Rasch analysis of the Patient Rated Elbow Evaluation questionnaire Academic Article uri icon

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abstract

  • BACKGROUND: The Patient Rated Elbow Evaluation (PREE) was developed as an elbow joint specific measure of pain and disability and validated with classical psychometric methods. More recently, Rasch analysis has contributed new methods for analyzing the clinical measurement properties of self-report outcome measures. The objective of the study was to determine aspects of validity of the PREE using the Rasch model to assess the overall fit of the PREE data, the response scaling, individual item fit, differential item functioning (DIF), local dependency, unidimensionality and person separation index (PSI). METHODS: A convenience sample of 236 patients (Age range 21-79 years; M: F- 97:139) with elbow disorders were recruited from the Roth│McFarlane Hand and Upper Limb Centre, London, Ontario, Canada. The baseline scores of the PREE were used. Rasch analysis was conducted using RUMM 2030 software on the 3 sub scales of the PREE separately. RESULTS: The 3 sub scales showed misfit initially with disordered thresholds on17 out of 20 items), uniform DIF was observed for two items ("Carrying a 10lbs object" from specific activities subscale for age group; and "household work" from the usual activities subscale for gender); multidimensionality and local dependency. The Pain subscale satisfied Rasch expectations when item 2 "Pain - At rest" was split for age group, while the usual activities subscale readily stood up to Rasch requirements when the item 2 "household work" was split for gender. The specific activities subscale demonstrated fit to the Rasch model when sub test analysis accounted for local dependency. All three subscales of the PREE were well targeted and had high reliability (PSI >0.80). CONCLUSION: The three subscales of the PREE appear to be robust when tested against the Rasch model when subject to a few alterations. The value of changing the 0-10 format is questionable given its widespread use; further Rasch-based analysis of whether these findings are stable in other samples is warranted.

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publication date

  • December 2015