Streamlining the Assessment of Patient-Reported Outcomes in Weight Loss and Body Contouring Patients Academic Article uri icon

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abstract

  • BACKGROUND: The BODY-Q is a widely used patient-reported outcome measure of surgical outcomes in weight loss and body contouring patients. Reducing the length of the BODY-Q assessment could overcome implementation barriers in busy clinics. A shorter BODY-Q could be achieved by using computerized adaptive testing, a method to shorten and tailor assessments while maintaining reliability and accuracy. In this study, the authors apply computerized adaptive testing to the BODY-Q and assess computerized adaptive testing performance in terms of item reduction and accuracy. METHODS: Parameters describing the psychometric properties of 138 BODY-Q items (i.e., questions) were derived from the original validation sample (n = 734). The 138 items are arranged into 18 scales reflecting Appearance, Quality of Life, and Experience of Care domains. The authors simulated 1000 administrations of the computerized adaptive testing until a stopping rule, reflecting assessment accuracy of standard error less than 0.55, was met. The authors describe the reduction of assessment length in terms of the mean and range of items administered. The authors assessed accuracy by determining correlation between full test and computerized adaptive testing scores. RESULTS: The authors ran 54 simulations. Mean item reduction was 36.9 percent (51 items; range, 48 to 138 items). Highest item reduction was achieved for the Experience of Care domain (56.2 percent, 22.5 items). Correlation between full test scores and the BODY-Q computerized adaptive test scores averaged 0.99. CONCLUSIONS: Substantial item reduction is possible by using BODY-Q computerized adaptive testing. Reduced assessment length using BODY-Q computerized adaptive testing could reduce patient burden while preserving the accuracy of clinical patient-reported outcomes for patients undergoing weight loss and body contouring operations.

authors

  • Geerards, Daan
  • Klassen, Anne
  • Hoogbergen, Maarten M
  • van der Hulst, René RWJ
  • van den Berg, Lisa
  • Pusic, Andrea L
  • Gibbons, Chris J

publication date

  • May 2019