Objectives: The purposes of this study were (1) to analyze the usefulness of self-report questionnaires, acoustic analysis, and auditory perceptual assessment for screening voice problems; and (2) to develop a new model for predicting a comprehensive voice severity using multi-assessment.
Methods: A total of 306 voice samples were analyzed in this study (typical group, n = 72; dysphonia group, n = 234). We performed a receiver operating characteristic analysis to determine the cutoff values of auditory perceptual assessments (visual analog scale), acoustic parameters (spectral- and cepstral-based analyses), and self-report questionnaires for screening voice disorders. We also performed a stepwise multiple regression analysis to verify which combination of parameters (acoustic parameters, and self-report questionnaires) could best predict perceived voice severity.
Results: We verified that most of the variables analyzed were useful for voice evaluation, and found to be useful for screening voice problems. Of these, a five-variable model was a useful to predict perceived voice severity (mean R2 = .807). The five-variable model consisted of acoustic parameters based on cepstral analysis (cepstral peak prominences in connected speech and sustained vowel task, and low versus high-frequency spectral energy ratio in connected speech task) and self-report questionnaires (total score of the Voice Handicap Index, and rumination score of the Voice Catastrophization Index).
Conclusion: We verified that most of the variables were useful for screening dysphonia and five-variable model was a useful to predict perceived voice severity. The five-variable model could be used as an objective criterion for predicting voice severity.
Keywords: Multi-assessment–Predicting voice severity–Voice disorder.
Copyright © 2020 The Voice Foundation. Published by Elsevier Inc. All rights reserved.