The Impact of Novel Nontechnical Stressors (Visual and Auditory) on Simulated Laparoscopic Task Performance Among Surgeons and Students.

Background: Surgical training emphasizes technical competence. Growing evidence indicates that nontechnical skills are also significant in determining performance. Critically, surgeons should be aware how performance is affected by pressure or distraction. We assessed the impact of novel auditory and visual stressors on performance during a simulated laparoscopic task. We hypothesized that the stressors would worsen performance, and that stress-induced diminution in performance would be inversely related to surgical experience. Methods: Twenty participants (10 surgeons and 10 medical students) completed a peg-threading task using a laparoscopic simulator: three times under control conditions, next with a visual distraction overlay (progressive red saturation of the surgical field, timing personalized to the user's index performance), and then with an auditory distraction overlay (operating theater environment noise). Task completion time and instrument tracking metrics (instrument tip distance traveled and instrument smoothness) were measured. Results: Under control conditions, surgeons completed the task significantly faster, with greater economy of movement, and improved instrument smoothness-compared with students. When exposed to distracting stimuli, the groups behaved differently. Surgeons completed the task more slowly, instrument movements became less smooth (significantly so under audio distraction conditions), but total distance traveled by instruments was unchanged. By contrast, student performance was not impaired and, in some ways, improved. Conclusion: The impact of visual and auditory distraction on surgical performance can be modeled in a laparoscopic simulation environment. The effect of distraction varies according to expertise. This environment may be an effective setting within which to learn to mitigate stress-induced diminution in performance.

Using Automated Continuous Instrument Tracking to Benchmark Simulated Laparoscopic Performance and Personalize Training.

OBJECTIVE: Laparoscopic simulation is widely used in surgical training. However, the impact of training on performance is difficult to assess. Observation is time-intensive and subjective. SurgTrac laparoscopic box-trainer instrument tracking software provides continuous, automated, real-time, objective performance feedback. We used this data to assess the relationship between task attempts and performance. We assessed whether improvement in performance with repetition could be modeled in learning curves that might be used for benchmarking. DESIGN: Anonymized SurgTrac data for performances undertaken between 10/2016 and 05/2019 were retrospectively extracted. The thread transfer task, a basic instrument handling task, was assessed. Task duration and instrument-based metrics were analyzed; total distance travelled by instrument tips, average speed, average acceleration, and the ratio of movements between the left and right hands. Curve estimation regression was used to assess the relationship between attempt number and metrics for pooled data across the entire cohort of users and amongst individual users with ≥50 attempts. Threshold for significance p = 0.05. SETTING: SurgTrac has generated the largest available database of performances in box trainer simulated tasks with 64,000 activities performed by over 1450 users in 77 countries to date. PARTICIPANTS: Data was derived from the unselected world-wide cohort of SurgTrac users. No participants were excluded. RESULTS: Five hundred seventy-eight users performed 13,027 attempts in the thread transfer task. Across the entire cohort, SurgTrac performance metrics were significantly associated with attempt number. Task duration and total distance decreased with attempt number. This benefit persisted across 100 attempts. Ambidexterity increased with attempt number. Individual candidate performance improved in line with predicted learning curves for better performing candidates. CONCLUSIONS: We analyzed the largest database of simulated laparoscopic task performances. Performance improves with practice. Using learning curves derived from peer-group performances as benchmarks, users may be regularly and objectively assessed to support personalization of training.