고신대학교 언어치료학과 배인호 교수가 ‘The usefulness of multi voice evaluation: Development of a model for predicting a degree of dysphonia’로 SCI급 학술지인 Journal of voice에 이름을 올렸다. 부산대학교병원과 공동연구한 이 논문은 음성평가 다중변인을 통하여 발성장애 환자의 심한정도를 예측하는 모델을 개발한 것으로 발성장애 평가에 활용활 수 있는 새로운 지표를 개발하였다는데 의미가 있다.

Summary: 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 selfreport 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.

Key Words: Multi-assessment−Predicting voice severity−Voice disorder.