“You Say Severe, I Say Mild”: Toward an Empirical Classification of Dysarthria Severity

Purpose: The main purpose of this study was to create an empirical classification system for speech severity in patients with dysarthria secondary to amyotro-phic lateral sclerosis (ALS) by exploring the reliability and validity of speech-language pathologists’ (SLPs’) ratings of dysarthric speech. Method: Ten SLPs listened to speech samples from 52 speakers with ALS and 20 healthy control speakers. SLPs were asked to rate the speech severity of the speakers using five response options: normal, mild, moderate, severe, and pro-found. Four severity-surrogate measures were also calculated: SLPs transcribed the speech samples for the calculation of speech intelligibility and rated the effort it took to understand the speakers on a visual analog scale. In addition, speaking rate and intelligible speaking rate were calculated for each speaker. Intrarater and interrater reliability were calculated for each measure. We explored the validity of clinician-based severity ratings by comparing them to the severity-surrogate measures. Receiver operating characteristic (ROC) curves were conducted to create optimal cutoff points for defining dysarthria severity categories. Results: Intrarater and interrater reliability for the clinician-based severity ratings were excellent and were comparable to reliability for the severity-surrogate measures explored. Clinician severity ratings were strongly associated with all severity-surrogate measures, suggesting strong construct validity. We also provided a range of values for each severity-surrogate measure within each severity category based on the cutoff points obtained from the ROC analyses. Conclusions: Clinician severity ratings of dysarthric speech are reliable and valid. We discuss the underlying challenges that arise when selecting a stratifi-cation measure and offer recommendations for a classification scheme when stratifying patients and research participants into speech severity categories.