Validating the Short Form-12 and the development of disease-specific norms in a cohort of Australian private health insurance members
Michael R. Le Grande
A B E , Graeme Tucker C , Stephen Bunker D and Alun C. Jackson A B
A Australian Centre for Heart Health, 75 Chetwynd Street, North Melbourne, Vic. 3051, Australia.
B Faculty of Health, Deakin University, 75 Pigdons Road, Waurn Ponds, Vic. 3216, Australia.
C Adelaide Medical School, University of Adelaide, Adelaide, SA 5000, Australia.
D Department of Epidemiology and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Prahran, Vic. 3181, Australia.
E Corresponding author. Email: michael.legrande@australianhearthealth.org.au
Australian Journal of Primary Health 25(1) 90-96 https://doi.org/10.1071/PY18069
Submitted: 17 May 2018 Accepted: 29 November 2018 Published: 4 February 2019
Abstract
Despite the large number of Australians with private health insurance (PHI), normative quality-of-life data are not available for this population. The Short Form (SF)-12 has been used to characterise the health-related quality of life of Australians in the general population, but there is debate concerning the appropriate algorithm that should be used to calculate its physical and mental component summary scores. The standard (orthogonal method) approach assumes that the mental and physical components are unrelated, whereas an alternate approach (the correlated method) assumes that the two components are related. A consecutive sample of 24 957 PHI members with four major initial disease conditions were administered the SF-12 via phone and 4330 participants were followed up at a mean of 16 months after the first survey. The SF-12 was scored using both the orthogonal and correlated methods, and both scoring models were assessed for model fit and ability to discriminate between the four major disease conditions. Confirmatory factor analysis demonstrated superior model fit and improved discriminative validity when the SF-12 was scored using the correlated method instead of the default orthogonal method. Further, the correlated method demonstrated utility by producing scores that were responsive to change over time.
Additional keywords: chronic diseases, health-related quality of life, measurement, structural equation modelling.
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