Work

Training pathways and formal curricula in robotic bariatric surgery: a systematic review

Year: 2026

Type: review

Abstract: The adoption of robotic platforms in bariatric and metabolic surgery has increased steadily, raising important questions regarding how surgeons are trained to safely acquire robotic skills. While structured and competency-based training models are increasingly adopted in other fields of robotic surgery, training approaches in robotic bariatric surgery remain less standardized. A systematic review was conducted in accordance with PRISMA 2020 guidelines to identify studies describing structured training pathways or formal curricula for robotic bariatric surgery. PubMed, Embase, Scopus, and Cochrane Library, were searched from inception without date restrictions. Eligible studies explicitly reported training programs, curricula, or educational pathways for robotic bariatric procedures. Learning curve analyses without a defined curriculum were excluded. Data were synthesized using a structured narrative approach. Five studies met the inclusion criteria. Training models included stepwise intraoperative curricula, simulation-based and proficiency-driven programs, and modular educational interventions. Common components across curricula were simulation training, task decomposition, supervised progression, and defined competency benchmarks. Assessment strategies were heterogeneous and ranged from simulation-based proficiency thresholds to operative participation metrics and subjective workload measures. No study reported standardized certification or long-term competency outcomes. Structured training pathways for robotic bariatric surgery have been described and incorporate elements aimed at supporting safe skill acquisition. However, existing curricula remain heterogeneous and lack standardized assessment frameworks. Future efforts should focus on developing competency-driven and proficiency-based progression training models to support reproducible and safe adoption of robotic bariatric surgery.

Source: Journal of Robotic Surgery

DOI: 10.1007/s11701-026-03247-2

Authors: Francesco Brucchi, Daqi Zhang, Simona Bertoli, Santo Colosimo, Gianlorenzo Dionigi

Institutions: University of Milan, IRCCS Istituto Auxologico Italiano, Jilin University

Language: English

Topic: Surgical Simulation and Training

Subfield: Surgery

Field: Medicine

Domain: Health Sciences

SDGs: Good health and well-being, Quality education

Open Access status: hybrid

Estimated APC paid: $4,090