Evidence map›Paper›PMID 40713054›Full record

ArticleBMJ open2025

Deconstructing resuscitation training for healthcare providers: a protocol for a component network meta-analysis.

Defi Efendi, Adam Cheng, Dessie Wanda, Toshi A Furukawa, Maria Petropoulou, Orestis Efthimiou, Kee-Hsin Chen, LIFESAVERS (Leading Innovations for Emergency Support and Vital Enhancements in Resuscitation Simulation) study network

Abstract read
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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Defi EfendiDepartment of Pediatric Nursing, Faculty of Nursing, Universitas Indonesia, Depok, Indonesia.
Adam ChengPediatrics, University of Calgary, Calgary, Alberta, Canada.ORCID http://orcid.org/0000-0002-1039-7502
Dessie WandaDepartment of Pediatric Nursing, Faculty of Nursing, Universitas Indonesia, Depok, Indonesia.ORCID http://orcid.org/0000-0003-0659-1748
Toshi A FurukawaOffice of Institutional Advancement and Communications, Kyoto University, Kyoto, Japan.ORCID http://orcid.org/0000-0003-2159-3776
Maria Petropoulou *University of Freiburg, Freiburg im Breisgau, Germany.ORCID http://orcid.org/0000-0002-7147-3644
Orestis Efthimiou *Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland.
Kee-Hsin ChenPost-Baccalaureate Program in Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan keehsin@tmu.edu.tw.ORCID http://orcid.org/0000-0001-7838-169X
LIFESAVERS (Leading Innovations for Emergency Support and Vital Enhancements in Resuscitation Simulation) study network

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe necessity of enhancing resuscitation training has been encouraged by The International Liaison Committee on Resuscitation and the American Heart Association to reduce mortality, disability and healthcare costs. Resuscitation training is a complicated approach that encompasses various components and their mixture. It is essential to identify the most effective of these components and their combinations, to measure the corresponding effect size and to understand which participant groups may enjoy the greatest advantage. METHODS AND ANALYSIS: We will systematically search 12 databases and two clinical trial registries for randomised controlled trials (RCTs) that examine different resuscitation training methods from inception to April 2025. The analysis will be carried out using the standard network meta-analysis and component network meta-analysis models. Resuscitation skills of staff will be the primary outcome of this analysis. Paired reviewers will independently screen and extract data. A consensus will be sought with the principal investigators to resolve any disagreements that cannot be achieved through regular meetings. Each intervention in each RCT will be decomposed according to its constituent components, such as delivery method, interactivity, teamwork, digitalisation and type of simulator. The analysis will be conducted using the frequentist and bayesian approach in the R environment. RoB V.2.0 and Confidence in Network Meta-Analysis will, respectively, be used to assess the risk of bias and the certainty of the evidence. ETHICS AND DISSEMINATION: As we will use only aggregated secondary data without individual identities, ethical approval is not required. Results of this review will be shared through a peer-reviewed publication and presentation of papers at any relevant conferences. PROSPERO REGISTRATION NUMBER: CRD42024532878.

Indexed as

Cardiopulmonary ResuscitationHealth PersonnelResuscitationBayes TheoremClinical CompetenceHumansNetwork Meta-Analysis as TopicResearch DesignCardiopulmonary ResuscitationEDUCATION & TRAINING (see Medical Education & Training)Health Care CostsNetwork Meta-AnalysisSystematic Review

Identifiers

PMID40713054
PMCPMC12306232

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.