Systematic review of measurement tools to assess surgeons’ intraoperative cognitive workload. BJS 2018; 105: 491-501.
Published: 21st February 2018
Authors: R. D. Dias, M. C. Ngo‐Howard, M. T. Boskovski, M. A. Zenati, S. J. Yule
Surgeons in the operating theatre deal constantly with high‐demand tasks that require simultaneous processing of a large amount of information. In certain situations, high cognitive load occurs, which may impact negatively on a surgeon's performance. This systematic review aims to provide a comprehensive understanding of the different methods used to assess surgeons' cognitive load, and a critique of the reliability and validity of current assessment metrics.
A search strategy encompassing MEDLINE, Embase, Web of Science, PsycINFO, ACM Digital Library, IEEE Xplore, PROSPERO and the Cochrane database was developed to identify peer‐reviewed articles published from inception to November 2016. Quality was assessed by using the Medical Education Research Study Quality Instrument (MERSQI). A summary table was created to describe study design, setting, specialty, participants, cognitive load measures and MERSQI score.
Of 391 articles retrieved, 84 met the inclusion criteria, totalling 2053 unique participants. Most studies were carried out in a simulated setting (59 studies, 70 per cent). Sixty studies (71 per cent) used self‐reporting methods, of which the NASA Task Load Index (NASA‐TLX) was the most commonly applied tool (44 studies, 52 per cent). Heart rate variability analysis was the most used real‐time method (11 studies, 13 per cent).
Self‐report instruments are valuable when the aim is to assess the overall cognitive load in different surgical procedures and assess learning curves within competence‐based surgical education. When the aim is to assess cognitive load related to specific operative stages, real‐time tools should be used, as they allow capture of cognitive load fluctuation. A combination of both subjective and objective methods might provide optimal measurement of surgeons' cognition.Full text
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