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Abstract: Rasch analysis of OSDI

OSDI is definitely a less than perfect tool, but hey, it's the best we got (if I'm wrong please email me a link to something better) for the time being. We patients must have a scientifically validated way to quantify our symptoms or doctors simply won't take our pain seriously (especially in the absence of dramatic clinical signs). - This is also a big issue in getting drugs FDA approved - how can you prove improvement to both signs and symptoms if you can't quantify symptoms reliably?

Rasch Analysis of the Ocular Surface Disease Index (OSDI).

The Ocular Surface Disease Index (OSDI) is a 12-item scale for the assessment of symptoms related to dry eye disease and their effect on vision. Its reliability and validity has been investigated within the classical test theory framework and, more recently, using Rasch analysis. The purpose of the present analysis was to more completely investigate the functioning of its response category structure, the validity of its three subscales, and the unidimensionality of the latent construct it is intended to assess.

Responses to the OSDI from 172 women participating in the Dry Eye in Postmenopause (DEiM) study who had previously been diagnosed with dry eye or reported significant ocular irritation and dryness were analyzed. Response category structure and item fit statistics were evaluated for assessment of model fit. Person separation statistics were used to examine the validity of the subscales. Unidimensionality was assessed by principle component analysis of model residuals.

Results:The recommended five-category response structure resulted in disordered response thresholds. A four category structure resulted in ordered thresholds. Item infit statistics were acceptable for all 12 items. Person separation with this category structure was adequate, with person separation index of 2.16. None of the three subscales demonstrated adequate person separation. PCA showed one other significant factor onto which the three environmental items loaded significantly.

Conclusions:All items demonstrated acceptable fit to the model after collapsing categories to order the response thresholds. The original subscales did not prove valid, and there is some evidence of multidimensionality and poor targeting.

Invest Ophthalmol Vis Sci. 2011 Sep 24. [Epub ahead of print]
Dougherty BE, Nichols JJ, Nichols KK.
The Ohio State University College of Optometry, Columbus, OH.