Graeme Hawthorne1. 1. Department of Psychiatry, The University of Melbourne, Melbourne, Australia. graemeeh@unimelb.edu.au
Abstract
OBJECTIVES: As researchers seek to include clinical outcomes, the health-related quality of life (HRQoL) of participants and meet economic evaluation demands, they are confronted with collecting disparate outcome data where parsimony is imperative. This study addressed this through construction of a short HRQoL measure, the Assessment of Quality of Life (AQoL)-8 from the original AQoL. METHODS: Data from the AQoL validation database (N = 996) were reanalyzed using item response theory (IRT) to identify the least fitting items, which were removed. The standard AQoL scoring algorithm and weights were applied. Validity, reliability, and sensitivity tests were carried out using the 2004 South Australian Health Omnibus Survey (N = 3015), including direct comparisons with other short utility measures, the EQ5D and SF6D. RESULTS: The IRT analysis showed that the AQoL was a weak scale (Loevinger H = 0.36) but reliable (Mokken rho = 0.84). Removal of the four weakest items led to an 8-item instrument with two items per subscale, the AQoL-8. The AQoL-8 Loevinger H = 0.38 and Mokken rho = 0.80 suggested similar psychometric properties to the AQoL. It correlated (intraclass correlation coefficient) 0.95 (or 90% of shared variance) with the AQoL. The AQoL-8 was as sensitive to six common health conditions as the AQoL, EQ5D, and SF6D. CONCLUSIONS: The utility scores fall on the same life-death scale as those of the AQoL. Where parsimony is imperative, researchers may consider use of the AQoL-8 to collect participant self-report HRQoL data that is suitable for use either as reported outcomes or for the calculation of quality-adjusted life-years for cost-utility analysis.
OBJECTIVES: As researchers seek to include clinical outcomes, the health-related quality of life (HRQoL) of participants and meet economic evaluation demands, they are confronted with collecting disparate outcome data where parsimony is imperative. This study addressed this through construction of a short HRQoL measure, the Assessment of Quality of Life (AQoL)-8 from the original AQoL. METHODS: Data from the AQoL validation database (N = 996) were reanalyzed using item response theory (IRT) to identify the least fitting items, which were removed. The standard AQoL scoring algorithm and weights were applied. Validity, reliability, and sensitivity tests were carried out using the 2004 South Australian Health Omnibus Survey (N = 3015), including direct comparisons with other short utility measures, the EQ5D and SF6D. RESULTS: The IRT analysis showed that the AQoL was a weak scale (Loevinger H = 0.36) but reliable (Mokken rho = 0.84). Removal of the four weakest items led to an 8-item instrument with two items per subscale, the AQoL-8. The AQoL-8 Loevinger H = 0.38 and Mokken rho = 0.80 suggested similar psychometric properties to the AQoL. It correlated (intraclass correlation coefficient) 0.95 (or 90% of shared variance) with the AQoL. The AQoL-8 was as sensitive to six common health conditions as the AQoL, EQ5D, and SF6D. CONCLUSIONS: The utility scores fall on the same life-death scale as those of the AQoL. Where parsimony is imperative, researchers may consider use of the AQoL-8 to collect participant self-report HRQoL data that is suitable for use either as reported outcomes or for the calculation of quality-adjusted life-years for cost-utility analysis.
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