000128208 001__ 128208
000128208 005__ 20241125101200.0
000128208 0247_ $$2doi$$a10.1016/j.jad.2023.08.097
000128208 0248_ $$2sideral$$a135446
000128208 037__ $$aART-2023-135446
000128208 041__ $$aeng
000128208 100__ $$aCummins, Nicholas
000128208 245__ $$aMultilingual markers of depression in remotely collected speech samples: A preliminary analysis
000128208 260__ $$c2023
000128208 5060_ $$aAccess copy available to the general public$$fUnrestricted
000128208 5203_ $$aBackground: 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. Methods: 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. Results: 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. Limitations: 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. Conclusions: 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.
000128208 536__ $$9info:eu-repo/grantAgreement/EC/H2020/115902/EU/Remote Assessment of Disease and Relapse in Central Nervous System Disorders/RADAR-CNS$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 115902-RADAR-CNS
000128208 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000128208 590__ $$a4.9$$b2023
000128208 592__ $$a2.082$$b2023
000128208 591__ $$aCLINICAL NEUROLOGY$$b35 / 280 = 0.125$$c2023$$dQ1$$eT1
000128208 593__ $$aPsychiatry and Mental Health$$c2023$$dQ1
000128208 591__ $$aPSYCHIATRY$$b38 / 279 = 0.136$$c2023$$dQ1$$eT1
000128208 593__ $$aClinical Psychology$$c2023$$dQ1
000128208 591__ $$aPSYCHIATRY$$b38 / 279 = 0.136$$c2023$$dQ1$$eT1
000128208 594__ $$a10.9$$b2023
000128208 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000128208 700__ $$aDineley, Judith
000128208 700__ $$aConde, Pauline
000128208 700__ $$aMatcham, Faith
000128208 700__ $$aSiddi, Sara
000128208 700__ $$aLamers, Femke
000128208 700__ $$aCarr, Ewan
000128208 700__ $$aLavelle, Grace
000128208 700__ $$aLeightley, Daniel
000128208 700__ $$aWhite, Katie M.
000128208 700__ $$aOetzmann, Carolin
000128208 700__ $$aCampbell, Edward L.
000128208 700__ $$aSimblett, Sara
000128208 700__ $$aBruce, Stuart
000128208 700__ $$aHaro, Josep Maria
000128208 700__ $$aPenninx, Brenda W.J.H.
000128208 700__ $$aRanjan, Yatharth
000128208 700__ $$aRashid, Zulqarnain
000128208 700__ $$aStewart, Callum
000128208 700__ $$aFolarin, Amos A.
000128208 700__ $$0(orcid)0000-0003-1272-0550$$aBailón, Raquel$$uUniversidad de Zaragoza
000128208 700__ $$aSchuller, Björn W.
000128208 700__ $$aWykes, Til
000128208 700__ $$aVairavan, Srinivasan
000128208 700__ $$aDobson, Richard J.B.
000128208 700__ $$aNarayan, Vaibhav A.
000128208 700__ $$aHotopf, Matthew
000128208 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac.
000128208 773__ $$g341 (2023), 128-136$$pJ. affect. disord.$$tJournal of Affective Disorders$$x0165-0327
000128208 8564_ $$s1735313$$uhttps://zaguan.unizar.es/record/128208/files/texto_completo.pdf$$yVersión publicada
000128208 8564_ $$s2227457$$uhttps://zaguan.unizar.es/record/128208/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000128208 909CO $$ooai:zaguan.unizar.es:128208$$particulos$$pdriver
000128208 951__ $$a2024-11-22-12:11:25
000128208 980__ $$aARTICLE