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Updated: Apr 18, 2026

Investigating Motor Skill Learning Processes with a Robotic Manipulandum
Published on: February 12, 2017
External validation of Global Evaluative Assessment of Robotic Skills (GEARS)
Monty A Aghazadeh1,2, Isuru S Jayaratna3, Andrew J Hung3
1Department of Urology, Methodist Institute for Technology, Innovation, and Education, Houston Methodist Hospital, 6560 Fannin Street, Suite 2100, Houston, TX, 77030, USA.
Background:
We demonstrate the construct validity, reliability, and utility of Global Evaluative Assessment of Robotic Skills (GEARS), a clinical assessment tool designed to measure robotic technical skills, in an independent cohort using an in vivo animal training model.
Methods:
Using a cross-sectional observational study design, 47 voluntary participants were categorized as experts (>30 robotic cases completed as primary surgeon) or trainees. The trainee group was further divided into intermediates (≥5 but ≤30 cases) or novices (<5 cases). All participants completed a standardized in vivo robotic task in a porcine model. Task performance was evaluated by two expert robotic surgeons and self-assessed by the participants using the GEARS assessment tool. Kruskal-Wallis test was used to compare the GEARS performance scores to determine construct validity; Spearman's rank correlation measured interobserver reliability; and Cronbach's alpha was used to assess internal consistency.
Results:
Performance evaluations were completed on nine experts and 38 trainees (14 intermediate, 24 novice). Experts demonstrated superior performance compared to intermediates and novices overall and in all individual domains (p < 0.0001). In comparing intermediates and novices, the overall performance difference trended toward significance (p = 0.0505), while the individual domains of efficiency and autonomy were significantly different between groups (p = 0.0280 and 0.0425, respectively). Interobserver reliability between expert ratings was confirmed with a strong correlation observed (r = 0.857, 95 % CI [0.691, 0.941]). Experts and participant scoring showed less agreement (r = 0.435, 95 % CI [0.121, 0.689] and r = 0.422, 95 % CI [0.081, 0.0672]). Internal consistency was excellent for experts and participants (α = 0.96, 0.98, 0.93).
Conclusions:
In an independent cohort, GEARS was able to differentiate between different robotic skill levels, demonstrating excellent construct validity. As a standardized assessment tool, GEARS maintained consistency and reliability for an in vivo robotic surgical task and may be applied for skills evaluation in a broad range of robotic procedures.
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