The purpose of the current study was to estimate the minimal clinically important difference (MCID) of sentence intelligibility in control speakers and in speakers with dysarthria due to multiple sclerosis (MS) and Parkinson's disease (PD). Sixteen control speakers, 16 speakers with MS, and 16 speakers with PD were audio-recorded reading aloud sentences in habitual, clear, fast, loud, and slow speaking conditions. Two hundred forty nonexpert crowdsourced listeners heard paired conditions of the same sentence content from a speaker and indicated if one condition was more understandable than another. Listeners then used the Global Ratings of Change (GROC) Scale to indicate how much more understandable that condition was than the other. Listener ratings were compared with objective intelligibility scores obtained previously via orthographic transcriptions from nonexpert listeners. Receiver operating characteristic (ROC) curves and average magnitude of intelligibility difference per level of the GROC Scale were evaluated to determine the sensitivity, specificity, and accuracy of potential cutoff scores in intelligibility for establishing thresholds of important change. MCIDs derived from the ROC curves were invalid. However, the average magnitude of intelligibility difference derived valid and useful thresholds. The MCID of intelligibility was determined to be about 7% for a small amount of difference and about 15% for a large amount of difference. This work demonstrates the feasibility of the novel experimental paradigm for collecting crowdsourced perceptual data to estimate MCIDs. Results provide empirical evidence that clinical tools for the perception of intelligibility by nonexpert listeners could consist of three categories, which emerged from the data ("no difference," "a little bit of difference," "a lot of difference"). The current work is a critical step toward development of a universal language with which to evaluate changes in intelligibility as a result of neurological injury, disease progression, and speech-language therapy.
Read full abstract