Evidence map›Paper›PMID 40840990›Full record

ArticleBMJ open2025

Protocol for development of a checklist and guideline for transparent reporting of cluster analyses (TRoCA).

Daniil Lisik, Syed Ahmar Shah, Rani Basna, Tai Dinh, Ryan P Browne, Jeffrey L Andrews, Meredith Wallace, Absalom Ezugwu, Ana Marusic, Dat Tran and 9 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2025. 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
  2. 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

19 authors.

Daniil LisikDepartment of Public Health and Clinical Medicine, Section of Sustainable Health, The OLIN Unit, Umeå Universitet, Umeå, Sweden daniil.lisik@gmail.com.ORCID http://orcid.org/0000-0002-0220-5961
Syed Ahmar ShahThe University of Edinburgh Usher Institute, Edinburgh, UK.ORCID http://orcid.org/0000-0001-5672-0443
Rani BasnaKrefting Research Centre, Institute of Medicine, University of Gothenburg Sahlgrenska Academy, Gothenburg, Sweden.
Tai DinhCMC University, Hanoi, Vietnam.
Ryan P BrowneDepartment of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canada.
Jeffrey L AndrewsDepartment of Statistics, The University of British Columbia, Vancouver, British Columbia, Canada.
Meredith WallaceDepartment of Psychiatry, Statistics and Biostatistics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Absalom EzugwuUnit for Data Science and Computing, North-West University, Potchefstroom, South Africa.
Ana MarusicDepartment of Research in Biomedicine and Health, University of Split School of Medicine, Split, Croatia.ORCID http://orcid.org/0000-0001-6272-0917
Dat TranUniversity of Canberra, Canberra, Australian Capital Territory, Australia.
Joaquín Torres-SospedraDepartment of Computer Science, Universitat de València, Valencia, Spain.
Hieu-Chi DamJapan Advanced Institute of Science and Technology, Nomi, Japan.
Philippe Fournier-VigerBig Data Institute, Shenzhen University College of Computer Science and Software Engineering, Shenzhen, Guangdong, China.
Christian HennigDepartment of Statistical Sciences 'Paolo Fortunati', University of Bologna, Bologna, Italy.
Marieke TimmermanDepartment of Psychometrics and Statistics, University of Groningen, Groningen, Netherlands.
Matthijs J WarrensGION Education/Research, Department of Pedagogical and Educational Sciences, University of Groningen, Groningen, The Netherlands.
Eva CeulemansQuantitative Psychology and Individual Differences, KU Leuven, Leuven, Belgium.
Bright I NwaruKrefting Research Centre, Institute of Medicine, University of Gothenburg Sahlgrenska Academy, Gothenburg, Sweden.
Tina M Hernandez-BoussardDepartment of Biomedical Data Science, Stanford University, Stanford, California, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCluster analysis, a machine learning-based and data-driven technique for identifying groups in data, has demonstrated its potential in a wide range of contexts. However, critical appraisal and reproducibility are often limited by insufficient reporting, ultimately hampering the interpretation and trust of key stakeholders. The present paper describes the protocol that will guide the development of a reporting guideline and checklist for studies incorporating cluster analyses-Transparent Reporting of Cluster Analyses. METHODS AND ANALYSIS: Following the recommended steps for developing reporting guidelines outlined by the Enhancing the QUAlity and Transparency Of health Research Network, the work will be divided into six stages. Stage 1: literature review to guide development of initial checklist. Stage 2: drafting of the initial checklist. Stage 3: internal revision of checklist. Stage 4: Delphi study in a global sample of researchers from varying fields ( ETHICS AND DISSEMINATION: Due to local regulations, the planned study is exempt from the requirement of ethical review. The findings will be disseminated through peer-reviewed publications. The checklist with explanations will also be made available freely on a dedicated web platform (troca-statement.org) and in a repository.

Indexed as

ChecklistGuidelines as TopicResearch DesignCluster AnalysisConsensusDelphi TechniqueHumansHealth informaticsInformation managementInformation technology

Identifiers

PMID40840990
PMCPMC12374645

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.