Disease-related differential item functioning in the work instability scale for rheumatoid arthritis: converging results from three methods

Publication type
Journal article
Tang K
Date published
2011 Jan 25
Arthritis Care & Research
Open Access?

OBJECTIVE: The 23-item Work Instability Scale for Rheumatoid Arthritis (RA-WIS) is a promising measure to assess risk for future work disability. Validated in both rheumatoid arthritis (RA) and osteoarthritis (OA), it has high potential for cross-disease applications. Our objective was to examine disease-related differential item functioning (DIF) in the RA-WIS. METHODS: Workers with RA (n = 120) or OA (n = 130) were recruited from 3 sites and completed a questionnaire consisting of demographic and health- and work-related variables, including the RA-WIS (range 0-23, where 23 = highest work instability). Multiple DIF detection methods were applied for comparability: 1) Mantel-Haenszel and Breslow-Day procedures, 2) hierarchical 3-step sequential logistic regression procedure, and 3) a 1-parameter item response theory approach (Rasch analysis). Both tests of significance (chi-square and F tests) and effect size statistics (Delta(MH) , DeltaR(2) ) were assessed to confirm items demonstrating uniform or nonuniform DIF. A 2-step purification procedure was applied to establish a DIF-free conditioning variable (total RA-WIS score) for DIF analyses. The resultant impact of disease-related DIF at the scale level was also evaluated. RESULTS: All 3 DIF detection methods converged to reveal 3 RA-WIS items as having significant disease-related uniform DIF. Two items ('difficulty opening doors' and 'pressure on hand') were more likely affirmed in RA, while 1 item ('very stiff') was more likely affirmed in OA. Overall, only a marginal impact at the scale level was found due to a small proportion of scale items exhibiting DIF and the bidirectional nature of DIF effects. CONCLUSION: RA-WIS scores can be directly compared between RA and OA without significant concerns for DIF-related measurement bias