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1000
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Abstract/Summary
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The rapid rise of robotic-assisted surgery (RAS) has necessitated an efficient and standardized training curriculum. Cognitive training (CT) can significantly improve skills, such as attention, working memory and problem solving, and can enhance surgical capacity and support RAS training. This pilot study was carried out between 02/2019 and 04/2019. The participants included 33 student volunteers, randomized into 3 groups: group 1 received training using the da Vinci training simulator, group 2 received computer-based cognitive training, and group 3 was the control group without training. Before (T1) and after-training (T2), performance was measured. Additionally, expert ratings and self-evaluations were collected. Subjective evaluations of performance were supplemented by evaluations based on three scales from the revised NEO Personality Inventory (NEO PI-R). In total, 25 probands remained with complete data for further analyses: n = 8 (group 1), n = 7 (group 2) and n = 10 (group 3). There were no significant differences in T1 and T2 among all three groups. The average training gain of group 1 and 2 was 15.87% and 24.6%, respectively, (a restricting condition is the loss of the last training session in group 2). Analyses of semi-structured psychological interviews (SPIs) revealed no significant differences for T1, but in T2, significance occurred at 'self-reflection' for group 2 (F(2.22) = 8.56; p < .005). The efficacy of CT in training highly complex and difficult procedures, such as RAS, is a proven and accepted fact. Further investigation involving higher numbers of training trials (while also being cost effective) should be performed.
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1000
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Hinweis
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DeepGreen-ID: 0a65773bd9c644f9b8d3d8c8d2bb9ce4 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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