The EQ-5D and SF-36 achieved mixed results in the quantitative testing against psychometric criteria .
The qualitative analysis suggests this is because they provide a very limited coverage of themes identified by people with mental health problems .
BACKGROUND Generic preference-based measures of health like the EQ-5D and SF-6D ( ® ) are increasingly being used in economic evaluation and outcome assessment .
However , there are concerns as to whether or not these generic measures are appropriate for use in people with mental health problems .
OBJECTIVES The EQ-5D and SF-36 ( ® ) ( including its derivatives the SF-12 ( ® ) and SF-6D ) were assessed using the psychometric criteria of validity and responsiveness using quantitative and qualitative methods .
Another aim was to estimate mapping functions between the EQ-5D and SF-6D and condition-specific measures , where appropriate .
Estimating a Preference-Based Index from the Clinical Outcomes in Routine Evaluation–Outcome Measure (CORE-OM)
Background . The Clinical Outcomes in Routine Evaluation– Outcome Measure ( CORE-OM ) is used to evaluate the effectiveness of psychological therapies in people with common mental disorders . The objective of this study was to estimate a preference-based index for this population using CORE-6D , a health state classification system derived from the CORE-OM consisting of a 5-item emotional component and a physical item , and to demonstrate a novel method for generating states that are not orthogonal . Methods . Rasch analysis was used to identify 11 emotional health states from CORE-6D that were frequently observed in the study population and are , thus , plausible ( in contrast , conventional statistical design might generate implausible states ) . Combined with the 3 response levels of the physical item of CORE-6D , they generate 33 plausible health states , 18 of which were selected for valuation . A valuation survey of 220 members of the public in South Yorkshire , United Kingdom , was undertaken using the time tradeoff ( TTO ) method . Regression analysis was subsequently used to predict values for all possible states described by CORE-6D . Results . A number of multivariate regression models were built to predict values for the 33 health states of CORE-6D , using the Rasch logit value of the emotional state and the response level of the physical item as independent variables . A cubic model with high predictive value ( adjusted R2 = 0.990 ) was selected to predict TTO values for all 729 CORE-6D health states . Conclusion . The CORE-6D preference-based index will enable the assessment of cost-effectiveness of interventions for people with common mental disorders using existing and prospect i ve CORE-OM data sets . The new method for generating states may be useful for other instruments with highly correlated dimensions
The EQ-5D and SF-36 achieved mixed results in the quantitative testing against psychometric criteria .
The qualitative analysis suggests this is because they provide a very limited coverage of themes identified by people with mental health problems .
BACKGROUND Generic preference-based measures of health like the EQ-5D and SF-6D ( ® ) are increasingly being used in economic evaluation and outcome assessment .
However , there are concerns as to whether or not these generic measures are appropriate for use in people with mental health problems .
OBJECTIVES The EQ-5D and SF-36 ( ® ) ( including its derivatives the SF-12 ( ® ) and SF-6D ) were assessed using the psychometric criteria of validity and responsiveness using quantitative and qualitative methods .
Another aim was to estimate mapping functions between the EQ-5D and SF-6D and condition-specific measures , where appropriate .