Measurement properties of the WOMAC LK 3.1 pain scale Academic Article uri icon

  •  
  • Overview
  •  
  • Research
  •  
  • Identity
  •  
  • Additional Document Info
  •  
  • View All
  •  

abstract

  • OBJECTIVE: The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) is applied extensively to patients with osteoarthritis of the hip or knee. Previous work has challenged the validity of its physical function scale however an extensive evaluation of its pain scale has not been reported. Our purpose was to estimate internal consistency, factorial validity, test-retest reliability, and the standard error of measurement (SEM) of the WOMAC LK 3.1 pain scale. METHOD: Four hundred and seventy-four patients with osteoarthritis of the hip or knee awaiting arthroplasty were administered the WOMAC. Estimates of internal consistency (coefficient alpha), factorial validity (confirmatory factor analysis), and the SEM based on internal consistency (SEM(IC)) were obtained. Test-retest reliability [Type 2,1 intraclass correlation coefficients (ICC)] and a corresponding SEM(TRT) were estimated on a subsample of 36 patients. RESULTS: Our estimates were: internal consistency alpha=0.84; SEM(IC)=1.48; Type 2,1 ICC=0.77; SEM(TRT)=1.69. Confirmatory factor analysis failed to support a single factor structure of the pain scale with uncorrelated error terms. Two comparable models provided excellent fit: (1) a model with correlated error terms between the walking and stairs items, and between night and sit items (chi2=0.18, P=0.98); (2) a two factor model with walking and stairs items loading on one factor, night and sit items loading on a second factor, and the standing item loading on both factors (chi2=0.18, P=0.98). CONCLUSION: Our examination of the factorial structure of the WOMAC pain scale failed to support a single factor and internal consistency analysis yielded a coefficient less than optimal for individual patient use. An alternate strategy to summing the five-item responses when considering individual patient application would be to interpret item responses separately or to sum only those items which display homogeneity.

publication date

  • March 2007