Facial Disability Index in Adults With Peripheral Facial Palsy: Rasch Analysis and Suggestions for Refinement

Abstract

ObjectiveTo investigate the psychometric properties of the validated Italian version of the Facial Disability Index (FDI), a patient-reported outcome measure widely used to assess individuals with peripheral facial palsy. DesignMethodological research on cross-sectional data from a convenience sample. SettingOutpatient university rehabilitation clinic. ParticipantsA total of 168 (N=168) outpatients (66% female; mean age, 44±15 years) with peripheral facial palsy of diverse etiology (48% postsurgical, 31% Bell palsy, 8% posttraumatic, 3% congenital, 11% other medical conditions) and severity at the first visit. InterventionsNot applicable. Main Outcome MeasuresThe 2 FDI subscales, physical function (FDI-PHY) and social/well-being function (FDI-SWB), were separately analyzed using classical test theory methods and Rasch analysis. ResultsCronbach α was 0.79 in FDI-PHY and 0.74 in FDI-SWB, while item-rest correlation ranged from 0.36-0.67 in FDI-PHY and from 0.43-0.68 in FDI-SWB. In the FDI-PHY, we deleted 2 underused response categories, rescoring the remaining ones. In the FDI-SWB, some response categories did not function as expected by the Rasch model: their collapse into a 4-level format solved this problem. In each subscale, all items fitted the Rasch model except item 4 (eye tearing/becoming dry) in FDI-PHY that showed an unexpectedly high response variability. The person separation reliability of both subscales indicated that they are useful only for group-level judgments. In both subscales, principal component analysis of the residuals showed unidimensionality and absence of locally dependent items. No significant differential item functioning concerning sex, age, or time from paralysis emerged. ConclusionsOur study demonstrated overall positive psychometric characteristics of FDI except for the functioning of the response categories. We propose a refined version with 4 response categories only and related conversion graphs that may improve the interpretability, feasibility, and metric performance of this tool.