Stress and Surgical Performance

Project summary

Background

Safe surgical practice requires a combination of technical and non-technical skills. Acute stress can impair both sets of skills, thereby compromising both surgical performance and patient safety in the operating theatre.

This project uses a systematic and scientific analysis to investigate stress in surgeons with the global aim of developing a practical, evidence-based intervention to reduce stress and its deleterious consequences.

Aims

A number of related studies have been carried out, aiming to:

1. Identify the key stressors that impact upon surgical performance
2. Identify surgeons’ requirements from a stress management training intervention
3. Develop and validate the Imperial Stress Assessment Tool (ISAT) to measure stress in surgery
4. Develop and validate an intervention taken from sports science, based on the concept of “mental practice” (i.e., the mental rehearsal of a task in the absence of relevant physical action) that enhances surgical skill and reduces stress levels
5. Demonstrate quantitative improvements in surgical performance after using the intervention through a RCT set in a high fidelity simulated operating theatre

Methods

A range of methods and approaches have been used within this project including:

• Standardised systematic review methodology to identify the impact of stress on surgical performance
• Qualitative methodology (eg interviews and ethnographic observations) to elicit surgeons’ stressors and coping strategies in the operating theatre alongside their training needs.
• Quantitative methodology to develop and validate stress assessment tools and to assess the quality of the surgeons’ mental imagery processes
• Randomised controlled trial (RCT) methodology to test the efficacy of a stress management and performance enhancement intervention (mental practice) in a simulated operating theatre

Outputs

Stress and Surgical Performance outputs (PDF)

External collaborators

Professor Aidan Moran, University College Dublin