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Robotic surgery has seen substantial growth, however training access remains limited by resources and time-intensive credentialling pathways. Technology enhanced learning may address these barriers whilst improving training efficiency and assessment objectivity. We aimed to systematically evaluate technology-enhanced approaches to basic robotic surgical skills training. This systematic review followed PRISMA guidelines with prospective registration (OSF: V93MZ). MEDLINE (via OVID), Embase, and the Cochrane Library (CENTRAL and CDSR) were searched on 23 May 2025 without date restrictions. Technologies included virtual reality, augmented reality, sensor-based systems, video review, and performance feedback. Risk of bias was assessed using the RoB-2 and ROBINS-I tools, and certainty of evidence using GRADE. Narrative synthesis was utilised given methodological heterogeneity, with reported outcomes mapped to the Kirkpatrick model of training evaluation. Seventeen studies involving 484 participants were included (10 randomised trials, 7 prospective cohort studies; 16 single-centre). Technologies comprised virtual reality (7), sensor-based systems (5), performance feedback (3), video review (1), and augmented reality (1); no eligible artificial intelligence studies were identified. Virtual reality, utilised within bespoke robotic simulators, demonstrated accelerated learning curves, although some systems required more repetitions than traditional robotic simulator-based training. The single augmented reality study improved instrument velocity. Sensor-based force measurement devices improved force application and ergonomics. Video review improved accuracy but temporarily increased completion time. Multimodal feedback systems outperformed conventional feedback. Evidence was concentrated at Kirkpatrick level 2 (learning); one study reported only level 1 (reaction) data, with no studies reporting level 3 or 4 outcomes. Risk of bias was low in randomised studies and low-moderate in non-randomised studies. Technology-enhanced basic robotic skills training has evidence supporting improved performance outcomes, accelerated learning curves, and enhanced objective assessment capabilities. Gaps persist for basic skills training in augmented reality, artificial intelligence, and docking and setup. Standardised competency assessment frameworks are required to evaluate these rapidly progressing tools.
Shakir et al. (Mon,) studied this question.