND METHODS: A cross-sectional study was conducted from February 2019 to July 2019 among 200 women with GDM who attended public health clinics in Johor Bahru, Malaysia. The original author of the questionnaire granted us permission to use for this study. The translation of the questionnaire, content, and face validation was performed. It was followed by confirmatory factor analysis using R version 3.5.3 and item analysis for the knowledge domain. The composite reliability and internal consistency reliability using Cronbach alpha were also computed. RESULTS: The Malay version consists of 20 items in five domains; personal control (2 items), optimistic bias (2 items), knowledge of diabetes risk factors (11 items), benefits and barriers of preventive behaviour (3 items), and risk perception (2 items). Confirmatory factor analysis confirmed the structure of the model. The goodness-of-fit values were adequate [comparative fit index=0.994, Tucker-Lewis Index=0.990, standardized root mean square residual=0.038, root mean square of approximation=0.021 (90% CI: 0.000,0.064)]. The four domains had composite reliability values between 0.60 and 0.88. The Cronbach alpha value for knowledge of diabetes risk factors domain was 0.843. CONCLUSION: The translated Malay questionnaire is valid and reliable to assess the perception of women with GDM towards their future risk of getting diabetes.
Databáze: OpenAIRE
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