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Multilingual markers of depression in remotely collected speech samples: A preliminary analysis.

Authors :
Cummins, Nicholas
Dineley, Judith
Conde, Pauline
Matcham, Faith
Siddi, Sara
Lamers, Femke
Carr, Ewan
Lavelle, Grace
Leightley, Daniel
White, Katie M.
Oetzmann, Carolin
Campbell, Edward L.
Simblett, Sara
Bruce, Stuart
Haro, Josep Maria
Penninx, Brenda W.J.H.
Ranjan, Yatharth
Rashid, Zulqarnain
Stewart, Callum
Folarin, Amos A.
Source :
Journal of Affective Disorders. Nov2023, Vol. 341, p128-136. 9p.
Publication Year :
2023

Abstract

Speech contains neuromuscular, physiological and cognitive components, and so is a potential biomarker of mental disorders. Previous studies indicate that speaking rate and pausing are associated with major depressive disorder (MDD). However, results are inconclusive as many studies are small and underpowered and do not include clinical samples. These studies have also been unilingual and use speech collected in controlled settings. If speech markers are to help understand the onset and progress of MDD, we need to uncover markers that are robust to language and establish the strength of associations in real-world data. We collected speech data in 585 participants with a history of MDD in the United Kingdom, Spain, and Netherlands as part of the RADAR-MDD study. Participants recorded their speech via smartphones every two weeks for 18 months. Linear mixed models were used to estimate the strength of specific markers of depression from a set of 28 speech features. Increased depressive symptoms were associated with speech rate, articulation rate and intensity of speech elicited from a scripted task. These features had consistently stronger effect sizes than pauses. Our findings are derived at the cohort level so may have limited impact on identifying intra-individual speech changes associated with changes in symptom severity. The analysis of features averaged over the entire recording may have underestimated the importance of some features. Participants with more severe depressive symptoms spoke more slowly and quietly. Our findings are from a real-world, multilingual, clinical dataset so represent a step-change in the usefulness of speech as a digital phenotype of MDD. • Collected of a unique multilingual clinical speech dataset • Identified three multilingual speech phenotypes of MDD • Pausing not universally impacted by MDD across the three languages • Slowing of speech is most likely due to psychomotor impairments. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01650327
Volume :
341
Database :
Academic Search Index
Journal :
Journal of Affective Disorders
Publication Type :
Academic Journal
Accession number :
171990681
Full Text :
https://doi.org/10.1016/j.jad.2023.08.097