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- Title
Psychometric Analysis of the Hip Disability and Osteoarthritis Outcome Score (HOOS).
- Authors
Miley, Emilie N.; Casanova, Madeline P.; Pickering, Michael A.; Cheatham, Scott W.; Larkins, Lindsay W.; Cady, Adam C.; Baker, Russell T.
- Abstract
Hip Disability and Osteoarthritis Outcome Survey (HOOS) was developed as a region- and disease-specific outcome to assess hip disability. Despite the use of the HOOS in clinical practice and research, psychometric analyses of the scale in a large dataset of patients have not been performed. As such, the purposes of this study were to assess the structural validity of the HOOS in patients who underwent a total hip arthroplasty. Data were obtained from the Surgical Outcome System (SOS) global registry. Confirmatory factor analysis (CFA) was conducted to assess the scale structure of the 40-item HOOS and exploratory factor analysis (EFA) was conducted to identify a parsimonious scale structure. The parsimonious model identified was subjected to multi-group and longitudinal invariance testing and LGC modeling. The original five-factor, 40-item HOOS did not meet recommended model fit indices values (CFI = 0.822, TLI = 0.809, IFI = 0.822, RMSEA = 0.085). Alternate model generation identified an alternative model (i.e., HOOS-9). Sound model fit was identified for the HOOS-9 (CFI = 0.974, TLI = 0.961, RMSEA = 0.046). Invariance testing criteria were also met between groups (i.e., age and sex) and across time. Lastly, a nonlinear growth trajectory was identified in responses pertaining to hip disability. The original scale structure of the 40-item HOOS was not supported. The HOOS-9 met contemporary model fit recommendations, along with multi-group and longitudinal invariance testing. Our findings support the preliminary use of the HOOS-9 to assess hip function and disability in research and clinical practice.
- Subjects
TOTAL hip replacement; RESEARCH methodology evaluation; QUESTIONNAIRES; RESEARCH evaluation; DESCRIPTIVE statistics; MULTIVARIATE analysis; PSYCHOMETRICS; RESEARCH methodology; STATISTICS; STATISTICAL reliability; FACTOR analysis; DATA analysis software
- Publication
Healthcare (2227-9032), 2024, Vol 12, Issue 17, p1789
- ISSN
2227-9032
- Publication type
Article
- DOI
10.3390/healthcare12171789