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Psychometric Validation of the Translated and Adapted Bengali Version of the HLS-EU-Q16/Q6 for Adults.

Sabrina MousumMarium SalwaKhandakar FatemaMd Atiqul Haque
Published in: Inquiry : a journal of medical care organization, provision and financing (2024)
Health Literacy (HL) emerges as a critical tool in addressing the escalating burden of noncommunicable diseases (NCDs) and their associated costs. Particularly in Bangladesh, where the inadequacy of HL presents multifaceted challenges, there is an urgent need to address this issue. This study aimed to translate and evaluate the Bengali versions of the European Health Literacy Questionnaire with 16 items (HLS-EU Q16) and its shorter 6-item version (HLS-EU Q6), as there is currently no validated Bengali tool for assessing HL. This article used a subset of data from a Bangladeshi national survey of Primary Healthcare (PHC) facilities. The study included adults seeking Non-Communicable Disease (NCD) services at PHCs. Validity and reliability testing succeeded in a detailed back-to-back translation. The statistics covered were descriptive, Cronbach's internal consistency, confirmatory factor analysis, and the chi-square test. Following the translation and preliminary testing, minor rephrasing and the insertion of Item-Relevant Stimulus Material were performed to ensure cultural equivalency. The Confirmatory Factor Analysis produced a 3-factor structure for the HLS-EU-Q16 that included a second-order general component, confirming the viability of using an HL total score. A 3-factor model based on a priori was determined to be suitable for the factor structure of the HLS-EU-Q6. The model fit indices (Chi-square/df, TLI, AGFI, CFI, GFI, SRMR, RMSEA, and PCLOSE) supported CFA models of both scales. The internal consistency of the translated and adapted instruments was α = .934 and .857, respectively. This study showed that the Bengali version of the HLS-EU-Q16 and HLS-EU-Q6 are psychometrically sound, have clear factor structures, and are equivalent to the original models. However, the HLS-EU_Q16 is recommended over the shorter version considering its better psychometric properties.
Keyphrases
  • psychometric properties
  • healthcare
  • mental health
  • high resolution
  • big data
  • machine learning
  • patient reported