OPTIMI: Early Detection & Prevention

Institute for Response-Genetics, University of Zurich

Head: Prof. Dr. Hans H. Stassen

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Partners:
Everis, Spain
ETH, Switzerland
UZH, Switzerland
Freiburg, Germany
MA Systems, UK
Bristol, UK
Xiwrite, Italy
Ultrasis, UK
Jaume, Spain
Valencia, Spain
Lanzhou, China

 

EU-Grant (FP7):
248544

Early Detection and Prevention of Depression

Major depressive disorders (MDD) affect about 4-8% percent of the general population, causing the loss of the ability to work, to have close relationships, and to have a fulfilling life. Available treatments, though effective, have only modest response rates and, most disturbingly, the question of predicting treatment response in the individual patient is not answerable for any of the currently available therapeutic approaches. A considerable number of patients suffer from recurrent episodes of depression so that the early detection of relapse is key for prevention and the development of effective longterm therapies.

Speaking Behavior and Voice Sound Characteristics

Depression significantly reduces the dynamic expressiveness of human voices, thus greatly reducing inter-individual differences. As a direct consequence, the patients' voices become more similar to each other ("depressive voice"): The patients speak in a low voice, slowly, hesitatingly, monotonously, sometimes stuttering, whispering, try several times before they bring out a word, become mute in the middle of a sentence (Kraepelin 1921). During recovery, however, the patients' speaking behavior and voice sound characteristics return to "normal" values. In a series of clinical studies we found a close correlation in two thirds of patients between speech parameters on the one hand, and psychopathology scores on the other. Consequently, speech analyses allow one to monitor the time course of improvement (and possible deterioration) in these patients.



References

Moragrega I, Bridler R, Mohr C, Possenti M, Rochat D, Sanchez Parramon J, Stassen HH: Monitoring Mental Health and the Effects of Therapeutic Interventions through Self-Assessment Voice Analyses. Res Psychother. 2021, 24(3): 250-262 [get the article]
Bhake R, Kluckner V, Stassen HH, Russell GM, Leendertz J, Stevens K, Linthorst ACE, Lightman S: Continuous Free Cortisol Profiles — Circadian Rhythms in Healthy Men. J Clinical Endocrinology & Metabolism 2019; 104(12): 5935-5947
Braun S, Annovazzi C, Botella C, Bridler B, Camussi E, Delfino JP, Mohr C, Moragrega I, Papagno C, Pisoni A, Soler C, Seifritz E, Stassen HH: Assessing Chronic Stress, Coping Skills and Mood Disorders through Speech Analysis. A Self-Assessment "Voice App" for Laptops, Tablets, and Smartphones. Psychopathology 2016; 49(6): 406-419 [get the article]
Braun S, Botella C, Bridler R, Chmetz F, Delfino JP, Herzig D, Kluckner VJ, Mohr C, Moragrega I, Schrag Y, Seifritz E, Soler C, Stassen HH: Affective State and Voice: Cross-Cultural Assessment of Speaking Behavior and Voice Sound Characteristics; A Normative Multi-Center Study of 577+36 Healthy Subjects. Psychopathology 2014; 47(5): 327-340
Delfino JP, Barragán E, Botella C, Braun S, Bridler R, Camussi E, Chafrat V, Lott P, Mohr C, Moragrega I, Papagno C, Sanchez S, Seifritz E, Soler C, Stassen HH: Quantifying Insufficient Coping Behavior under Chronic Stress. A cross-cultural study of 1,303 students from Italy, Spain, and Argentina. Psychopathology 2015; 48: 230-239
Mohr C, Braun S, Bridler R, Chmetz F, Delfino JP, Kluckner VJ, Lott P, Schrag Y, Seifritz E, Stassen HH: Insufficient Coping Behavior under Chronic Stress and Vulnerability to Psychiatric Disorders. Psychopathology 2014; 47: 235-243
Stassen HH, Delfino JP, Kluckner VJ, Lott P, Mohr C: Vulnerabilität und psychische Erkrankung. Swiss Archives of Neurology and Psychiatry 2014; 165(5): 152-157
Zhang M, Bridler R, Mohr C, Moragrega I, Sun N, Xu Z, Yang Z, Possenti M, Stassen HH: Early Detection of the Risk of Developing Psychiatric Disorders: A Study of 461 Chinese University Students under Chronic Stress. Psychopathology 2019; 52(6): 367-377 [get the article]

 

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We have developed a «Depressive-Voice» App for the analysis of speaking behavior and voice sound characteristics as a function of time and in a language-independent way.
«Depressive-Voice» App: Get involved in health issues and health prevention!
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