Conclusions The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions
Background Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values ( HSUVs ) from data obtained from another health-related quality of life ( HRQoL ) measure .
There have been several method ological developments in this area since a previous review up to 2007 .
Mapping scores from the Strengths and Difficulties Questionnaire (SDQ) to preference-based utility values
Abstract Purpose Quality of life mapping methods such as “ Transfer to Utility ” can be used to translate scores on disease-specific measures to utility values , when traditional utility measurement methods ( e.g. st and ard gamble , time trade-off , preference-based multi-attribute instruments ) have not been used . The aim of this study was to generate preliminary ordinary least squares ( OLS ) regression-based algorithms to transform scores from the Strengths and Difficulties Question naires ( SDQ ) , a widely used measure of mental health in children and adolescents , to utility values obtained using the preference-based Child Health Utility ( CHU9D ) instrument . Methods Two hundred caregivers of children receiving community mental health services completed the  SDQ and CHU9D  during a telephone interview . Two OLS regressions were run with the CHU9D utility value as the dependent variable and SDQ subscales as predictors . Result ing algorithms were vali date d by comparing predicted and observed group mean utility values in r and omly selected sub sample s. Results Preliminary validation was obtained for two algorithms , utilising five and three subscales of the SDQ , respectively . Root mean square error values ( .124 ) for both models suggested poor fit at an individual level , but both algorithms performed well in predicting mean group observed utility values . Conclusion This research generated algorithms for translating SDQ scores to utility values and providing research ers with an additional tool for conducting health economic evaluations with child and adolescent mental health data
Conclusions The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions
Background Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values ( HSUVs ) from data obtained from another health-related quality of life ( HRQoL ) measure .
There have been several method ological developments in this area since a previous review up to 2007 .