Psychophysical and EEG measures predict speech-in-noise ability better than pure-tone audiometry

Evidence

The regression indicated that QuickSIN scores were best predicted by a combination of all variables except the hearing thresholds (R 2 = 64.4, F (4,26) = 6.32, p = 0.004). A follow-up standard linear regression using the four predictors identified by the best-subsets procedure echoed these results, although TFS sensitivity was not a significant factor. The main model was significant (R 2 = 41.8, F (4,26) = 4.49, p = 0.007), with age accounting for most of the variance in the model (18.1 %), followed by the stimulus encoding accuracy variables contributing 13.7 and 10.0 % for the modulated and complex harmonic tones respectively. When the pure-tone average hearing thresholds were added to the model, they contributed only 2 % variance. — Dijk, Pim van, Physiology, Psychoacoustics and…, 4187

Categorization

Category: Causal Relationships

• XREF: Connects to the growing ‘hidden hearing loss’ literature arguing audiograms miss suprathreshold deficits that explain speech-in-noise complaints.
• SEED: Angle for an explainer: why two people with identical normal audiograms can have vastly different real-world hearing — the objective-measure story.

Related

• Better speech-in-noise ability correlated with worse brainstem encoding (similarity 0.87)
• Aging impairs speech-in-noise ability beyond what hearing thresholds predict (similarity 0.86)
• TFS sensitivity predicts speech-in-noise ability among normally hearing adults (similarity 0.84)
• Audiometric pure-tone thresholds predict speech intelligibility even after sensitivity adjustment (similarity 0.84)
• Speech-in-speech intelligibility depends on non-auditory factors beyond audibility alone (similarity 0.84)
• Objective hearing measures require linking perception, physiology, and speech ability. (similarity 0.84)
• Audiograms flatten the curved hearing threshold into a straight reference line (similarity 0.83)
• Meaningful speech-in-noise benefit requires double the detectable SNR change (similarity 0.83)
• The audiogram measures only detection thresholds, so it misses everyday speech-in-noise ability. (similarity 0.83)
• Pure-tone average hearing sensitivity still predicts intelligibility even at equalized levels (similarity 0.82)
• Speech-in-noise ability is measured as SNR loss relative to normal hearing (similarity 0.82)
• Hearing thresholds correlate more strongly with speech intelligibility at low signal-to-noise ratios. (similarity 0.82)
• Speech-in-noise ability is scored as the added SNR a listener needs (similarity 0.82)
• A higher required signal-to-noise ratio indicates worse speech-in-noise performance. (similarity 0.82)
• Envelope-following response measures capture hearing aspects beyond the audiometric threshold (similarity 0.82)