Evidence map›Paper›PMID 27334771›Full record

ReviewJournal of robotic surgery2016

Da Vinci© Skills Simulator™: is an early selection of talented console surgeons possible?

Mark Meier, Kevin Horton, Hubert John

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of robotic surgery, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
3.8field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 34 citations in OpenAlex.

  1. Trial
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  3. Review
  4. Article
  5. Exploring "Talent" in Medical Education: A Scoping Review.Perspectives on medical education · 2026
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  11. Observational
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  16. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Mark MeierDepartment of Urology, Kantonsspital Winterthur, 8400, Winterthur, Switzerland. mark.meier@gzo.ch.ORCID http://orcid.org/0000-0003-1069-1194
Kevin HortonDepartment of Urology, Kantonsspital Winterthur, 8400, Winterthur, Switzerland.
Hubert JohnDepartment of Urology, Kantonsspital Winterthur, 8400, Winterthur, Switzerland.
Kantonsspital Winterthur · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To investigate whether the learning curve of robotic surgery simulator training depends on the probands' characteristics, such as age and prior experience, we conducted a study of six distinct proband groups, using the da Vinci Skills Simulator: experienced urological robotic surgeons, surgeons with experience as da Vinci tableside assistants, urological surgeons with laparoscopic experience, urological surgeons without laparoscopic experience, and complete novices aged 25 and younger and 40 and older. The results showed that all experienced robotic surgeons reached expert level (>90 %, as defined previously in the literature) within the first three repetitions and remained on a high level of performance. All other groups performed worse. Tableside assistants, laparoscopically experienced surgeons, and younger novices showed a better performance in all exercises than surgeons without laparoscopic experience and older novices. A linear mixed-effects model analysis demonstrated no significant difference in learning curves between proband groups in all exercises except the RW1 exercise for the younger proband group. In summary, we found that performance in robotic surgery, measured by performance scores in three virtual simulator modules using the EndoWrist techniques, was dependent on age and prior experience with robotic and laparoscopic surgery. However, and most importantly, the learning curve was not significantly affected by these factors. This suggests that the da Vinci Skills Simulator™ is a useful practice tool for everyone learning or performing robotic surgery, and that early selection of talented surgeons is neither possible nor necessary.

Indexed as

AdultAgedClinical CompetenceHumansLaparoscopyLearning CurveMiddle AgedPersonnel SelectionPhysician AssistantsRoboticsRobotic Surgical ProceduresSimulation TrainingSurgeonsUrologistsEducationRobotic surgerySelectionSkillTraining

Identifiers

PMID27334771
OpenAlexW2464826291

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.