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Purpose: We 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.
Methods: In 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).
Results: Half 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).
Conclusion: The 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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0298141 | PLOS |
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Institute of Biotechnology, Department of Medical Biotechnology, SIMATS Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, 602105, Tamil Nadu, India. Electronic address:
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The Koret School of Veterinary Medicine, Hebrew University, Rehovot, Israel.
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Department of Animal Health and Anatomy, Autonomous University of Barcelona, Catalunya, Spain. Electronic address:
Dynamic modelling of infectious diseases of importance to livestock production is a valuable tool for policy and decision makers. Mathematical and simulation models play an essential role in understanding complex systems, but parameterising these models can be challenging, especially in data-sparse environments. When parameters are unable to be estimated from epidemiological or experimental data, a time-consuming and labour-intensive literature review-to identify suitable literature-informed values-is often necessary.
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