Evidence map›Paper›PMID 41572735›Full record

ArticleEuropean psychiatry : the journal of the Association of European Psychiatrists2026

Linking spontaneous speech, cognition, and psychopathology across affective and psychotic disorders: A network approach.

Rieke Roxanne Mülfarth, Svenja Seuffert, Nina Alexander, Hamidreza Jamalabadi, Igor Nenadić, Benjamin Straube, Lea Teutenberg, Florian Thomas-Odenthal, Paula Usemann, Udo Dannlowski and 2 more

Abstract read
In one paragraph

Article in European psychiatry : the journal of the Association of European Psychiatrists, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Review
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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

12 authors.

Rieke Roxanne MülfarthFaculty of Medicine, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany.ORCID 0009-0001-8425-0431
Svenja SeuffertFaculty of Medicine, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany.ORCID 0009-0007-2230-4741
Nina AlexanderFaculty of Medicine, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany.
Hamidreza JamalabadiFaculty of Medicine, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany.
Igor NenadićFaculty of Medicine, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany.
Benjamin StraubeFaculty of Medicine, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany.
Lea TeutenbergFaculty of Medicine, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany.ORCID 0009-0002-7783-8461
Florian Thomas-OdenthalFaculty of Medicine, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany.ORCID 0000-0003-4912-8307
Paula UsemannFaculty of Medicine, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany.ORCID 0009-0005-4566-0058
Udo DannlowskiInstitute for Translational Psychiatry, University of Münster, Münster, Germany.
Tilo KircherFaculty of Medicine, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany.ORCID 0000-0002-2514-2625
Frederike SteinFaculty of Medicine, Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany.ORCID 0000-0002-5052-6022

Funding

Deutsche Forschungsgemeinschaft CRC/TRR 393, project number 521379614Deutsche Forschungsgemeinschaft DA1151/5-1, DA1151/5-2, DA1151/9-1, DA1151/10-1, DA1151/11-1; FOR 2107, project number 240413749Deutsche Forschungsgemeinschaft KI588/14-1, KI588/14-2, KI588/20-1, KI588/22-1; FOR 2107, project number 240413749Deutsche Forschungsgemeinschaft STE3301/1-1; project number 527712970Von-Behring-Röntgen-Stiftung project number 72_0013
6 · The paper itself

Abstract

backgroundLanguage impairments are common in affective and psychotic disorders, yet their patterns and underlying pathomechanisms remain insufficiently understood. A transdiagnostic perspective provides a framework for identifying shared and disorder-specific language alterations across diagnostic boundaries. Combining natural language processing (NLP) with network analysis enables the investigation of complex associations between linguistic, cognitive, and psychopathological features.

methodsSpontaneous speech from

resultsLinguistic variables formed the densest network cluster, with type-token ratio, mean length of utterance, and syntactic complexity emerging as central nodes. Psychopathology variables were less cohesive, while TLI "Impoverishment", coherence mean, and executive functioning bridged linguistic, cognitive, and psychopathological domains. Network comparison tests revealed no significant differences in linguistic-cognitive network structure across HC, MDD, BD, and SSD.

conclusionsLinguistic networks show high structural consistency across healthy individuals and patients, whereas psychopathological symptom networks reflect transdiagnostic profiles. These findings support a dimensional and transdiagnostic framework underscore shared language-cognition mechanisms, and highlight executive functioning as key cross-domain connection, which opens up new avenues for dimensional research into the pathophysiological and etiological mechanisms underlying language dysfunctions.

Indexed as

Bipolar DisorderCognitionLanguage DisordersMajor Depressive DisorderPsychotic DisordersSpeechAdultFemaleHumansMaleMiddle AgedNatural Language Processingcognitionnatural language processingnetwork analysispsychopathologytransdiagnostic

Identifiers

PMID41572735
PMCPMC12925669

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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.