Abstract

Abstract Introduction Surgeons strive to continually enhance performance. Currently, assessment relies on subjective, retrospective methods-hindering real-time improvement and error prevention. Learning from sports, surgeons can utilise surgical sabermetrics for data-driven analysis. Cognitive load(CogL) impacts performance, with overload impairing skills and judgement. Sabermetrics can be leveraged to measure CogL objectively(e.g.Electrodermal activity(EDA)) and subjectively. This study aimed to combine these measures and explore their relationship with surgeon factors and patient outcomes. Methods Fourteen surgeons conducting 58 benign surgery cases participated. Surgeons’ intraoperative EDA was captured using a digital sensor. Subjective data collected included (i)Surgery Task-Load-Index(SURG-TLX)), (ii)mood, (iii)sleep-disturbance and (iv)risk-aversion. EDA underwent decomposition into (a)tonic (background autonomic arousal) and (b) phasic(response to events) components. Patient outcomes included (i)30-day morbidity and (ii)case difficulty. Results Overall, mean phasic-EDA was 0.038μS and mean tonic-EDA was 0.483μS(ranges 0-1:1 indicating highest CogL). Mean SURG-TLX was 47.128(/120, where 120 is the highest workload). Negative mood related to changes in tonic-EDA(p<0.05,F=11.84). EDA climbed throughout each case (Tonic:p<0.05,F=2.035;Phasic:p<0.05,F=1.626). SURG-TLX were weakly correlated with sleep(p<0.05,ϱ=-0.273) and moderately correlated with case duration(p<0.05, ϱ=0.598), but not EDA(p>0.50). Discussion This study is the first in the UK to report combined CogL measures gathered during live surgery. Awareness of factors that affect CogL crucially allows for the management of factors to prevent overload and to inform targeted interventions for performance improvement. Using digital sensors to measure CogL provides opportunity for automated, real-time performance assessment, advanced feedback, and behavioural modifications.

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