{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T22:28:11Z","timestamp":1793140091725,"version":"4.5.0"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T00:00:00Z","timestamp":1783382400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T00:00:00Z","timestamp":1783382400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Surg Endosc"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The expansion of robotic surgery has created interest in resident robotic curricula to develop competent robotic surgeons. While it has been demonstrated that curricula improve technical performance, less is known about resident factors that predispose poor baseline performance and whether structured training can reduce these disparities. Predictors of early underperformance were hypothesized to be attenuated after completion of a multimodal robotic curriculum.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>PGY-3 general surgery residents (2019\u20132023) completed a standardized 2-week curriculum. Training included periodic assessment tests, virtual reality (VR) simulation training, and procedure-based simulation with bio-tissue drills. Objective performance across the curriculum was evaluated, and resident-specific predictors of performance were examined. Performance was graded by an expert surgeon using OSATS (range 6\u201330). Perceived mental workload and stress were measured using the NASA Task Load Index, Borg Exertion Scale, and Edwards Arousal Rating.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Thirty-nine residents completed the curriculum. Residents were stratified by pre-test mOSATS; high (top 25%), mid (50%), and low (bottom 25%). Pre-test strata remained associated with VR post-test strata (50% of high performers and 55% of low performers remained in pre-test strata;\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.041). However, pre-test and post-test strata were not associated with final test performance after bio-tissue drills. Higher pre-curriculum comfort predicted high pre-test performance (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.003). Low pre-test performance was associated with male sex (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.010), less robotic experience (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.025), and lower pre-curriculum comfort (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.031). Anticipated career use of robotics predicted better initial bio-tissue drill performance (running hepaticojejunostomy\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.042; interrupted hepaticojejunostomy\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.024). Higher baseline stress correlated with worse final pancreatojejunostomy performance (Spearman\n                      <jats:italic>\u03c1<\/jats:italic>\n                      \u2009=\u2009\u22120.46;\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.004).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Resident characteristics influence early robotic simulation performance, but a structured curriculum mitigates baseline disparities such that initial performance and its predictors no longer influence final outcomes. These findings highlight the value of a robotic curriculum\u2019s ability to foster competency and optimize resident training.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00464-026-13035-6","type":"journal-article","created":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T15:29:30Z","timestamp":1783438170000},"page":"7016-7025","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Balancing the scales: predictors of performance and the long-term impact of a robotic surgery curriculum"],"prefix":"10.1007","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-6150-6799","authenticated-orcid":false,"given":"Colin M.","family":"Johnson","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarah B.","family":"Hays","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jason L.","family":"Schwarz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristine","family":"Kuchta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aram","family":"Rojas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Syed A.","family":"Mehdi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sangrag","family":"Ganguli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7502-4790","authenticated-orcid":false,"given":"Alessia","family":"Vallorani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miral S.","family":"Grandhi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melissa E.","family":"Hogg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,7]]},"reference":[{"key":"13035_CR1","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2019.18911","author":"KH Sheetz","year":"2020","unstructured":"Sheetz KH, Claflin J, Dimick JB (2020) Trends in the adoption of robotic surgery for common surgical procedures. 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Hogg receives funding from Intuitive Surgical for observations, engaging in HPB courses, and proctoring, as well as Olympus where she is a consultant, but there is no direct funds for\u2009>\u20092\u00a0years. Dr. Colin M. Johnson, Dr. Sarah B. Hays, Dr. Jason L. Schwarz, Ms. Kristine Kuchta, Dr. Aram Rojas, Dr. Syed A. Mehdi, Dr. Sangrag Ganguli, Dr. Alessia Vallorani, and Dr. Miral S. Grandhi have no conflicts of interest or financial ties to disclose.","order":1,"name":"Ethics","label":"Disclosures","group":{"name":"EthicsHeading","label":"Declarations"}}]}}