{
  "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",
  "authors": [
    {
      "affiliations": [
        "Department of Pediatric Nursing, Faculty of Nursing, Universitas Indonesia, Depok, Indonesia",
        "Neonatal Intensive Care Unit, Universitas Indonesia Hospital, Depok, Indonesia",
        "School of Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan"
      ],
      "name": "Defi Efendi"
    },
    {
      "affiliations": [
        "Pediatrics, University of Calgary, Calgary, Alberta, Canada",
        "KidSIM-ASPIRE Research Program, Alberta Children’s Hospital, Calgary, Alberta, Canada"
      ],
      "name": "Adam Cheng"
    },
    {
      "affiliations": [
        "Department of Pediatric Nursing, Faculty of Nursing, Universitas Indonesia, Depok, Indonesia"
      ],
      "name": "Dessie Wanda"
    },
    {
      "affiliations": [
        "Office of Institutional Advancement and Communications, Kyoto University, Kyoto, Japan"
      ],
      "name": "Toshi A Furukawa"
    },
    {
      "affiliations": [
        "University of Freiburg, Freiburg im Breisgau, Germany"
      ],
      "name": "Maria Petropoulou"
    },
    {
      "affiliations": [
        "Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland"
      ],
      "name": "Orestis Efthimiou"
    },
    {
      "affiliations": [
        "Post-Baccalaureate Program in Nursing, College of Nursing, Taipei Medical University, Taipei, Taiwan",
        "Cochrane Taiwan, Taipei Medical University, Taipei, Taiwan",
        "Department of Nursing & Research Center in Nursing Clinical Practice, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan",
        "School of Medicine, Faculty of Health and Medical Sciences, Taylor’s University, Subang Jaya, Selangor, Malaysia"
      ],
      "name": "Kee-Hsin Chen"
    },
    {
      "affiliations": [],
      "name": "on behalf of the LIFESAVERS (Leading Innovations for Emergency Support and Vital Enhancements in Resuscitation Simulation) study network"
    }
  ],
  "title": "Deconstructing resuscitation training for healthcare providers: a protocol for a component network meta-analysis",
  "uid": "13be2754-4a5a-5a82-a010-3734036c9d1d"
}