ArticleJournal of robotic surgery2026
Face and content validation of a novel aquablation training simulator: an educational project of the European school of urology.
Article in Journal of robotic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
16 authors.
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Abstract
Aquablation is an innovative robotic waterjet procedure designed to treat benign prostatic obstruction (BPO) by combining real-time transrectal ultrasound (TRUS) guidance with automated tissue removal using water jets. With its increasing adoption throughout Europe, there is a crucial need for structured and validated training materials. This research represents an opportunistic expert evaluation conducted within a European School of Urology (ESU) educational setting and provides preliminary validity evidence by assessing the face and content validity of an Aquablation training simulator, focusing on realism, procedural accuracy, and suitability for training. A cross-sectional validation study was conducted involving expert endourologists who are familiar with Aquablation. Participants completed standardized questionnaires to assess face and content validity, using 4-point Likert scales. Descriptive statistics were computed, along with measures of internal consistency (Cronbach’s α) and Content Validity Indices (I-CVI, S-CVI/Ave, S-CVI/UA). Face validation demonstrated a high degree of realism and strong consensus across all items, achieving a Cronbach’s alpha of 0.92. Content validation showed excellent agreement, with an S-CVI/Ave of 0.91 and an S-CVI/UA of 0.50. Experts unanimously supported the model’s integration into structured Aquablation training programs. The expert validation confirms the simulator’s educational relevance and procedural accuracy, supporting its use as a training platform for Aquablation within lower urinary tract endoscopy education. Next steps will include defining curriculum components guided by CTA/Delphi and establishing objective performance metrics; subsequent work will evaluate construct and predictive validity across multiple centers.
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