Evidence map›Paper›PMID 41050346›Full record

ReviewSchizophrenia research. Cognition2026

Clinical psychopathology-based early relapse prediction model using speech and language in psychosis.

Tyler C Dalal, Min Tae M Park, Angelica M Silva, Svetlana Iskhakova, Alban Voppel, Noah J Brierley, Michael MacKinley, Emmanuel Olarewaju, Lena Palaniyappan

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Schizophrenia research. Cognition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Tyler C DalalSchulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Min Tae M ParkDouglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada.
Angelica M SilvaRobarts Research Institute, London, ON, Canada.
Svetlana IskhakovaSchulich School of Medicine and Dentistry, Western University, London, ON, Canada.
Alban VoppelDouglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada.
Noah J BrierleyDepartment of Psychology, Laurentian University, Sudbury, ON, Canada.
Michael MacKinleyDepartment of Psychiatry, Western University, London, ON, Canada.
Emmanuel OlarewajuDouglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada.
Lena PalaniyappanSchulich School of Medicine and Dentistry, Western University, London, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Prediction of psychotic relapse using speech-derived markers promises targeted early intervention. However, the sheer number of speech markers and the 'black box' nature of predictive models challenges clinical translation. Methods: We propose a psychopathology-based systematic approach to identify likely relapse. We draw on the notion that the predictors of relapse should mark (1) the presence of schizophrenia in its untreated early stages and (2) track disorganization in psychosis. By leveraging Natural Language Processing, we derive 3 lexical, syntactic and narrative markers -semantic similarity, clause complexity, and analytic thinking index from speech samples of people with acute psychosis ( Results: Speech-based model predicted relapse status with strong evidence (Bayes Factor BF Conclusion: Using a Bayesian approach, this preliminary study demonstrates the utility of psychopathology-guided variable selection for speech-based relapse prediction complementing clinical intuition in practice.

Indexed as

Computational linguisticsDisorganizationEarly interventionImpoverishmentPrecision psychiatryRelapseThought disorder

Identifiers

PMID41050346
PMCPMC12493218

What OpenQuestion holds

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Registered trials

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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.