Auditory and Cognitive Factors Underlying Individual Differences in Aided Speech-Understanding among Older Adults

• Main Authors: Larry E. Humes, Gary R. Kidd, Jennifer J. Lentz
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2013-10-01
• Series: Frontiers in Systems Neuroscience
• Subjects: Aging; Presbycusis; Amplification; Psychoacoustics; speech recognition
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fnsys.2013.00055/full

This study was designed to address individual differences in aided speech understanding among a relatively large group of older adults. The group of older adults consisted of 98 adults (50 female and 48 male) ranging in age from 60 to 86 (mean = 69.2). Hearing loss was typical for this age group and about 90% had not worn hearing aids. All subjects completed a battery of tests, including cognitive (6 measures), psychophysical (17 measures), and speech-understanding (9 measures), as well as the Speech, Spatial and Qualities of Hearing (SSQ) self-report scale. Most of the speech-understanding measures made use of competing speech and the non-speech psychophysical measures were designed to tap phenomena thought to be relevant for the perception of speech in competing speech (e.g., stream segregation, modulation-detection interference). All measures of speech understanding were administered with spectral shaping applied to the speech stimuli to fully restore audibility through at least 4000 Hz. The measures used were demonstrated to be reliable in older adults and, when compared to a reference group of 28 young normal-hearing adults, age-group differences were observed on many of the measures. Principal-components factor analysis was applied successfully to reduce the number of independent and dependent (speech understanding) measures for a multiple-regression analysis. Doing so yielded one global cognitive-processing factor and five non-speech psychoacoustic factors (hearing loss, dichotic signal detection, multi-burst masking, stream segregation, and modulation detection) as potential predictors. To this set of six potential predictor variables were added subject age, Environmental Sound Identification (ESI), and performance on the text-recognition-threshold (TRT) task (a visual analog of interrupted speech recognition). These variables were used to successfully predict one global aided speech-understanding factor, accounting for about 60% of the variance.