BACKGROUND

The field of surgery has been transformed with the implementation of minimally invasive surgery and robotic surgery.1 Introduced by Intuitive Surgical Inc. in 1999, the Da Vinci robotic system uses a multi-arm platform controlled by a surgeon from a console. It provides a high-definition image, and 3D view of the surgical site, allowing precise manipulation of robotic arms that mimic the surgeon’s hand movements in real-time.2 This integration enhances precision, dexterity, and extends the range of motion, beyond laparoscopy limitations.

The Da Vinci Robotic System requires specific training programs for surgeons, using reality simulators as the primary educational tool. Introduced in 2007, developed by Mimic and Intuitive Technologies, integrates the EndoWrist instruments and finger clutch controls used in actual surgeries.3,4 The Da Vinci Skills Simulator (dVSS) includes a training software with over 30 exercises, designed to improve skills including camera and clutch control in three-dimensional images. Advanced modules focus on energy and needle control, providing a controlled environment for surgeons to practice complex procedures and refine oculomotor skills, and currently, simple surgical procedure simulators are being implemented.5

In 2016, Meier et al. demonstrated that surgical experience does not improve simulator performance, and younger novices performed the exercises significantly better. This finding suggests that age is a better predictor of robotic skills than prior surgical experience.2 Similar results were obtained by Tillou.6 Hagen et al. evaluated various skill backgrounds, including computer gaming skills, general dexterity with chopsticks, and laparoscopic experience in performance with the Da Vinci robot. They found that computer gaming and chopstick proficiency slightly improved the overall performance of robotic exercises.7

Oculomotor coordination, like other cognitive skills, can be trained and improved, and this intersects with surgical technique. Most hand movements require visual guidance; fine motor skills control the movements of small hand muscles, coordinated with visual cues. Simulators designed for developing oculomotor skills vary from simple setups to complex virtual reality systems, directly enhancing skills and academic training.

Developing oculomotor skills involves practice and training that coordinates eye movements with hand movements. This skill development typically begins in childhood, but certain activities can neurologically strengthen it. Studies have shown that playing video games, practicing musical instruments, and engaging in activities like sewing or knitting enhance the brain’s ability to process visual information and translate it into precise muscular movements. Furthermore, repetitive practice in controlled environments allows the nervous system to refine neuromotor connections, thereby improving the precision and coordination required for complex tasks such as robotic surgery.

However, there are no recent studies to determine activities that could enhance oculomotor skills for robotic surgery. The aim of this study was to compare the performance of experienced robotic surgeons with that of non-robotic surgeons, as well as to analyze non-surgical skilled activities such as playing musical instruments, video game playing, and knitting, under the assumption that these activities develop oculomotor skills. We investigated the performance of these groups on various tasks using the Da Vinci skills simulator, focusing on instrument manipulation, oculomotor coordination, and precision maneuvers.

METHODS AND MATERIALS

This prospective study included 80 volunteers. Medical participants were recruited from Hospital Ángeles de Puebla and the non-medical participants were invited by email from the Universidad Anáhuac Puebla. The volunteers were categorized into five groups: robotic surgeons, non-robotic surgeons, individuals engaged in activities such as video gaming, playing a musical instrument, or knitting, and individuals without the mentioned skills. Demographic data including age, sex, scholar degree, surgical experience, and experience in robotic surgery were collected using Google Forms. The survey also included questions regarding participants’ skills. After answering the survey, participants performed a simulation exercise using the dVSS. This exercise focused on EndoWrist manipulation, requiring participants to manipulate robotic arms to touch a red ball inside a crystal sphere that changed orientation, challenging participants at various angles. Participants then rated the difficulty of the simulation exercise on a scale from easy to very hard. Performance metrics within the dVSS were analyzed, including task completion time, motion distance, instrument collisions, excessive instrument force, instrument out of view, and missed targets. Metrics compared across groups included average task completion time, success rate, and overall penalty rate.

Statistical analysis was conducted using GraphPad Dotmatics software. Descriptive statistics were used, and a one-way ANOVA test for differences among more than two groups, while the t-test compared differences between two groups. A of p ≤ 0.05 was considered statistically significant.

Ethical approval for this study was obtained from the institutional review board of Hospital Ángeles de Puebla. Informed consent was obtained from all participants, outlining the study’s purpose, potential risks, and benefits, and participants’ rights to anonymity.

RESULTS

In our initial analysis, we examined the demographic data of the participants. The participants ranged in age from 18 to 65 years, with a mean of 36.4 ± 26 years. To evaluate the skill related to age, the group was divided into 3 groups, younger than 30 years (n = 54), between 30 and 50 years (n = 23), and older than 50 years (n = 3). Statistical analysis using one-way ANOVA revealed significant differences among the age groups in terms of general scores (p=0.04), success rate (p=0.0005), and penalties (p=0.0003). However, no significant differences were found in time spent and in the glass movement (Table 1). We compared the performance between males (n = 39) and females (n = 41). Statistical analysis showed no significant differences between both groups in terms of overall scores, time spent, glass movement, success rate, and penalties (Table 2).

Table 1.Age distribution, and the performance metrics of the participants using the dVSS.
≤ 30
(n = 54)		 30 – 50
(n = 23)		 ≥ 50
(n = 3)
Overall score 38.1 ± 23-1 33.9 ± 31 0.3 ± 0.5
Time spent (seconds) 176.7 ± 87.4 161 ± 70.8 238.8 ± 74.5
Glass movement (cm) 3.6 ± 5.6 1.1 ± 1.7 7.8 ± 8.5
Success rate (5) 95 ± 8.8 94.2 ± 8.4 73.3 ± 15.2
Overall penalty rate (points) -4.3 ± 5.4 -4.4 ± 5.3 -18 ± 7.2
Table 2.Performance metrics between gender groups using the dVSS.
Male
(n = 39)		 Female
(n = 41)
Overall score 34.4 ± 26 38.2 ± 26.2
Time spent (seconds) 163.1 ± 46.9 182.2 ± 102
Glass movement (cm) 2.5 ± 3.7 3.9 ± 5.9
Success rate (5) 94.8 ± 10.2 93.4 ± 9.3
Overall penalty rate (points) -4.4 ± 6.7 -5.1 ± 5.2

After comparing the general data of the group, we divided it according to its abilities as mentioned in the methodology into five groups, the first analysis was the comparison between surgeons (n = 24) and non-surgeons (n = 56), the t-test results indicated no significant difference between both groups in terms of, time spent, glass movement, and success rate and only significant differences were observed in the overall score (p = 0.05) and the penalties score (p=0.02) (Table 3).

Table 3.Performance metrics between Surgeons and Non-surgeons using the dVSS.
Surgeons
(n = 24)		 Non-Surgeons
(n = 56)
Overall score 43.8 ± 25.6 37 ± 25.8
Time spent (seconds) 148.7 ± 38.9 183.3 ± 90.7
Glass movement (cm) 1.7 ± 3.5 3.9 ± 5.4
Success rate (5) 97 ± 4.6 92.8 ± 11
Overall penalty rate (points) -2.5 ± 3.4 -5.8 ± 6.5

The analysis of the comparison between the group with surgical experience using the Da Vinci system and the group without such experience revealed significant differences between the groups in terms of the overall score (p=0.05), glass movement (p=0.03), the success rate (p=0.03), and penalties (p=0.01), with the experienced group performing better in these aspects. There were no significant differences in time spent between both groups (Table 4).

Table 4.Results of performance metrics between the group with experience with the Da Vinci robot and the group without experience with the Da Vinci using the dVSS.
Da Vinci Surgeons
(n = 11)		 Non Da Vinci Surgeons
(n = 13)
Overall score 47.1 ± 28.9 39.7 ± 25
Time spent (seconds) 135.9 ± 49.6 148.7 ± 38.9
Glass movement (cm) 0.6 ± 0.6 1.7 ± 3.5
Success rate (5) 99.2 ± 2.7 97 ± 4.6
Overall penalty rate (points) -1 ± 1.7 -2.5 ± 3.4

In our analysis, we examined participants who frequently performed surgeries with the Da Vinci robot, categorizing them based on the number of surgeries performed. We compared the performance between those who had performed less than 10 surgeries with the Da Vinci robot (n = 4) and those who have performed 10 or more surgeries (n = 3). Statistical analysis using a t-test indicated no significant differences between the two groups in terms of overall scores, time spent, glass movement, success rate, and penalties.

Finally, we analyzed the non-Da Vinci surgeons compared to the participants engaged in specific activities (playing video games, knitting, playing a musical instrument), and a group of individuals without the mentioned skills. The results indicated that there were no significant differences in overall scores and success rates among the groups engaged in specific activities. However, significant differences were observed in the time spent (p=0.04), glass movement (p=0.04), and penalties (p=0.05). The analysis showed that individuals who practiced these activities obtained a better overall score than those who were surgeons without experience in the Da Vinci, with a particularly significant difference in the overall scores when compared exclusively to the group that knitted (Table 5).

Table 5.Results of performance metrics between the groups of participants who are engaged in different activities, non Da Vinci surgeons.
Video gaming
(n = 20)		 Knitting
(n = 8)		 Musical instruments
(n = 11)		 Control
(n = 17)		 Non Da Vinci Surgeons
(n = 13)
Overall score 42.3 ± 26.8 43.8 ± 29.5 41.2 ± 26.1 24.2 ± 19.7 39.7 ± 25
Time spent (seconds) 155.5 ± 72.2 157.8 ± 52.4 168.1 ± 45.6 214.4 ± 143.1 180.1 ± 85.3
Glass movement (cm) 2.7 ± 4.5 2.2 ± 1.5 2.6 ± 3.7 5.7 ± 8.5 3.7 ± 5.3
Success rate (5) 92.8 ± 12.6 96.4 ± 9,9 95.8 ± 8.8 90 ± 9.3 93.1 ± 10.3
Overall penalty rate (points) -3.7 ± 7.8 -3.1 ± 5.2 -3.7 ± 5.5 -7.7 ± 5 -5.5 ± 6.2

DISCUSSION

The results of this study provide valuable insights into the factors influencing performance in robotic surgery using the dVSS. Despite research suggesting that age and prior surgical experience might predict performance outcomes, our findings indicate a more nuanced relationship between these factors and robotic surgery.8 Our study demonstrated significant differences among different age groups, with younger participants outperforming older ones. This supports previous findings by Meier et al. and Tillou, suggesting that younger individuals may adapt more quickly to the technical demands of robotic surgery. The lack of significant differences in time spent and glass movement, however, implies that while younger participants might achieve higher scores and success rates, their overall efficiency and precision in movement might not differ substantially from older participants.

When comparing surgeons and non-surgeons, significant differences were observed in overall scores and penalties, with surgeons performing better. This suggests that surgical experience contributes to higher scores and fewer mistakes, highlighting the importance of prior surgical training. However, non-surgeons engaged in activities such as video gaming, knitting, and playing musical instruments showed significant differences in time spent, glass movement, and penalties, indicating that these activities may enhance specific skills beneficial to robotic surgery. Participants with experience using the Da Vinci system showed better performance in terms of glass movement, success rate, and penalties suggesting that familiarity with the robotic system enhances specific aspects of performance. The analysis of non-surgeon participants engaging in activities like video gaming, knitting, and playing musical instruments revealed significant differences in time spent, glass movement, and penalties. These findings suggest that activities requiring fine motor skills and oculomotor coordination can positively influence performance in robotic surgery. However, no significant differences in the overall scores and success rates imply that these activities might enhance specific skills rather than overall performance.

The findings underscore the importance of incorporating diverse training modules in robotic surgery programs. Given that younger participants and those engaged in specific activities like knitting showed better performance in certain aspects, training programs might benefit from including exercises that mimic these activities to develop fine motor skills and oculomotor coordination. This study highlights the complexity of factors that contribute to proficiency in robotic surgery. Tailored training programs that consider age, leverage fine motor skill activities, and provide ample hands-on experience with the Da Vinci system are crucial for developing highly skilled robotic surgeons. Further research should aim to validate these findings in larger, more diverse populations and explore additional activities that could further enhance surgical training outcomes.9,10

These findings challenge conventional assumptions and imply that non-surgical activities, such as knitting, may have unexpected benefits in enhancing performance in surgical simulations. In summary, the study reveals intriguing insights into the potential influence of non-surgical activities on surgical performance. Further research with a larger and more diverse sample size and a deeper exploration of relevant variables can provide valuable insights into skill acquisition, skill transferability across domains, and optimization of surgical training programs for enhanced performance and patient outcomes.

CONCLUSIONS

The results of this study highlight the influence of factors affecting performance on the Da Vinci robotic simulator, emphasizing the importance of both innate and developed manual skills. Age emerged as a significant determinant, with younger participants demonstrating better results. Previous experience with the Da Vinci system strongly correlated across metrics with better performance, showing the value of hands-on experience in mastering robotic surgical skills. It is noteworthy that participants who knit achieved comparable results to experienced surgeons; those who play instruments and video games also performed very well.

These findings suggest an opportunity to integrate non-surgical manual skill activities into surgical training programs before the Da Vinci Skills Simulator to potentially accelerate the acquisition of fine motor skills, while offering accessible options for robotic surgery training.

ACKNOWLEDGMENTS

We gratefully acknowledge Cyber Robotics for providing the Da Vinci Simulator, which was essential for conducting this study.