Rasch analysis informed the development of a classification system for a diabetes-specific preference-based measure of health.

Published

Journal Article

OBJECTIVE: To develop a classification system (CS) for a diabetes-specific preference-based measure of health titled the Diabetes Utility Index (DUI). STUDY DESIGN AND SETTING: Factor analysis of the Audit of Diabetes-Dependent Quality-of-Life (ADDQoL) items (n=385) identified plausible attributes. An expert panel provided qualitative input, including additional items. Data from three pilot rounds on patients with type 1 or type 2 diabetes were analyzed using Rasch analysis (RA). In a validation survey, the final version of the CS was mailed along with the SF-12v2, Well-Being Questionnaire, and Diabetes Empowerment Scale Short Form to a convenience sample (type 1 or type 2 diabetes). RESULTS: Factor analysis identified two plausible attributes. Experts rated the importance of ADDQoL and additional items, described attributes from item sets and suggested severity levels. Three pilot rounds (n1=52, n2=65, n3=111) tested versions of a CS, containing five attributes with severity levels that were modified using RA and expert input. The final attributes were Physical Ability and Energy, Relationships, Mood and Feelings, Enjoyment of Diet, and Satisfaction with Management of Diabetes. The validation survey (n=396) results indicated satisfactory Rasch fit statistics, reliability, and severity scaling, whereas correspondence of responses to the CS with included measures suggested validity. CONCLUSION: Results provide initial report of the validity and reliability of the CS of the DUI.

Full Text

Cited Authors

  • Sundaram, M; Smith, MJ; Revicki, DA; Elswick, B; Miller, L-A

Published Date

  • August 2009

Published In

Volume / Issue

  • 62 / 8

Start / End Page

  • 845 - 856

PubMed ID

  • 19573741

Pubmed Central ID

  • 19573741

Electronic International Standard Serial Number (EISSN)

  • 1878-5921

International Standard Serial Number (ISSN)

  • 0895-4356

Digital Object Identifier (DOI)

  • 10.1016/j.jclinepi.2009.01.020

Language

  • eng