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

Introduction The 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.

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Publication Details

Journal
Open Access CRIS of the University of Bern
Published
2025-07-25
DOI
https://doi.org/10.48620/90447
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
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article

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

Open Access CRIS of the University of Bern
Species Distribution and Climate Change
article

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

article en

Abstract

Introduction The 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.

Open Access CRIS of the University of Bern
Primary Health Care (QA)
Good health and well-being
Openalex Percentile: Top 48%
Species Distribution and Climate Change
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Deconstructing resuscitation training for healthcare providers: a protocol for a component network meta-analysis. · Open Access CRIS of the University of Bern (2025) | TGRS Research Map | TGRS