Evidence map›Paper›PMID 25464920›Full record

ArticleSchizophrenia research2014

Speech deficits in serious mental illness: a cognitive resource issue?

Alex S Cohen, Jessica E McGovern, Thomas J Dinzeo, Michael A Covington

Abstract read
In one paragraph

Article in Schizophrenia research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 3 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

54 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Article
  6. Humanizing "multimodal" digital phenotyping of serious mental illness.Journal of psychopathology and clinical science · 2026
    Article
  7. Article
  8. Disorganisation and depression: a re-examination of how we think and speak when depressed.European archives of psychiatry and clinical neuroscience · 2026
    Review
  9. Review
  10. Linking spontaneous speech, cognition, and psychopathology across affective and psychotic disorders: A network approach.European psychiatry : the journal of the Association of European Psychiatrists · 2026
    Article
  11. An End-to-End Overview of Clinical Speech AI.IEEE transactions on audio, speech, and language processing (2025) · 2026
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Multitask and Transfer Learning Approach for Joint Classification and Severity Estimation of Dysphonia.IEEE journal of translational engineering in health and medicine · 2024
    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

4 authors.

Alex S CohenDepartment of Psychology, Louisiana State University, United States. Electronic address: acohen@lsu.edu.
Jessica E McGovernDepartment of Psychology, Louisiana State University, United States.
Thomas J DinzeoDepartment of Psychology, Rowan University, United States.
Michael A CovingtonInstitute for Artificial Intelligence, The University of Georgia, United States.

Funding

Identifying the Vocal Markers of Schizophrenia-Spectrum DisordersR03MH092622 · NIMH · LOUISIANA STATE UNIV A&M COL BATON ROUGE · PI COHEN, ALEX S · 2011 to 2012
$148k
NIMH NIH HHS R03 MH092622
6 · The paper itself

Abstract

Speech deficits, notably those involved in psychomotor retardation, blunted affect, alogia and poverty of content of speech, are pronounced in a wide range of serious mental illnesses (e.g., schizophrenia, unipolar depression, bipolar disorders). The present project evaluated the degree to which these deficits manifest as a function of cognitive resource limitations. We examined natural speech from 52 patients meeting criteria for serious mental illnesses (i.e., severe functional deficits with a concomitant diagnosis of schizophrenia, unipolar and/or bipolar affective disorders) and 30 non-psychiatric controls using a range of objective, computer-based measures tapping speech production ("alogia"), variability ("blunted vocal affect") and content ("poverty of content of speech"). Subjects produced natural speech during a baseline condition and while engaging in an experimentally-manipulated cognitively-effortful task. For correlational analysis, cognitive ability was measured using a standardized battery. Generally speaking, speech deficits did not differ as a function of SMI diagnosis. However, every speech production and content measure was significantly abnormal in SMI versus control groups. Speech variability measures generally did not differ between groups. For both patients and controls as a group, speech during the cognitively-effortful task was sparser and less rich in content. Relative to controls, patients were abnormal under cognitive load with respect only to average pause length. Correlations between the speech variables and cognitive ability were only significant for this same variable: average pause length. Results suggest that certain speech deficits, notably involving pause length, may manifest as a function of cognitive resource limitations. Implications for treatment, research and assessment are discussed.

Indexed as

Schizophrenic PsychologySpeechAdultBipolar DisorderCognitionFemaleHumansMajor Depressive DisorderMaleModels, PsychologicalPsychological TestsSchizophreniaAlogiaBipolarBlunted affectDepressionNegative symptomsSchizophreniaSpeechVocal

Identifiers

PMID25464920
PMCPMC4310829

What OpenQuestion holds

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Registered trials

None linked

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.