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Voice Patterns as Markers of Schizophrenia: Building a Cumulative Generalizable Approach Via a Cross-Linguistic and Meta-analysis Based Investigation.
Parola, Alberto; Simonsen, Arndis; Lin, Jessica Mary; Zhou, Yuan; Wang, Huiling; Ubukata, Shiho; Koelkebeck, Katja; Bliksted, Vibeke; Fusaroli, Riccardo.
Afiliação
  • Parola A; Department of Linguistics, Cognitive Science and Semiotics, Aarhus University, Aarhus, Denmark.
  • Simonsen A; The Interacting Minds Center, Institute of Culture and Society, Aarhus University, Aarhus, Denmark.
  • Lin JM; Department of Psychology, University of Turin, Turin, Italy.
  • Zhou Y; The Interacting Minds Center, Institute of Culture and Society, Aarhus University, Aarhus, Denmark.
  • Wang H; Psychosis Research Unit, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
  • Ubukata S; Department of Linguistics, Cognitive Science and Semiotics, Aarhus University, Aarhus, Denmark.
  • Koelkebeck K; The Interacting Minds Center, Institute of Culture and Society, Aarhus University, Aarhus, Denmark.
  • Bliksted V; Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
  • Fusaroli R; Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China.
Schizophr Bull ; 49(Suppl_2): S125-S141, 2023 03 22.
Article em En | MEDLINE | ID: mdl-36946527
BACKGROUND AND HYPOTHESIS: Voice atypicalities are potential markers of clinical features of schizophrenia (eg, negative symptoms). A recent meta-analysis identified an acoustic profile associated with schizophrenia (reduced pitch variability and increased pauses), but also highlighted shortcomings in the field: small sample sizes, little attention to the heterogeneity of the disorder, and to generalizing findings to diverse samples and languages. STUDY DESIGN: We provide a critical cumulative approach to vocal atypicalities in schizophrenia, where we conceptually and statistically build on previous studies. We aim at identifying a cross-linguistically reliable acoustic profile of schizophrenia and assessing sources of heterogeneity (symptomatology, pharmacotherapy, clinical and social characteristics). We relied on previous meta-analysis to build and analyze a large cross-linguistic dataset of audio recordings of 231 patients with schizophrenia and 238 matched controls (>4000 recordings in Danish, German, Mandarin and Japanese). We used multilevel Bayesian modeling, contrasting meta-analytically informed and skeptical inferences. STUDY RESULTS: We found only a minimal generalizable acoustic profile of schizophrenia (reduced pitch variability), while duration atypicalities replicated only in some languages. We identified reliable associations between acoustic profile and individual differences in clinical ratings of negative symptoms, medication, age and gender. However, these associations vary across languages. CONCLUSIONS: The findings indicate that a strong cross-linguistically reliable acoustic profile of schizophrenia is unlikely. Rather, if we are to devise effective clinical applications able to target different ranges of patients, we need first to establish larger and more diverse cross-linguistic datasets, focus on individual differences, and build self-critical cumulative approaches.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Esquizofrenia / Voz Tipo de estudo: Diagnostic_studies / Prognostic_studies / Systematic_reviews Limite: Humans Idioma: En Revista: Schizophr Bull Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Dinamarca

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Esquizofrenia / Voz Tipo de estudo: Diagnostic_studies / Prognostic_studies / Systematic_reviews Limite: Humans Idioma: En Revista: Schizophr Bull Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Dinamarca