Evidence map›Paper›PMID 35203930›Full record

ArticleBrain sciences2022

Graph Analysis of Verbal Fluency Tests in Schizophrenia and Bipolar Disorder.

Adrian Andrzej Chrobak, Aleksander Turek, Karolina Machalska, Aleksandra Arciszewska-Leszczuk, Anna Starowicz-Filip, Anna Julia Krupa, Dominika Dudek, Marcin Siwek

Open access · goldAbstract read
In one paragraph

Article in Brain sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
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  5. Review
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

8 authors at 2 institutions in 1 country.

Adrian Andrzej ChrobakDepartment of Adult Psychiatry, Jagiellonian University Medical College, Kopernika St. 21a, 31-501 Kraków, Poland.ORCID 0000-0002-2107-9980
Aleksander TurekStudent's Scientific Association of Affective Disorders, Jagiellonian University Medical College, Kopernika St. 21a, 31-501 Kraków, Poland.ORCID 0000-0002-4327-252X
Karolina MachalskaStudent's Scientific Association of Affective Disorders, Jagiellonian University Medical College, Kopernika St. 21a, 31-501 Kraków, Poland.
Aleksandra Arciszewska-LeszczukFaculty of Psychology, SWPS University of Social Sciences and Humanities, Polna St. 16/20, 81-745 Sopot, Poland.ORCID 0000-0002-1762-3963
Anna Starowicz-FilipDepartment of Medical Psychology, Jagiellonian University Medical College, Jakubowskiego St. 2, 30-688 Kraków, Poland.
Anna Julia KrupaDepartment of Psychiatry, Jagiellonian University Medical College, Kopernika St. 21a, 31-501 Kraków, Poland.ORCID 0000-0003-3291-9663
Dominika DudekDepartment of Adult Psychiatry, Jagiellonian University Medical College, Kopernika St. 21a, 31-501 Kraków, Poland.
Marcin SiwekDepartment of Affective Disorders, Jagiellonian University Medical College, Kopernika St. 21a, 31-501 Kraków, Poland.ORCID 0000-0002-3109-1895
Jagiellonian University · PLUniwersytet SWPS · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Verbal Fluency Tests (VFT) are one of the most common neuropsychological tasks used in bipolar disorder (BD) and schizophrenia (SZ) research. Recently, a new VFT analysis method based on graph theory was developed. Interpreting spoken words as nodes and every temporal connection between consecutive words as edges, researchers created graph structures, allowing the extraction of more data from participants' speech, called Speech Graph Attributes (SGA). The aim of our study was to compare speech graphs, derived from Phonemic and Semantic VFT, between SZ, BD, and healthy controls (HC). Twenty-nine SZ patients, twenty-nine BD patients, and twenty-nine HC performed Semantic and Phonemic VFT. Standard measures (SM) and 13 SGA were analyzed. SZ patients' Semantic VFT graphs showed lower total word count and correct responses. Their graphs presented less nodes and edges, higher density, smaller diameter, average shortest path (ASP), and largest strongly connected component than the HC group. SM did not differentiate BD and HC groups, and patients' Semantic VFT graphs presented smaller diameter and ASP than HC. None of the parameters differentiated BD and SZ patients. Our results encourage the use of speech graph analysis, as it reveals verbal fluency alterations that remained unnoticed in the routine comparisons of groups with the use SM.

Indexed as

cognitive impairmentssemantic networkspeech graphs

Identifiers

PMID35203930
PMCPMC8870283
OpenAlexW4210579099

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.