Visual cognitive testing to predict speech-in-noise performance in individuals with normal hearing to mild hearing loss

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Abstract Introduction. Previous research has shown that speech performance correlates with cognitive test performance and can predict outcomes after cochlear implantation. Since cognitive abilities for processing acoustic information are difficult to assess in hearing-impaired patients, we hypothesize that cognitive abilities for processing visual information can serve as a surrogate. Here, we validate a test battery for cognitive information processing in the visual system in subjects with normal hearing and mild hearing loss and assess their performance in processing speech in noisy listening environments. Methods Forty test subjects were recruited and consented to the study. For patients included in the study, hearing was assessed using pure-tone audiometry and a speech-in-noise test (QuickSIN). Cognitive tests included the Stroop Test and the Trail Making Test (TMT). Other tests that distorted the input signal and assessed word working memory included the word scramble (WS) and visual signal-to-noise ratio (visual SNR) tests. Results The correlation coefficient for the Stroop Test, which evaluates incongruent information naming colors, and the QuickSIN SNR loss was 0.71, while the correlation coefficient for the TMT-A, which involves connecting numbers from 1 through 25, was 0.68. The averaged results of both tests correlated with the QuickSIN SNR loss with a correlation coefficient of 0.75. Of the residuals, 90% ranged from − 1.5 to + 1.5 dB. Little to no correlation with the speech and noise test was found for the other tests. Discussion Visual tests for cognitive performance correlate well with outcomes from the QuickSIN SNR loss, with better predictive power after Stroop and TMT test results were averaged.
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Visual cognitive testing to predict speech-in-noise performance in individuals with normal hearing to mild hearing loss | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Visual cognitive testing to predict speech-in-noise performance in individuals with normal hearing to mild hearing loss Maaz S. Haji, Irina Cheng, Claus-Peter Richter This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9307655/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract Introduction. Previous research has shown that speech performance correlates with cognitive test performance and can predict outcomes after cochlear implantation. Since cognitive abilities for processing acoustic information are difficult to assess in hearing-impaired patients, we hypothesize that cognitive abilities for processing visual information can serve as a surrogate. Here, we validate a test battery for cognitive information processing in the visual system in subjects with normal hearing and mild hearing loss and assess their performance in processing speech in noisy listening environments. Methods Forty test subjects were recruited and consented to the study. For patients included in the study, hearing was assessed using pure-tone audiometry and a speech-in-noise test (QuickSIN). Cognitive tests included the Stroop Test and the Trail Making Test (TMT). Other tests that distorted the input signal and assessed word working memory included the word scramble (WS) and visual signal-to-noise ratio (visual SNR) tests. Results The correlation coefficient for the Stroop Test, which evaluates incongruent information naming colors, and the QuickSIN SNR loss was 0.71, while the correlation coefficient for the TMT-A, which involves connecting numbers from 1 through 25, was 0.68. The averaged results of both tests correlated with the QuickSIN SNR loss with a correlation coefficient of 0.75. Of the residuals, 90% ranged from − 1.5 to + 1.5 dB. Little to no correlation with the speech and noise test was found for the other tests. Discussion Visual tests for cognitive performance correlate well with outcomes from the QuickSIN SNR loss, with better predictive power after Stroop and TMT test results were averaged. Health sciences/Health care Health sciences/Medical research Biological sciences/Neuroscience Top-down signal processing cognitive testing speech in noise performance prediction hearing loss bottom-up signal processing auditory Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 27 Apr, 2026 Reviews received at journal 24 Apr, 2026 Reviews received at journal 16 Apr, 2026 Reviewers agreed at journal 12 Apr, 2026 Reviewers agreed at journal 11 Apr, 2026 Reviewers agreed at journal 10 Apr, 2026 Reviewers agreed at journal 09 Apr, 2026 Reviewers invited by journal 09 Apr, 2026 Editor invited by journal 09 Apr, 2026 Editor assigned by journal 04 Apr, 2026 Submission checks completed at journal 04 Apr, 2026 First submitted to journal 02 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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