Literature DB >> 31839552

Voice patterns in schizophrenia: A systematic review and Bayesian meta-analysis.

Alberto Parola1, Arndis Simonsen2, Vibeke Bliksted2, Riccardo Fusaroli3.   

Abstract

Voice atypicalities have been a characteristic feature of schizophrenia since its first definitions. They are often associated with core negative symptoms such as flat affect and alogia, and with the social impairments seen in the disorder. This suggests that voice atypicalities may represent a marker of clinical features and social functioning in schizophrenia. We systematically reviewed and meta-analyzed the evidence for distinctive acoustic patterns in schizophrenia, as well as their relation to clinical features. We identified 46 articles, including 55 studies with a total of 1254 patients with schizophrenia and 699 healthy controls. Summary effect sizes (Hedges'g and Pearson's r) estimates were calculated using multilevel Bayesian modeling. We identified weak atypicalities in pitch variability (g = -0.55) related to flat affect, and stronger atypicalities in proportion of spoken time, speech rate, and pauses (g's between -0.75 and -1.89) related to alogia and flat affect. However, the effects were mostly modest (with the important exception of pause duration) compared to perceptual and clinical judgments, and characterized by large heterogeneity between studies. Moderator analyses revealed that tasks with a more demanding cognitive and social component showed larger effects both in contrasting patients and controls and in assessing symptomatology. In conclusion, studies of acoustic patterns are a promising but, yet unsystematic avenue for establishing markers of schizophrenia. We outline recommendations towards more cumulative, open, and theory-driven research.
Copyright © 2019. Published by Elsevier B.V.

Entities:  

Keywords:  Acoustic analysis; Biomarker; Machine learning; Negative symptoms; Social communication; Speech signal

Mesh:

Year:  2019        PMID: 31839552     DOI: 10.1016/j.schres.2019.11.031

Source DB:  PubMed          Journal:  Schizophr Res        ISSN: 0920-9964            Impact factor:   4.939


  14 in total

1.  A systematic review and Bayesian meta-analysis of the acoustic features of infant-directed speech.

Authors:  Christopher Cox; Christina Bergmann; Emma Fowler; Tamar Keren-Portnoy; Andreas Roepstorff; Greg Bryant; Riccardo Fusaroli
Journal:  Nat Hum Behav       Date:  2022-10-03

2.  Natural language processing methods are sensitive to sub-clinical linguistic differences in schizophrenia spectrum disorders.

Authors:  Reno Kriz; Sunghye Cho; Sunny X Tang; Suh Jung Park; Jenna Harowitz; Raquel E Gur; Mahendra T Bhati; Daniel H Wolf; João Sedoc; Mark Y Liberman
Journal:  NPJ Schizophr       Date:  2021-05-14

3.  Understanding communicative intentions in schizophrenia using an error analysis approach.

Authors:  Alberto Parola; Claudio Brasso; Rosalba Morese; Paola Rocca; Francesca M Bosco
Journal:  NPJ Schizophr       Date:  2021-02-26

Review 4.  Automated assessment of psychiatric disorders using speech: A systematic review.

Authors:  Daniel M Low; Kate H Bentley; Satrajit S Ghosh
Journal:  Laryngoscope Investig Otolaryngol       Date:  2020-01-31

5.  Pragmatics, Theory of Mind and executive functions in schizophrenia: Disentangling the puzzle using machine learning.

Authors:  Alberto Parola; Rogerio Salvini; Ilaria Gabbatore; Livia Colle; Laura Berardinelli; Francesca M Bosco
Journal:  PLoS One       Date:  2020-03-03       Impact factor: 3.240

6.  Distinctive prosodic features of people with autism spectrum disorder: a systematic review and meta-analysis study.

Authors:  Seyedeh Zahra Asghari; Sajjad Farashi; Saeid Bashirian; Ensiyeh Jenabi
Journal:  Sci Rep       Date:  2021-11-29       Impact factor: 4.379

7.  Using automated syllable counting to detect missing information in speech transcripts from clinical settings.

Authors:  Marama Diaz-Asper; Terje B Holmlund; Chelsea Chandler; Catherine Diaz-Asper; Peter W Foltz; Alex S Cohen; Brita Elvevåg
Journal:  Psychiatry Res       Date:  2022-07-05       Impact factor: 11.225

8.  Computer Vision-Based Assessment of Motor Functioning in Schizophrenia: Use of Smartphones for Remote Measurement of Schizophrenia Symptomatology.

Authors:  Anzar Abbas; Vijay Yadav; Emma Smith; Elizabeth Ramjas; Sarah B Rutter; Caridad Benavidez; Vidya Koesmahargyo; Li Zhang; Lei Guan; Paul Rosenfield; Mercedes Perez-Rodriguez; Isaac R Galatzer-Levy
Journal:  Digit Biomark       Date:  2021-01-21

9.  Multimodal assessment of communicative-pragmatic features in schizophrenia: a machine learning approach.

Authors:  Alberto Parola; Ilaria Gabbatore; Laura Berardinelli; Rogerio Salvini; Francesca M Bosco
Journal:  NPJ Schizophr       Date:  2021-05-24

10.  Facial and Vocal Markers of Schizophrenia Measured Using Remote Smartphone Assessments: Observational Study.

Authors:  Anzar Abbas; Bryan J Hansen; Vidya Koesmahargyo; Vijay Yadav; Paul J Rosenfield; Omkar Patil; Marissa F Dockendorf; Matthew Moyer; Lisa A Shipley; M Mercedez Perez-Rodriguez; Isaac R Galatzer-Levy
Journal:  JMIR Form Res       Date:  2022-01-21
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