Evidence map›Paper›PMID 40415539›Full record

ArticleEuropean psychiatry : the journal of the Association of European Psychiatrists2025

ItemComplex: A Python-based visualization framework for ex-post organization and integration of large language-based datasets.

Karina Janson, Karl Gottfried, Olaf Reis, Johannes Kornhuber, Anna Eichler, Michael Deuschle, Tobias Banaschewski, Frauke Nees, IMAC-Mind Consortium

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Article in European psychiatry : the journal of the Association of European Psychiatrists, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Karina JansonDepartment of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.ORCID https://orcid.org/0000-0002-0902-0628
Karl GottfriedDepartment of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.
Olaf ReisDepartment of Child and Adolescent Psychiatry, Neurology, Psychosomatics and Psychotherapy, Rostock University Medical Centre, Gehlsheimer Strasse 20, Rostock18147, Germany.
Johannes KornhuberDepartment of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen91054, Germany.
Anna EichlerDepartment of Child and Adolescent Mental Health, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen91054, Germany.
Michael DeuschleDepartment of Psychiatry and Psychotherapy, Medical Faculty Mannheim, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany.
Tobias BanaschewskiDepartment of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.ORCID https://orcid.org/0000-0003-4595-1144
Frauke NeesDepartment of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany.ORCID https://orcid.org/0000-0002-7796-8234
IMAC-Mind Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNowadays, both researchers and clinicians alike have to deal with increasingly larger datasets, specifically also in the context of mental health data. Sophisticated tools for dataset visualization of information from various item-based instruments, such as questionnaire data or data from digital applications or clinical documentations, are still lacking, specifically for an integration at multiple levels and for use in both data organization and appropriate construction for its valid use in subsequent analyses.

methodsHere, we introduce

resultsThe

conclusionsThe

Indexed as

Big DataDatasets as TopicData VisualizationSoftwareHumansbig dataconstructscontent networksdata navigationdata structuringdata visualizationitems

Identifiers

PMID40415539
PMCPMC12188333

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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.