Psychometric Properties of the Voice Handicap Index-10 in Kannada.

OBJECTIVES

This study aimed to derive the 10-item voice handicap index in the Kannada language (VHI-K10) from the existing VHI-30 in Kannada (VHI-K30). We also aimed to examine several psychometric properties of the newly derived VHI-K10, such as internal consistency, reliability, concurrent validity, discriminant validity, and diagnostic accuracy.

METHODS

Initially, VHI-K10 was derived from the existing VHI-K30 through item reduction, consistent with the recommendations for item reduction of the voice handicap index. This newly derived VHI-K10 was administered to 273 individuals (199 individuals with dysphonia and 74 individuals with normal voice quality). We also obtained phonation and reading samples from the participants. The obtained data were subjected to appropriate statistical analysis to determine several psychometric properties.

RESULTS

The newly derived VHI-K10 was found to have a strong internal consistency (Cronbach's α = 0.93). We also found strong test-retest reliability for VHI-K10, with an intraclass correlation coefficient of 0.933. There was a strong statistically significant correlation between the VHI-K10 and the existing VHI-K30 for both individuals with dysphonia (ρ = 0.924, P < 0.001) and individuals with normal voice quality (ρ = 0.798, P < 0.001). However, the correlation of VHI-K10 with the auditory-perceptual measure of GRBAS was fair (ρ = 0.353, P < 0.001) for individuals with dysphonia and was not statistically significant for individuals with normal voice quality. Further, the diagnostic accuracy of VHI-K10 was found to be excellent, with an area under the curve (AROC) value of 0.926 with a cut-off point of ≥6.5, which was slightly superior to that of VHI-K30 (AROC = 0.909, cut-off point ≥21.5).

CONCLUSIONS

The shortened 10-item version of the voice handicap index in Kannada is consistent with versions of the VHI-10 in other languages. This version of the VHI-10 in Kannada is found to be a robust tool with strong psychometric properties.