ArticleNPJ schizophrenia2015
Automated analysis of free speech predicts psychosis onset in high-risk youths.
Article in NPJ schizophrenia, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 249 papers, 9 of them syntheses that pooled it.
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Who cites it
249 citing papers in PubMed, 9 syntheses or guidelines pooled it, 668 citations in OpenAlex.
- Speech and Language Markers as Longitudinal Predictors of Youth Mental Health: A Systematic Review.Early intervention in psychiatry · 2025Pooled it
- A systematic review of artificial intelligence-powered (AI-powered) chatbot intervention for managing chronic illness.Annals of medicine · 2024Pooled it
- The temporal dynamics of transition to psychosis in individuals at clinical high-risk (CHR-P) shows negative prognostic effects of baseline antipsychotic exposure: a meta-analysis.Translational psychiatry · 2023Pooled it
- Association between formal thought disorders, neurocognition and functioning in the early stages of psychosis: a systematic review of the last half-century studies.European archives of psychiatry and clinical neuroscience · 2022Pooled it
- Negative Prognostic Effect of Baseline Antipsychotic Exposure in Clinical High Risk for Psychosis (CHR-P): Is Pre-Test Risk Enrichment the Hidden Culprit?The international journal of neuropsychopharmacology · 2021Pooled it
- Machine Learning and Natural Language Processing in Mental Health: Systematic Review.Journal of medical Internet research · 2021Pooled it
- Implementing Precision Psychiatry: A Systematic Review of Individualized Prediction Models for Clinical Practice.Schizophrenia bulletin · 2021Pooled it
- A technical review of canonical correlation analysis for neuroscience applications.Human brain mapping · 2020Pooled it
- The link between formal thought disorder and social functioning in schizophrenia: A meta-analysis.European psychiatry : the journal of the Association of European Psychiatrists · 2020Pooled it
- Comprehensive verbal fluency features predict executive function performance.Scientific reports · 2021Trial
- Network analysis of narrative discourse and attention-deficit hyperactivity symptoms in adults.PloS one · 2021Trial
- The entropic brain today.Brain : a journal of neurology · 2026Review
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- Cross-linguistic benchmarking of NLP metrics for psychosis research.NPJ digital medicine · 2026Article
- Structural neuroimaging correlates of semantic incoherence in schizophrenia.European archives of psychiatry and clinical neuroscience · 2026Article
- Reading between the lines: Combining pause dynamics and semantic coherence for automated assessment of thought disorder.Neuropsychologia · 2026Article
- An integrative NLP framework identifies multilevel linguistic phenotypes of schizophrenia across tasks.Psychological medicine · 2026Article
- A scoping review of the use of artificial intelligence as a psychological assessment tool.Translational psychiatry · 2026Article
- From thought to language: Comparing schizophrenia spectrum disorders and Wernicke's aphasia with machine learning and LLMs.Schizophrenia research. Cognition · 2026Article
189 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
10 authors at 6 institutions in 3 countries.
Funding
Abstract
BACKGROUND/
objectivesPsychiatry lacks the objective clinical tests routinely used in other specializations. Novel computerized methods to characterize complex behaviors such as speech could be used to identify and predict psychiatric illness in individuals.
aimsIn this proof-of-principle study, our aim was to test automated speech analyses combined with Machine Learning to predict later psychosis onset in youths at clinical high-risk (CHR) for psychosis.
methodsThirty-four CHR youths (11 females) had baseline interviews and were assessed quarterly for up to 2.5 years; five transitioned to psychosis. Using automated analysis, transcripts of interviews were evaluated for semantic and syntactic features predicting later psychosis onset. Speech features were fed into a convex hull classification algorithm with leave-one-subject-out cross-validation to assess their predictive value for psychosis outcome. The canonical correlation between the speech features and prodromal symptom ratings was computed.
resultsDerived speech features included a Latent Semantic Analysis measure of semantic coherence and two syntactic markers of speech complexity: maximum phrase length and use of determiners (e.g., which). These speech features predicted later psychosis development with 100% accuracy, outperforming classification from clinical interviews. Speech features were significantly correlated with prodromal symptoms.
conclusionsFindings support the utility of automated speech analysis to measure subtle, clinically relevant mental state changes in emergent psychosis. Recent developments in computer science, including natural language processing, could provide the foundation for future development of objective clinical tests for psychiatry.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.