TY - JOUR
T1 - Acoustic speech features are associated with late-life depression and apathy symptoms
T2 - Preliminary findings
AU - Harlev, Daniel
AU - Singer, Shir
AU - Goldshalger, Maya
AU - Wolpe, Noham
AU - Bergmann, Eyal
N1 - Publisher Copyright: © 2025 The Author(s). Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring published by Wiley Periodicals, LLC on behalf of Alzheimer's Association.
PY - 2025/1/1
Y1 - 2025/1/1
N2 - 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.
AB - 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.
KW - acoustic vocal features
KW - aging
KW - apathy
KW - classification models
KW - late-life depression
UR - http://www.scopus.com/inward/record.url?scp=85215525925&partnerID=8YFLogxK
U2 - https://doi.org/10.1002/dad2.70055
DO - https://doi.org/10.1002/dad2.70055
M3 - مقالة
SN - 2352-8729
VL - 17
JO - Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
JF - Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
IS - 1
M1 - e70055
ER -