Understanding Excessive SNR Loss in Hearing-Impaired Listeners

Abstract

Background: Traditional audiometric measures, such as pure-tone thresholds or unaided word-recognition in quiet, appear to be of marginal use in predicting speech understanding by hearing-impaired (HI) individuals in background noise with or without amplification. Suprathreshold measures of auditory function (tolerance of noise, temporal and frequency resolution) appear to contribute more to success with amplification and may describe more effectively the distortion component of hearing. However, these measures are not typically measured clinically. When combined with measures of audibility, suprathreshold measures of auditory distortion may provide a much more complete understanding of speech deficits in noise by HI individuals. Purpose: The primary goal of this study was to investigate the relationship among measures of speech recognition in noise, frequency selectivity, temporal acuity, modulation masking release, and informational masking in adult and elderly patients with sensorineural hearing loss to determine whether peripheral distortion for suprathreshold sounds contributes to the varied outcomes experienced by patients with sensorineural hearing loss listening to speech in noise. Research Design: A correlational study. Study Sample: Twenty-seven patients with sensorineural hearing loss and four adults with normal hearing were enrolled in the study. Data Collection and Analysis: The data were collected in a sound attenuated test booth. For speech testing, subjects' verbal responses were scored by the experimenter and entered into a custom computer program. For frequency selectivity and temporal acuity measures, subject responses were recorded via a touch screen. Simple correlation, step-wise multiple linear regression analyses and a repeated analysis of variance were performed. Results: Results showed that the signal-to-noise ratio (SNR) loss could only be partially predicted by a listener's thresholds or audibility measures such as the Speech Intelligibility Index (SII). Correlations between SII and SNR loss were higher using the Hearing-in-Noise Test (HINT) than the Quick Speech-in-Noise test (QSIN) with the SII accounting for 71% of the variance in SNR loss for the HINT but only 49% for the QSIN. However, listener age and the addition of suprathreshold measures improved the prediction of SNR loss using the QSIN, accounting for nearly 71% of the variance. Conclusions: Two standard clinical speech-in-noise tests, QSIN and HINT, were used in this study to obtain a measure of SNR loss. When administered clinically, the QSIN appears to be less redundant with hearing thresholds than the HINT and is a better indicator of a patient's suprathreshold deficit and its impact on understanding speech in noise. Additional factors related to aging, spectral resolution, and, to a lesser extent, temporal resolution improved the ability to predict SNR loss measured with the QSIN. For the HINT, a listener's audibility and age were the only two significant factors. For both QSIN and HINT, roughly 25–30% of the variance in individual differences in SNR loss (i.e., the dB difference in SNR between an individual HI listener and a control group of NH listeners at a specified performance level, usually 50% word or sentence recognition) remained unexplained, suggesting the need for additional measures of suprathreshold acuity (e.g., sensitivity to temporal fine structure) or cognitive function (e.g., memory and attention) to further improve the ability to understand individual variability in SNR loss.