Acoustic speech features are associated with late‐life depression and apathy symptoms: Preliminary findings
Abstract BACKGROUND Late‐life depression (LLD) is a heterogenous disorder related to cognitive decline and neurodegenerative processes, raising a need for the development of novel biomarkers. We sought to provide preliminary evidence for acoustic speech signatures sensitive to LLD and their relation...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/dad2.70055 |
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| Summary: | Abstract BACKGROUND Late‐life depression (LLD) is a heterogenous disorder related to cognitive decline and neurodegenerative processes, raising a need for the development of novel biomarkers. We sought to provide preliminary evidence for acoustic speech signatures sensitive to LLD and their relationship to depressive dimensions. METHODS Forty patients (24 female, aged 65–82 years) were assessed with the Geriatric Depression Scale (GDS). Vocal features were extracted from speech samples (reading a pre‐written text) and tested as classifiers of LLD using random forest and XGBoost models. Post hoc analyses examined the relationship between these acoustic features and specific depressive dimensions. RESULTS The classification models demonstrated moderate discriminative ability for LLD with receiver operating characteristic = 0.78 for random forest and 0.84 for XGBoost in an out‐of‐sample testing set. The top classifying features were most strongly associated with the apathy dimension (R2 = 0.43). DISCUSSION Acoustic vocal features that may support the diagnosis of LLD are preferentially associated with apathy. Highlights The depressive dimensions in late‐life depression (LLD) have different cognitive correlates, with apathy characterized by more pronounced cognitive impairment. Acoustic speech features can predict LLD. Using acoustic features, we were able to train a random forest model to predict LLD in a held‐out sample. Acoustic speech features that predict LLD are preferentially associated with apathy. These results indicate a predominance of apathy in the vocal signatures of LLD, and suggest that the clinical heterogeneity of LLD should be considered in development of acoustic markers. |
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| ISSN: | 2352-8729 |