ArticleBMC psychiatry2025
The relationship between cognitive impairment and acoustic features in major depressive disorder: a longitudinal cohort study.
Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
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7 authors.
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Abstract
introductionCognitive impairments, especially in executive function, attention, and working memory, are prevalent in major depressive disorder (MDD). While studies has identified brain areas involved in these deficits, the connection between cognitive function and acoustic features of speech remains underexplored. This study examines this relationship in MDD.
methodsA longitudinal cohort study was conducted with 53 participants diagnosed with MDD (DSM-IV). Cognitive performance was assessed using the Trail Making Test (TMT), Digit Span (DS), Continuous Performance Test (CPT), and Symbol Coding (SC). Speech samples were analyzed for 6,373 vocal features across six domains: energy, pitch, prosody, spectral, voice quality, and others. Spearman's correlation and principal component analysis (PCA) assessed the link between cognitive scores and speech features. Regression analyses explored the predictive value of speech features for cognitive performance.
resultsSignificant cognitive impairments in executive function and attention were observed. Strong correlations were found between spectral speech features, particularly high-frequency components, and sustained attention and executive function. PCA showed that depression severity independently predicted certain vocal feature components. Notably, speech features related to cognitive impairment remained consistent across different cognitive tasks, and treatment-induced changes were observed over 8 weeks.
conclusionsThis study demonstrates that speech features, particularly spectral components, reflect cognitive impairment in MDD, offering promising non-invasive biomarkers for monitoring cognitive function in depression. Larger studies with extended follow-up are needed to explore their potential in predicting cognitive outcomes in MDD.
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