The Eating Behaviour Scale for Diabetes (EBSD) – A Brief Screening Instrument for Disordered Eating in Diabetes
KA Meadows. DHP Research and Consultancy Limited1.
B Mulhern. Health Economics and Decision Science, School of Health and Related Research, University of Sheffield, S1 4DA
Aims Disordered eating behaviour encompassing a range of both mild and more extreme dieting behaviour in people with diabetes is a clinical concern. The aim of this study was to develop a brief screening instrument – the Eating Behaviour Scale for Diabetes (EBDS) – to assess sub clinical disordered eating behaviour).
Methods Exploratory factor analysis was used to assess the dimensionality of the items tapping disordered eating included in the DHP-18 and Rasch analysis to assess item performance with the aim of selecting items for the EBSD. Discriminant validity and reliability of the EBSD was assessed using an external dataset of (N=3175) people with Type 1 and Type 2 diabetes.
Results Disordered eating items clustered as one dimension accounting for 58% of explained variance. Rasch analysis provided evidence of item disordering for three items and one item not fitting the Rasch model. Removal of the misfitting item resulted in the four-item EBSD. The EBSD discriminated between increasing body mass index (BMI) and occurrence of severe hypoglycaemic attack (F = 3.70, p=0.05; F) = 62.50, p=0.000) respectively. Cronbach’s alpha was 0.71.
Conclusion This study has provided provisional evidence to support further development of the EBSD as a psychometrically valid brief screening instrument to identify disordered eating in people with diabetes. Taking less than 4 minutes, the EBSD is easy to complete and score in a clinical setting. Further work is required to assess the psychometric and discriminant performance of the measure for both Type 1 and 2 diabetes populations.
MAPPING THE DIABETES HEALTH PROFILE-18 ONTO THE EQ-5D AND SF-6D GENERIC PREFERENCE BASED MEASURES OF HEALTH
Meadows K1, Mulhern B2, Rowen D2 & Brazier J2
1 DHP Research & Consultancy, London, United Kingdom
2 Health Economics and Decision Science, University of Sheffield, United Kingdom
Objectives: To carry out cost utility analysis, utility values can be derived using generic preference based measures such as EQ-5D or SF-6D. In some settings generic measures are not used, and mapping functions are being developed to predict utility scores from condition specific measures. The aim of this study is to map the DHP-18 – a diabetes-specific HRQoL patient reported outcome measure – onto EQ-5D and SF-6D utility scores for type 1 and type 2 diabetes mellitus populations.
Methods: The data used was pooled from a longitudinal study of quality of life in diabetes. OLS, GLS and Tobit models regressing DHP dimensions and, separately, DHP items onto EQ-5D and SF-6D index scores for both type 1 (n=236) and type 2 (n=2,358) diabetes populations were applied .
Results: For both the EQ-5D and SF-6D, the GLS model mapping selected DHP-18 item scores, squared item scores, age and gender onto the utility index provided the best fit, and this was the case for both the type 1 and type 2 populations (R2 EQ-5D type 1: 0.516; EQ-5D type 2: 0.290; SF-6D type 1: 0.647; SF-6D type 2: 0.396). The models under predict utility when the state is severe and over predict when the state is mild. The error associated with the models was lower for SF-6D than for EQ-5D due to differences in the range of the measures.
Conclusions: The DHP-18 items can predict both the EQ-5D and SF-6D utility scores with acceptable precision with the mapping algorithm for the SF-6D displaying a higher level of precision. The mapping functions developed from the models can be used to predict utility scores in settings where the EQ-5D or SF-6D have not been used alongside the DHP-18. However mapping should be considered second best in comparison to using generic measures in research studies. Click ISPOR Nov 2012 DHP to view poster