PLoS ONE (Jan 2024)

Establishing language and ethnic equivalence for health-related quality of life item banks and testing their efficiency via computerised adaptive testing simulations.

  • Yu Heng Kwan,
  • Eva Fenwick,
  • Ying Ying Leung,
  • Warren Fong,
  • Ting Hui Woon,
  • Ling Xiang,
  • Ecosse Lamoureux,
  • Julian Thumboo

DOI
https://doi.org/10.1371/journal.pone.0298141
Journal volume & issue
Vol. 19, no. 2
p. e0298141

Abstract

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PurposeWe aimed to (1) establish linguistic and ethnic equivalence (i.e. lack of bias) for the items in the English and Chinese versions of the Singapore Health and Well Being (SHAWS) Physical Functioning (PF), Positive Mindset (PM) and Social Relationship (SR) item banks (IBs); and (2) evaluate the preliminary efficiency of these IBs using Computer Adaptive Testing (CAT) simulations.MethodsIn this cross-sectional study, 671, 670, and 672 subjects answered 55, 48 and 30 items of the PF, PM, and SR IBs, respectively. Rasch analysis was conducted to assess each IB's psychometric properties, particularly the presence of differential item functioning (DIF) for language and ethnicity. A set of performance criteria related to removing items that displayed notable DIF were employed. CAT simulations determined the mean number of items for high, moderate, and moderate-low measurement precisions (stopping rule: SEM 0.300, 0.387. 0.521, respectively).ResultsHalf of subjects were >50 years old (40.9% PF, 42.1% PM, 41.4% SR), Chinese (50.7% PF, 51.0% PM, 50.6% SR) and female (50.0% PF. 49.4% PM, 52.8% SR) respectively. Rasch analysis revealed 4 items with DIF for the PF IB, 9 items with DIF for the PM IB and 2 items with DIF for the SR IB. In CAT simulations, the mean number of items administered was 8.5, 21.6 and 14.5 for the PF, PM and SR IBs, respectively (SEM 0.300), 5.1, 13.0, 8.0 for PF, PM and SR IBs, respectively (SEM 0.387) and 3.1, 5.3 and 4.1 for PF, PM and SR IBs, respectively (SEM 0.521).ConclusionThe PF, PM and SR IBs to measure health-related quality of life revealed minimal DIF for language and ethnicity after remedial efforts. CAT simulations demonstrated that these IBs were efficient, especially when the stopping rule was set at moderate precision, and support the implementation of the SHAWS IBs into routine clinical care.