SynthesisSchizophrenia bulletin2023
Voice Patterns as Markers of Schizophrenia: Building a Cumulative Generalizable Approach Via a Cross-Linguistic and Meta-analysis Based Investigation.
Synthesis in Schizophrenia bulletin, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Fundamental Frequency of Voice as a Potential Stress Biomarker: A Systematic Review and Meta-Analysis.Stress and health : journal of the International Society for the Investigation of Stress · 2025Pooled it
- Article
- Mobile Technology for Real-Life Assessment of Positive and Negative Symptoms as well as Stress Among Individuals With Early Psychosis: A Scoping Review.Early intervention in psychiatry · 2026Article
- Artificial Intelligence in Drug Discovery and Development: Raising Quality per Decision.Pharmacopsychiatry · 2026Review
- Vocal Markers of Schizophrenia: Assessing the Generalizability of Machine Learning Models and Their Clinical Applicability.Schizophrenia bulletin · 2026Article
- AI-enabled passive digital phenotyping of experiential negative symptoms in schizophrenia-spectrum disorders: a narrative review on the path from sensing to clinical endpoints.Frontiers in psychiatry · 2026Review
- Speech features as potential objective assessment indicators in schizophrenia patients with violence-related symptoms.Frontiers in psychiatry · 2026Article
- Syntactic network analysis in first-episode psychosis: toward generalizability.Schizophrenia (Heidelberg, Germany) · 2025Article
- Detecting schizophrenia, bipolar disorder, psychosis vulnerability and major depressive disorder from 5 minutes of online-collected speech.Translational psychiatry · 2025Article
- Hearing vocals to recognize schizophrenia: speech discriminant analysis with fusion of emotions and features based on deep learning.BMC psychiatry · 2025Article
- Predicting affective engagement and mental strain from prosodic speech features.Frontiers in psychiatry · 2025Article
- Taking a look at your speech: identifying diagnostic status and negative symptoms of psychosis using convolutional neural networks.NPP - digital psychiatry and neuroscience · 2025Article
- Natural Language Processing and Schizophrenia: A Scoping Review of Uses and Challenges.Journal of personalized medicine · 2024Article
- Different in different ways: A network-analysis approach to voice and prosody in Autism Spectrum Disorder.Language learning and development : the official journal of the Society for Language Development · 2024Article
- Relative importance of speech and voice features in the classification of schizophrenia and depression.Translational psychiatry · 2023Article
- Semantic and Acoustic Markers in Schizophrenia-Spectrum Disorders: A Combinatory Machine Learning Approach.Schizophrenia bulletin · 2023Article
- Language and Psychosis: Tightening the Association.Schizophrenia bulletin · 2023Article
- Language Network Dysfunction and Formal Thought Disorder in Schizophrenia.Schizophrenia bulletin · 2023Review
- Linguistic findings in persons with schizophrenia-a review of the current literature.Frontiers in psychology · 2023Review
- Understanding psychiatric illness through natural language processing (UNDERPIN): Rationale, design, and methodology.Frontiers in psychiatry · 2022Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
background and hypothesisVoice 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
designWe 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
resultsWe 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.
conclusionsThe 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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