Estimation of a Preference-based Index for Sexual Quality of Life (SQOL-3D)
This project developed a preference-based measure for sexual quality of life (SQOL-3D) from the existing sexual quality of life questionnaire (SQOL). The classification system has 3 dimensions: sexual performance, sexual relationship, and sexual anxiety. The project also compared preference weights for the health states using three valuation techniques: time trade-off, ranking and discrete choice experiment (DCE).
In recent years there has been an increasing interest in using data derived from ordinal methods (e.g. ranking, DCE) to estimate the cardinal health states utility values to calculate quality adjusted life years (QALYs). However using ordinal methods to produce cardinal QALY values faces the challenge of how to anchor the values on the full health–dead 1-0 scale used to calculate QALYs. This project deals with this problem to enable two ordinal techniques, DCE and ranking, to be used to produce cardinal health state utility values. These results are compared to the commonly used time trade-off technique.
All values were elicited from a random sample of the general population. 207 interviews were successfully conducted using the time trade-off and ranking techniques and 102 postal questionnaires were returned using the DCE technique.
Values were modelled using regression analysis to provide preference weights for each severity level of each dimension in the classification system. The preference weights vary by the different valuation techniques used to elicit values, and vary by different method used to anchor onto the full health-death scale.
The recommended model to derive the preference weights uses the time trade-off values. The worst state is valued at 0.663 and the best state defined by the classification system is valued at 0.961.
Ratcliffe, J., Brazier, J., Tsuchiya, A., et al. Using DCE and ranking data to estimate cardinal values for health states for deriving a preference-based single index from the sexual quality of life questionnaire. Health Economics 18, 1261-1276 (2009)
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