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Machine-learning modeling examines the relationship between self-perception and audiometric data, suggesting clinical implications.
The results indicate that subjective awareness is strongly tied to the size of the hearing difference between ears rather than its direction and becomes more reliable with greater asymmetry. These findings indicate that a simple "better ear" self-report item captures meaningful audiometric information, supporting its potential use in clinical triage and public health surveillance, while also highlighting the need for caution in cases of mild asymmetry where misclassification is more likely.
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Georgios P. Georgiou (2026) studied this question.
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