How Does Task Loading in a PICU Environment Impact on Clinician Situational Awareness and Awareness of the Passage of Time?

There is little published literature on the subject of clinician perception of trends in patient observations on PICUs (Paediatric Intensive Care Units) and how this situational awareness is impacted on by clinical tasks. Human factors training cautions against the loss of situational awareness and time perception but there is no supporting observational data in the IC (Paediatric Intensive Care) setting.

Perceptual loading theory hypothesises that, under low load situations, awareness extends to environmental features not directly related to the task at hand. However in high load situations awareness is restricted to the object of focused attention. Individuals experience different load from a given task depending on their skills and experience.

Our pilot project intends to examine how clinician perception is affected by task loading. In our protocol two tasks are undertaken. The administrative task involves requesting a list of investigations from a clinical guideline. The technical task is the uncomplicated insertion of a central venous catheter (CVC) into a simulated vein. In each case the investigators will record proxies for perception: awareness of the passage of time, the time point at which monitoring changes are noted and retrospective recall of observation trends. Our protocol was designed with psychology input from Prof. Nilli Lavie, group leader of the UCL Attention & Cognitive Control laboratory.

Passage of time is measured by the participant pressing a foot pedal linked to timing software at every perceived 10 second interval of elapsed time. A retrospective estimate of total elapsed time will also be recorded. After the second task, immediate verbal questions are asked followed by a written questionnaire which contains questions targeting the participant's awareness of monitoring changes.

Analysis will involve paired t testing of the timing interval and observation trend data to see if task loading significantly impacts accuracy.