Perceptions of cognitive workload measurement using multimodal sensors in surgery

Abstract

BackgroundThe study of cognitive load management in surgery has led to identification of objective cognitive workload (CWL) correlates offering the potential to improve patient safety, enhance surgeon performance and their long-term well-being. Sensors have been used in isolation within surgery to measure physiological changes of the surgeon to infer CWL. More recently however, the use of multimodal sensors (MMS) has been explored to improve the reliability of CWL measurement. Despite the emergence of this technology, the behavioural intention of future users of MMS is not well understood. The aim of this study is to explore the perceptions of CWL measurement using MMS in surgery and secondly, to develop a model of acceptance amongst a cohort of future users.MethodsA cross-sectional survey of medical students in the United Kingdom was undertaken by means of an online questionnaire based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, using performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC) and behavioural intention (BI) as latent constructs. A purposive sampling method was undertaken over a period of nine months. Results were analysed using structural equation modelling.ResultsThere were 232 responses with 138 fully completed responses used for final data analysis. Weighted averages of all item responses demonstrated positive responses to all questionnaire statements. Students strongly agreed to ‘Technology used to measure my mental workload would be useful to me’ (42.8%), ‘I would use the system if it was comfortable to wear’ (53.6%) and ‘I would like to know that the technology is reliable before using it’ (68.8%). Pathway co-efficients were 0.444 for PE → BI (p = < 0.001), 0.221 for EE → BI (p = < 0.001), 0.096 for SI → BI (p = 0.186) and 0.142 for FC → BI (p = 0.094).ConclusionThis study demonstrates an overall positive perception of CWL measurement using MMS. Although social influences and facilitating conditions demonstrate a positive influence on the behavioural intention of students, performance and effort expectancy are significant constructs to consider, namely the comfort and reliability of multimodal sensors. Findings from this study can be used to guide future development of emerging MMS systems that can be used to reduce human error, improve training and patient safety.