ArticleJournal of robotic surgery2024
IMRA/SRS Delphi consensus on international standards for common core components of robotic surgical training design.
Article in Journal of robotic surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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.
The trial behind it
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Expert consensus on best content of a robotic surgical curriculum: a systematic review.Journal of robotic surgery · 2025Pooled it
- Institutional availability, training resources, and supervised participation in robot-assisted surgery among Polish urology residents: a nationwide survey.Journal of robotic surgery · 2026Article
- Robotic enterorrhaphy model for junior residents: A step closer to the fundamentals of robotic surgery manual skills assessment.Journal of robotic surgery · 2026Article
- Pre-Procedural Robotic Surgery Curricula: A Systematic Review and Thematic Meta-Synthesis.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2026Review
- Robot-assisted TAPP inguinal hernia repair training: validation of a synthetic hydrogel model-an international expert panel study.Journal of robotic surgery · 2026Article
- Training and credentialing in robotic general surgery.International journal of colorectal disease · 2026Review
- Procedural robotic surgery training: a UK pan-specialty trainee Delphi consensus study.Journal of robotic surgery · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
24 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Robotic surgery has expanded internationally at pace. There are multiple local robotic training pathways but there is inconsistency in standardisation of core common components for curricula internationally. A framework is required to define key objectives that can be implemented across robotic training ecosystems. This Delphi consensus aimed to provide recommendations for core considerations in robotic training design across diverse training environments internationally. A literature search was performed and an international steering committee (AG, KL, JW, HM, TC) proposed key components for contemporary robotic training design and a modified Delphi approach was used to gather stakeholder opinion. The outcomes were then discussed at a face-to-face international expert consensus at the IMRA educational session at the Society of Robotic Surgery (SRS) meeting and final voting was conducted on outstanding items. Stakeholders included robotic surgeons, proctors, trainees and robotic surgical training providers. There was consensus achieved in 139 statements organised into 15 themes. There was 100% agreement that standardised themes in robotic curricula may improve patient safety. Key take-home messages include-training curricula should be multiplatform, non-technical skills are an important component of a robotic curriculum as well as console and bedside skills, clinically relevant performance metrics should be used for assessment where available, the reliance on cadaveric and live animal models should be reduced as high-fidelity synthetic models emerge, and stepwise component training is useful for advanced procedural training. These consensus recommendations are intended to guide design of fit for purpose contemporary robotic surgical curricula. Integration of these components into robotic training pathways internationally is recommended.
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Registered trials
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.